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Tweets for AI and Machine Learning in Clinical Trials April 12th, 2018 hosted at Pfizer’s Innovation Research Lab in Cambridge, MA @AVIVA1950 @pharma_BI

 

 

 

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Electronic Scientific AGORA: Comment Exchanges by Global Scientists on Articles published in the Open Access Journal @pharmaceuticalintelligence.com – Four Case Studies

Curator and Editor-in-Chief: Journal and BioMed e-Series, Aviva Lev-Ari, PhD, RN

 

Introduction

Case Study #1: 40 Responses

  • Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?

Author: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/10/17/is-the-warburg-effect-the-cause-or-the-effect-of-cancer-a-21st-century-view/

Case Study #2: 26 Responses

·      Knowing the tumor’s size and location, could we target treatment to THE ROI by applying…..

Author: Dror Nir, PhD

https://pharmaceuticalintelligence.com/2012/10/16/knowing-the-tumors-size-and-location-could-we-target-treatment-to-the-roi-by-applying-imaging-guided-intervention/

Case Study #3: 24 Responses

  • Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/12/01/personalized-medicine-cancer-cell-biology-and-minimally-invasive-surgery-mis/

Case Study #4: 13 Responses

  • Judging the ‘Tumor response’-there is more food for thought

https://pharmaceuticalintelligence.com/2012/12/04/judging-the-tumor-response-there-is-more-food-for-thought/

Conclusions

 

Introduction

Members of our Team published 5,295 articles, in the period between 4/2012 to 4/10/2018, and engaged in Comment Exchanges with Global Scientists Online. 1,412,106 eReaders had viewed our articles and 7,283 scientific comments are included in the Journal Archive.

Team Members’ Profile

Team Profile: DrugDiscovery @LPBI Group – A BioTech Start Up submitted for Funding Competition to MassChallenge Boston 2016 Accelerator

In our Scientific Agora: Multi Scientific Comment exchanges between Global e-Readers Scientists and LPBI’s Scientists/Experts/Authors/Writers take place. In this curation I am presenting four articles that generated dozens of scientific comments and multifaceted exchanges.

The Voice of Aviva Lev-Ari, PhD, RN:

It is my strongest conviction on the merit of the following features of Global SHARING the Scientific product, aka “An Article written by a Scientist” in the Digital Scientific Publishing Age:

  • Every new article published in Open Access Journals contributes to mitigate the most acute challenge of the e-Scientific Publishing industry today: Information Obsolescence – the newness of findings
  • Every new article published in Open Access Journals contributes AND in the Subscription-based Journals contributes to the second most acute challenge of of the e-Scientific Publishing industry today: Information Explosion – the volume of findings
  • The Scientific Agora as presented, below, in four Case Studies is an optimal means for Global SHARING in Real Time scientific knowledge deriving from clinical expertise and lab experience of all the participants in the Agora. REAL TIME means minimization of the negative impact of the most acute challenge of of the e-Scientific Publishing industry today: Information Obsolescence 
  • Knowledge SHARING of our Scientists articles occurs among two FORUMS:

Forum One, is the Scientists that joined the comment exchanges between the Article Author and other members of our Team on a given Scientific product, aka “An Article written by a Scientist”

Forum Two, is the Global Universe of Scientists that (a) are e-mail Followers opting to our Open Access Journal free subscription and (b) eReaders of our Journal that did not yet opt to follow the Journal by e-mail, a robust crowd of +1.4 Million Scientists

  • We mitigate the negative impact of the second most acute challenge of the e-Scientific Publishing industry today: Information Explosion by our own developed and advanced achievements reached in the practice of
  1. Development of the Methodology for Curation of Scientific Findings, Curation of Scientific Content @Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Boston
  2. Application of the Methodology for Curation of Scientific Findings in a BioMed e-Series of 16-Volumes in Medicine and Life Sciences on Amazon.com

electronic Table of Contents (eTOCs) of each Volume in the SIXTEEN Volume BioMed e-Series

WE ARE ON AMAZON.COM

https://www.amazon.com/s/ref=nb_sb_noss?url=search-alias%3Ddigital-text&field-keywords=Aviva+Lev-Ari&rh=n%3A133140011%2Ck%3AAviva+Lev-Ari

Commentaries on each Volume’s Contribution to Medical Education by L.H. Bernstein, MD, FCAP and by Aviva Lev-Ari, PhD, RN – BioMedical e-Books e-Series: Multiple Volumes in Five e-Series

https://pharmaceuticalintelligence.com/biomed-e-books/commentaries-on-each-volumes-contribution-to-medical-education-by-l-h-bernstein-md-fcap-and-aviva-lev-ari-phd-rn-biomedical-e-books-e-series-multiple-volumes-in-five-e-series/

In 2016, LPBI’s BioMed e-Series was Submitted for Nomination for 2016 COMMUNICATION AWARD FOR EXCELLENCE IN REPORTING SCIENCE, MEDICINE AND ENGINEERING – Reference #: 9076095, on 1/27/2016

https://pharmaceuticalintelligence.com/biomed-e-books/

  • Lastly, It is my strong belief that the Methodology of Curation will become a major tool used in Content creation for Curriculum Development in Medical Schools, in the Life Sciences and Healthcare Allied professions.
  • We have pioneered and showed the way BY EXAMPLE, +5,200 Scientific products, aka “An Article written by a Scientist” constitute our Journal Archive created by content curation
  • More New e-Book Titles are coming in 2018-2019 in LPBI’s BioMed e-Series.
  • More e-Scientific Publishers will use the Methodology of Creation of electronic Table of Contents of e-Books by combing Archives by very experienced subject matter Editors.
  • Global SHARING of Information became best practice for Academic Course Contents in the last ten years
  • On-Line Degrees are spreading in many disciplines and are offered by very many colleges, including the Ivy League
  • Open Access Scientific Journals is the FUTURE of the e-Scientific Publishing Industry.

 

Case Study #1:

  • Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?

Author: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/10/17/is-the-warburg-effect-the-cause-or-the-effect-of-cancer-a-21st-century-view/

40 Responses

  1. This is OUTSTANDING.

    Now we need a “shortcliff” post to follow one chart that traces the dynamic process, no reader shall get lost inside any of the process boxes.

  2. Really nice overview and very interesting metabolic changes.
    However, related to the title, the cancerous changes- event always comes first before lactate preferred metabolism comes into place. Right?

  3. This is what has been inferred. So if that is the premise, then the mutation would be the first event. That position has been successfully challenged and also poses a challenge to the proper view of genomic discovery. The real event may very well be the ongoing oxidative stress with aging, and decreased physiochemical reserve.

    I haven’t developed the whole picture. Nitric oxide and nitrosylation contribute to both vascular relaxation and vasoconstriction, which is also different in major organs. The major carriers of H+ are NADH and FADH2. Electron transport is in the ETC in mitochondria. I called attention to the “escape” of energy in aerobic glycolysis. As disease ensues, it appears that lactate generation is preferential as the mitochondrion takes up substrate from gluconeogenesis. Whether it is an endotoxic shock or a highly malignant fast growing tumor, the body becomes trapped in “autocatabolism”. So the tumor progresses, apoptosis is suppressed, and there is a loss of lean body mass.
    All of this is tied to genetic instability.

    We see the genetic instability as first because of the model DNA–RNA–protein. We don’t have a map.

  4. It is a very nice report. I did work for a short time to develop compounds to block the glucose uptake especially using glucose-mimics. I wonder is there any research on this area going on now?

  5. Thanks. I have been researching this exhaustively. There are even many patents trying to damp this down. You were on the right track. The biggest problem has been multidrug resistance and tumor progression.

  6. […] Is the Warburg Effect the cause or the effect of cancer: A 21st Century View? (pharmaceuticalintelligence.com) […]

  7. […] Is the Warburg Effect the cause or the effect of cancer: A 21st Century View? (pharmaceuticalintelligence.com) […]

  8. Martin Canizales • Warburg effect (http://www.cellsignal.com/reference/pathway/warburg_effect.html), is responsible of overactivation of the PI3K… the produced peroxide via free radicals over activate the cyclooxigenase and consequently the PI3K pathway activating there, the most important protein-kinase ever described in the last mmmh, 60-70 years? maybe… to broke the Warburg effect, will stop the PI3K activation (http://www.cellsignal.com/reference/pathway/Akt_PKB.html) then all the cancer protein related with the generation of tumor (pAKT,pP70S6K, Cyclin D1, HIF1, VEGF, EGFrc, GSK, Myc, etc, etc, etc), will get down regulation. That is what happen, when I knock down the new protein-kinase in pancreatic cancer cell lines… stable KD of pancreatic cancer cell lines divide very-very-veeeery slow (by Western blotting, cyclin D1 disapear, VEGF, HIF1a, MyC, pAKT, pP70S6K, GSK, and more and more also has, very-very few consume of glucose [diabetes and cancer]. Stable cells can be without change the media for 3 weeks and the color doesn’t change, cells divide but VERY slow and are alive [longevity]) are not able to generate xenograft tumors related, to scramble shRNA stable cell lines. When, we broke the warburg effect, the protein kinase get’s down as well all the others. Is the same, with bacteria infections…. bacteria infections, has many things to teach us about cancer and cell proliferation (http://www.ncbi.nlm.nih.gov/pubmed/22750098)

  9. edit this on November 12, 2012 at 5:41 PM | Replyhijoprodigoendistancia

    research paper, should be ready (writing) very soon and must be submmited before end this year. Hee hee! you know… end of the world is in December 21 2012

    • The emphasis on p13 and the work on pancreatic cancer is very interesting. I’ll check the references you give. The Warburg effect is still metabolic, and it looks like you are able to suppress the growth of either cancer cells or bacteria. The outstanding question is whether you can get a head start on the SIR transition to sepsis to severe sepsis to MODS, to shock.

      It looks like an article will be necessary after your work is accepted for publication. Thanks a lot for the response.

  10. edit this on November 12, 2012 at 8:52 PM | Replyhijoprodigoendistancia

    Also, when this protein-kinase is over expressed… UCP1 get down..then, less mitochondria, consequently less aerobic cell functions…in adipose tissue, less mitochondria promote the differentiation of BAT (Brown Adipose Tissue) to, WAT (White Agipose Tissue). Has relation with AS160 phosphorylation, Glut4 membrane translocation, promote the GABA phosphorylation (schizophrenia-autism), neuronal differentiation (NPCs:Neural Progenitor Cells), dopaminergic cell differentiation….

  11. edit this on November 12, 2012 at 8:55 PM | Replyhijoprodigoendistancia

    Larry, all comments are part of the second paper.

  12. […] Is the Warburg Effect the cause or the effect of cancer: A 21st Century View? […]

  13. […] Is the Warburg Effect the cause or the effect of cancer: A 21st Century View? […]

  14. Larry please take a look at Gonzalez et al. The Bioenergetic theory of Carcinogenesis. Med Hypotheses 2012; 79: 433-439 and let me know your thoughts.

  15. […] The Initiation and Growth of Molecular Biology and Genomics, Part I […]

  16. […] Is the Warburg Effect the cause or the effect of cancer: A 21st Century View? […]

  17. edit this on May 22, 2013 at 11:36 PM | ReplyAashir Awan, Phd

    Informative article especially concerning activation of HIF under normoxic conditions. Recently, a paper has come out showing patients showing symptoms of mood disorder having increased expression of Hif1a. Also, there are reports that Hif1a is important in development of certain tissue types.

  18. COLOURS AND LIFE. The basic idea of this theory is that the oxidation of hydrogen and carbon atoms, arising from the degradation of carbohydrates, is by two distinct processes based on oxidation-reduction electron transfer and photochemical process of energy release on the basis of color complementary, predominance of one or another depending on intracellular acid-base balance. I can not understand why nobody wants to do this experiment. I’m sure this assumption hides a truth. Before considering it a fiction to be checked experimentally. I would like to present a research project that concerns me for a long time that I can not experience myself.
    Involuntarily, after many years of searching, I have concluded that in the final biological oxidation, in addition to the oxidation-reduction electron transfer occurs photo-chemical process, accordance to the principle of color complementary energy transfer. I imagine an experiment that might be relevant (sure it can be improved). In my opinion, if this hypothesis proves true, one can control the energy metabolism of the cell by chromotherapy, as the structures involved are photosensitive and colorful. I would be very happy if this experiment were done under your leadership. Sincerely yours Dr. Viorel Bungau

    INNER LIGHT – LIGHT OF LIFE.
    CHROMOTHERAPY AND THE IMPLICATIONS IN THE METABOLISM OF THE NORMAL AND NEOPLASTIC CELL. “Chlorophyll and hemoglobin pigments of life porphyrin structure differs only in that chlorophyll is green because of magnesium atoms in the structure, and hemoglobin in red because of iron atoms in the structure. This is evidence of the common origin of life.” (Heilmeyer) We propose an experiment to prove that the final biological oxidation, in addition to its oxidation-reduction, with formation of H2O and CO2, there is a photochemical effect, by which energy is transferred from the H atom, or C, process is done selct, the colors, complementary colors on the basis of the structures involved are colored (red hemoglobin Fe, Mg chlorophyll green, blue ceruloplasmin Cu, Fe cytochrome oxidase red, green cytochrome oxidase with Cu etc.). The basic idea is that if life pigments (chlorophyll, hemoglobin, cytochromes), which provides energy metabolism of the cell, are colored, we can control their activities through chromotherapy, on the basis of complementary color and energy rebalance the body, with a figured X- body-colored-ray.
    In my opinion, at the basis of malign transformation is a disturbance of energetical metabolism, which reached a level that cell can not correct (after having succeeded before, many times), disturbance that affects the whole body in different degrees and requires corection from outside starting from the ideea that the final biological oxidizing takes place through photochemical process with releasing and receieving energy. “Duality of cytochrome oxidase. Proliferation (growth) and Differentiation (maturation) cell.” Cytochrome oxidase is present in two forms, depending on the context of acid-base internal environment : 1.- Form acidic (acidosis), which contains two Iron atoms, will be red, will absorb the additional green energy of the hydrogen atom, derived from carbohydrates, with formation of H2O, metabolic context that will promote cell proliferation. 2.-Form alkaline (alkalosis), containing two copper atoms, will be green, will absorb the additional red energy of the carbon atom, derived from carbohydrates, with formation of CO2, metabolic context that will promote cell differentiation. Cytochrome oxidase structure has two atoms of copper. It is known that in conditions of acidosis (oxidative potential), the principle electronegativity metals, copper is removed from combinations of the Iron. So cytochrome oxidase will contain two atoms of iron instead of copper atoms, which changes its oxidation-reduction potential, but (most important), and color. If the copper was green, the iron is red, which radically change its absorption spectrum, based on the principle of complementary colors.
    “Inner Light- Light of Life. Endogenous monochromatic irradiation. Red ferment of Warburg – Green ferment of Warburg.”
    In my opinion, at the basis of malign transformation is a disturbance of energetical metabolism, which reached a level that cell can not correct (after having succeeded before, many times), disturbance that affects the whole body in different degrees and requires corection from outside starting from the ideea that the final biological oxidizing takes place through photochemical process with releasing and receieving energy. If the structures involved in biological oxidation finals are colored, then their energy absorption is made based on the principle of complementary colors. If we can determine the absorption spectrum at different levels, we can control energy metabolism by chromotherapy – EXOGENOUS MONOCHROMATIC IRRADIATION . Energy absorption in biological oxidation process itself, based on complementary colors, the structures involved (cytochromes), is the nature of porphyrins, in combination with a metal becomes colored, will absorb the complementary color, corresponding to a specific absorption spectrum, it will be in – ENDOGENOUS MONOCHROMATIC IRRADIATION.
    This entitles us to believe that: In photosynthesis, light absorption and its storage form of carbohydrates, are selected, the colors, as in cellular energy metabolism, absorption of energy by the degradation of carbohydrates, is also done selectively, based on complementary colors. In the final biological oxidation, in addition to an oxidation-reduction process takes place and a photo-chemical process,based on complementary colors, the first in the electron transfer, the second in the energy transfer. So, in the mitochondria is a process of oxidation of atoms C and H, derived from carbohydrates, with energy release and absorption of its selection (the color), by the structures involved, which is the nature of porphyrins, are photosensitive and colorful, if we accept as coenzymes involved, containing a metal atom gives them a certain color, depending on the state of oxidation or reduction (red ferment of Warburg with iron, all copper cerloplasmin blue, green chlorophyll magnesium, red iron hemoglobin, green cytochrome oxidase with copper, etc.)
    According to the principle electronegativity metals, under certain conditions the acid-base imbalance (acidosis), iron will replace copper in combination , cytocromoxidase became inactive, leading to changing oxidation-reduction potential, BUT THE COLOR FROM GREEN, TO REED, to block the final biological oxidation and the appearance of aerobic glycolysis. In connection with my research proposal, to prove that the final biological oxidation, in addition to an oxidation-reduction process takes place and a photo-chemical process, the first in the electron transfer, the second in the energy transfer.
    I SUGGEST TO YOU AN EXPERIMENT:

    TWO PLANTS, A RED (CORAILLE) LIGHT ONLY, IN BASIC MEDIUM, WITH ADDED COPPER, WILL GROW, FLOWER AND FRUIT WILL SHORT TIME, AND THE OTHER ONLY GREEN LIGHT (TOURQUOISE), IN AN ACID MEDIUM, WITH ADDED COPPER CHELATOR , WHICH GROWS THROUGHOUT WILL NOT GROW FLOWERS AND FRUIT WILL DO.

    CULTURE OF NEOPLASTIC TISSUE, IRRADIATED WITH MONOCHROMATIC GREEN ( TOURQUOISE) LIGHT, IN AN ALKALINE MEDIUM, WITH ADDED COPPER, WILL IN REGRESSION OF THE TISSUE CULTURE.

    CULTURE OF NEOPLASTIC TISSUE, IRRADIATED WITH RED ( CORAILLE) LIGHT, IN AN ACID MEDIUM, WITH ADDED COPPER CHELATOR, WILL LEAD TO EXAGERATED AND ANARCHICAL MULTIPLICATION.
    If in photosynthesis is the direct effect of monochromatic irradiation, in the final biological oxidation effect is reversed. Exogenous irradiation with green, induces endogenous irradiation with red, and vice versa. A body with cancer disease will become chemically color “red”- Acid -(pH, Rh, pCO2, alkaline reserve), and in terms of energy, green (X-body-colored-ray). A healthy body will become chemically color “green”-Alkaline – (as evidenced by laboratory), and in terms of energy, red (visible by X-body-colored-ray). Sincerely, Dr. Viorel Bungau

    -In addition-
    “Life balance: Darkness and Light – Water and Fire – Inn and Yang.”

    Cytochrome oxidase structure has two atoms of copper. It is known that in conditions of acidosis (oxidative potential), the principle electronegativity metals, copper is removed from combinations of the Iron. So cytochrome oxidase will contain two atoms of iron instead of copper atoms, which changes its oxidation-reduction potential, but (most important), and color. If the copper was green, the iron is red, which radically change its absorption spectrum, based on the principle of complementary colors. If neoplastic cells, because acidosis is overactive acid form of cytochrome oxidase (red with iron atoms), which will absorb the additional green energy hydrogen atom (exclusively), the production of H20 , so water will prevail, in Schizophrenia , neuronal intracellular alkaline environment, will promote the basic form of cytochrome oxidase (green with copper atoms), which will oxidize only carbon atoms, the energy absorption of red (complementary) and production of CO2, so the fire will prevail. Drawn from this theory interdependent relationship between water and fire, of hydrogen(H2O) and carbon(CO2) ,in a controlled relationship with oxygen (O2). If photosynthesis is a process of reducing carbon oxide(CO2) and hydrogen oxide(H2O), by increasing electronegativity of C and H atoms, with the electrons back to oxygen, which will be released in the mitochondria is a process of oxidation of atoms C and H, derived from carbohydrates, with energy release and absorption of its selection (the color), by the structures involved, which is the nature of porphyrins, are photosensitive and colorful. It means that matter and energy in the universe are found in a relationship based on complementary colors, each color of energy, corresponding with a certain chemical structure. In my opinion, at the basis of malign transformation is a disturbance of energetical metabolism, which reached a level that cell can not correct (after having succeeded before, many times), disturbance that affects the whole body in different degrees and requires corection from outside starting from the ideea that the final biological oxidizing takes place through photochemical process with releasing and receieving energy. The final biological oxidation is achieved through a process of oxidation-reduction, while a photochemical process, based on the principle of complementary colors, if we accept as coenzymes involved, containing a metal atom gives them a certain color, depending on the state of oxidation or reduction (red ferment of Warburg with copper, all copper cerloplasmin blue, green chlorophyll magnesium, red iron hemoglobin,etc. If satisfied, the final biological oxidation is achieved by a photochemical mechanism (besides the oxidation-reduction), that energy is released based on complementary colors, means that we can control the final biological oxidation mechanism, irreversibly disrupted in cancer, by chromotherapy and correction of acid-base imbalance that underlies this disorder.We reached this conclusions studying the final biological oxidation, for understanding the biochemical mechanism of aerobic glycolysis in cancer. We found that cancer cell, energy metabolism is almost exclusively on hydrogen by oxidative dehydrogenation, due to excessive acidosis , coenzymes which makes carbon oxidation, as dormant (these coenzymes have become inactive). If we accept the nature of these coenzymes chloride (see Warburg ferment red), could be rectivate, by correcting acidosis (because that became leucoderivat), and by chromoterapie, on the basis of complementary colors. According to the principle electronegativity metals, under certain conditions the acid-base imbalance (acidosis), iron will replace copper in combination , cytocromoxidase became inactive (it contains two copper atoms) leading to changing oxidation-reduction potential, BUT THE COLOR FROM GREEN, TO REED, to block the final biological oxidation and the appearance of aerobic glycolysis.

    Malignant transformation occurs by energy metabolism imbalance in power generation purposes in the predominantly (exclusively) of the hydrogen atom of carbon oxidation is impossible. Thus at the cellular level will produce a multiplication (growth) exaggerated (exclusive), energy from hydrogen favoring growth, multiplication, at the expense of differentiation (maturation). Differentiation is achieved by energy obtained by oxidation of the carbon atom can not take, leading to carcinogenesis . The energy metabolism of the cell, an energy source is carbohydrate degradation, which is done by OXIDATIVE DEHYDROGENATION AND OXIDATIVE DECARBOXYLATION , to obtain energy and CO2 and H2O. In normal cells there is a balance between the two energy sources. If cancer cells, oxidation of the carbon atom is not possible, the cell being forced to summarize the only energy source available, of hydrogen. This disorder underlying malignant transformation of cells and affect the whole body, in various degrees, often managing to rebalance process, until at some point it becomes irreversible. The exclusive production of hydrogen energy will cause excessive multiplication, of immature cells, without functional differentiation. Exclusive carbon energy production will lead to hyperdifferentiation, hyperfunctional, multiplication is impossible. Normal cell is between two extremes, between some limits depending on the adjustment factors of homeostasis. Energy from energy metabolism is vital for cell (body). If the energy comes predominantly (or exclusively) by oxidation of the hydrogen atom, green energy, will occur at the structural level (biochemical), acidification of the cellular structures that will turn red, so WE HAVE MORPHOLOGICAL AND CHEMICAL STRUCTURES “RED”, WITH “GREEN” ENERGY. This background predisposes to accelerated growth, without differentiation, reaching up uncontrolled, anarchical. ENERGY STRUCTURE OF THE CELL BODY WOULD BE INN. If necessary energy cell derived mainly by oxidation of the carbon atom, red energy,cell structures will be colored green, will be alkaline(basic), so WE HAVE MORPHOLOGICAL AND CHEMICAL STRUCTURES “GREEN”, WITH “RED” ENERGY, on the same principle of complementarity. This context will lead hyperdifferentiation, hyperfunctional ,maturation, and grouth stops. ENERGY STRUCTURE OF THE CELL BODY WOULD BE YANG. If in photosynthesis, porphyrins chemicals group, whic be photosensitivity (their first feature), shows and a great affinity for metals with chelate forming and becoming colored (pigments of life), can absorb monochromatic light complementary, so if these pigments, which constitutes the group of chromoprotheine, in photosynthesis will achieve CO2 and H2O reduction the recovery of C, H respectively, and the issuance of and release of O, atoms as H and C that reduced the energy load, representing carbohydrates, is in the form of solar energy storage, in cellular energy metabolism, processes necessary life, energy will come from the degradation of substances produced in photosynthesis, the carbohydrates, by oxidative dehydrogenation and oxidative decarboxylation, through like substances, which form chelates with the metals, are colored, metals contained in the form of oxides of various colors(green Mg, red Fe, blue Cu,etc.),suffering from complementary color absorption process of reduction with H in case,if the oxidative dehydrogenation, when chelated metal pigment is red, becoming leucoderivat (colorless) by absorbing complementary color (green) of hydrogen, formation of H2O, or C, if the oxidative decarboxylation when chelated metallic pigment is green, energy absorbing additional, red energy of atom C, CO2 production, the process is identical. The process that lies at base cellular energy metabolism, takes place in the final biological oxidation, reducing the O atom in the form of metal oxide, in combination with photosensitive substance, porohyrin, colorful,absorbing complementary color, will reduce the O atom, with H and C, with the production of H2O and CO2. Green energy release of H atom in the oxidative dehydrogenation process, it is a process of”IRRADIATION MONOCHROMATIC ENDOGENOUS WITH GREEN”, and red energy release of C atom in the oxidative decarboxylation process, consists in an “IRRADIATION MONOCHROMATIC ENDOGENOUS WITH RED”. Porphyrin-metal combination in photosynthesis, the chelated form, by absorbing light in the visible spectrum, will be able to reduce to low and turn, C and H respectively, the state of oxide (CO2 and H2O),release of O. The final biological oxidation, the combination of metal-porphyrins in aerobically in the absence of light, will find in the oxidized state, so in the form of porphyrins and metal-oxide, will oxidize to C and H atom of hydrocarbonates, with formation of CO2 and H2O, or rather, will be reduced by C and H atom of hydrocarbonates,formation of CO2 and H2O, by absorbing energy produced by photosynthesis. If we can control the final biological oxidation, we can control cellular growth, thus multiplying, and on the other hand, maturation, so differentiation. Green energy will prevail if the cell (body) which multiplies (during growth), will in case of adult cell (functional) will prevail red energy . The two types of energy, that obtained by oxidative dehydrogenation , which will cause cell multiplication without differentiation , and that obtained by oxidative decarboxylation , which will be to stop proliferation, and will determine the differentiation (maturity, functionality). This process is carried out based on complementary colors, which are coenzymes oxidative dehydrogenation and oxidative decarboxylation is colored . It reveals the importance of acid-base balance, the predominance of the acidic or basic, as an acid structure (red), not only can gain energy from the carbon atom red (the principle of complementarity), but can not assimilate ( under the same principle). It must therefore acid-base balance of internal environment, and alkalinization his intake of organic substances by the electron donor. By alkalinization (addition of electrons) will occur neutralize acid structures, the red, they become leucoderivat, colorless, and inactive, while the basic, which because of acidosis became neutral, colorless and inactive, will be alkaline in electron contribution, will be in green, and will absorb red energy from the carbon atom. So, on two kinds of vital energy, it is clear correlation between the chemical structure of the cell(body),and type of energy that can produce and use. Thus a cell with acidic chemical structure, can produce only energy by oxidative dehydrogenation (green energy), because the acid can only be active coenzymes with acid chemical structure, red, will absorb the complementarity only green energy of hydrogen. Basic structures which should absorb red energy from carbon , are inactive due to acid environment, which in turn chemically in leucoderivat, so colorless structures, inactive. Conversion of these structures to normal, operation by alkalinization could be a long lasting process, therefore, we use parallel chromotherapy, based on the fact that these COENZYMES INVOLVED IN BIOLOGICAL OXIDATION FINALS ARE COLORED AND PHOTOSENSITIVE. Thus, exogenous irradiation with monochromatic green will neutralize, by complementarity, coenzymes red, acidic. In will reactivate alkaline coenzymes, which have become due acidosis leucoderivat, so colorless and inactive. Without producing CO2, carbonic anhydrase can not form H2CO3, severable and thus transferred through mitochondrial membrane. Will accumulate in the respiratory Flavin, OH groups, leading to excessive hydroxylation, followed by consecutive inclusion of amino (NH2). It is thus an imbalance between the hydrogenation-carboxylation and hydroxylation-amination, in favor of the latter. This will predominate AMINATION and HYDROXYLATION at the expense CARBOXYLATION and HYDROGENATION, leading to CONVERSION OF STRUCTURAL PROTEINS IN NUCLEIC ACIDS. Meanwhile, after chemical criteria not genetic, it synthesizes the remaining unoxidized carbon atoms, nucleic bases “de novo” by the same process of hydroxylation-amination, leading to THE SYNTHESIS OF NUCLEIC ACIDS “DE NOVO”. Sincerely yours, Dr. Viorel Bungau viorelbungau20@yahoo.com

    • Dr. Viorel Bungau,

      Your comment is beautiful, clorful, insightful, magestic.

      This article has drawn 3007 views

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      2013 283 330 465 390 288 208 187 164 255 274 163 3,007

  19. Dear Mr. Professor, Please join me in this research proposal, as leader, because I can not go alone.
    The basic idea of this theory is that the oxidation of hydrogen and carbon atoms, arising from the degradation of carbohydrates, is by two distinct processes based on oxidation-reduction electron transfer and photochemical process of energy release on the basis of color complementary, predominance of one or another depending on intracellular acid-base balance. I can not understand why nobody wants to do this experiment. I’m sure this assumption hides a truth. Before considering it a fiction to be checked experimentally. I would like to present a research project that concerns me for a long time that I can not experience myself.
    Involuntarily, after many years of searching, I have concluded that in the final biological oxidation, in addition to the oxidation-reduction electron transfer occurs photo-chemical process, accordance to the principle of color complementary energy transfer. I imagine an experiment that might be relevant (sure it can be improved). In my opinion, if this hypothesis proves true, one can control the energy metabolism of the cell by chromotherapy, as the structures involved are photosensitive and colorful. I would be very happy if this experiment were done under your leadership. Sincerely yours, Dr. Viorel Bungau

    INNER LIGHT – LIGHT OF LIFE.
    CHROMOTHERAPY AND THE IMPLICATIONS IN THE METABOLISM OF THE NORMAL AND NEOPLASTIC CELL. “Chlorophyll and hemoglobin pigments of life porphyrin structure differs only in that chlorophyll is green because of magnesium atoms in the structure, and hemoglobin in red because of iron atoms in the structure. This is evidence of the common origin of life.” (Heilmeyer) We propose an experiment to prove that the final biological oxidation, in addition to its oxidation-reduction, with formation of H2O and CO2, there is a photochemical effect, by which energy is transferred from the H atom, or C, process is done selct, the colors, complementary colors on the basis of the structures involved are colored (red hemoglobin Fe, Mg chlorophyll green, blue ceruloplasmin Cu, Fe cytochrome oxidase red, green cytochrome oxidase with Cu etc.). The basic idea is that if life pigments (chlorophyll, hemoglobin, cytochromes), which provides energy metabolism of the cell, are colored, we can control their activities through chromotherapy, on the basis of complementary color and energy rebalance the body, with a figured X- body-colored-ray.
    In my opinion, at the basis of malign transformation is a disturbance of energetical metabolism, which reached a level that cell can not correct (after having succeeded before, many times), disturbance that affects the whole body in different degrees and requires corection from outside starting from the ideea that the final biological oxidizing takes place through photochemical process with releasing and receieving energy. “Duality of cytochrome oxidase. Proliferation (growth) and Differentiation (maturation) cell.” Cytochrome oxidase is present in two forms, depending on the context of acid-base internal environment : 1.- Form acidic (acidosis), which contains two Iron atoms, will be red, will absorb the additional green energy of the hydrogen atom, derived from carbohydrates, with formation of H2O, metabolic context that will promote cell proliferation. 2.-Form alkaline (alkalosis), containing two copper atoms, will be green, will absorb the additional red energy of the carbon atom, derived from carbohydrates, with formation of CO2, metabolic context that will promote cell differentiation. Cytochrome oxidase structure has two atoms of copper. It is known that in conditions of acidosis (oxidative potential), the principle electronegativity metals, copper is removed from combinations of the Iron. So cytochrome oxidase will contain two atoms of iron instead of copper atoms, which changes its oxidation-reduction potential, but (most important), and color. If the copper was green, the iron is red, which radically change its absorption spectrum, based on the principle of complementary colors.
    “Inner Light- Light of Life. Endogenous monochromatic irradiation. Red ferment of Warburg – Green ferment of Warburg.”
    In my opinion, at the basis of malign transformation is a disturbance of energetical metabolism, which reached a level that cell can not correct (after having succeeded before, many times), disturbance that affects the whole body in different degrees and requires corection from outside starting from the ideea that the final biological oxidizing takes place through photochemical process with releasing and receieving energy. If the structures involved in biological oxidation finals are colored, then their energy absorption is made based on the principle of complementary colors. If we can determine the absorption spectrum at different levels, we can control energy metabolism by chromotherapy – EXOGENOUS MONOCHROMATIC IRRADIATION . Energy absorption in biological oxidation process itself, based on complementary colors, the structures involved (cytochromes), is the nature of porphyrins, in combination with a metal becomes colored, will absorb the complementary color, corresponding to a specific absorption spectrum, it will be in – ENDOGENOUS MONOCHROMATIC IRRADIATION.
    This entitles us to believe that: In photosynthesis, light absorption and its storage form of carbohydrates, are selected, the colors, as in cellular energy metabolism, absorption of energy by the degradation of carbohydrates, is also done selectively, based on complementary colors. In the final biological oxidation, in addition to an oxidation-reduction process takes place and a photo-chemical process,based on complementary colors, the first in the electron transfer, the second in the energy transfer. So, in the mitochondria is a process of oxidation of atoms C and H, derived from carbohydrates, with energy release and absorption of its selection (the color), by the structures involved, which is the nature of porphyrins, are photosensitive and colorful, if we accept as coenzymes involved, containing a metal atom gives them a certain color, depending on the state of oxidation or reduction (red ferment of Warburg with iron, all copper cerloplasmin blue, green chlorophyll magnesium, red iron hemoglobin, green cytochrome oxidase with copper, etc.)
    According to the principle electronegativity metals, under certain conditions the acid-base imbalance (acidosis), iron will replace copper in combination , cytocromoxidase became inactive, leading to changing oxidation-reduction potential, BUT THE COLOR FROM GREEN, TO REED, to block the final biological oxidation and the appearance of aerobic glycolysis. In connection with my research proposal, to prove that the final biological oxidation, in addition to an oxidation-reduction process takes place and a photo-chemical process, the first in the electron transfer, the second in the energy transfer.
    I SUGGEST TO YOU AN EXPERIMENT:

    TWO PLANTS, A RED (CORAILLE) LIGHT ONLY, IN BASIC MEDIUM, WITH ADDED COPPER, WILL GROW, FLOWER AND FRUIT WILL SHORT TIME, AND THE OTHER ONLY GREEN LIGHT (TOURQUOISE), IN AN ACID MEDIUM, WITH ADDED COPPER CHELATOR , WHICH GROWS THROUGHOUT WILL NOT GROW FLOWERS AND FRUIT WILL DO.

    CULTURE OF NEOPLASTIC TISSUE, IRRADIATED WITH MONOCHROMATIC GREEN ( TOURQUOISE) LIGHT, IN AN ALKALINE MEDIUM, WITH ADDED COPPER, WILL IN REGRESSION OF THE TISSUE CULTURE.

    CULTURE OF NEOPLASTIC TISSUE, IRRADIATED WITH RED ( CORAILLE) LIGHT, IN AN ACID MEDIUM, WITH ADDED COPPER CHELATOR, WILL LEAD TO EXAGERATED AND ANARCHICAL MULTIPLICATION.
    If in photosynthesis is the direct effect of monochromatic irradiation, in the final biological oxidation effect is reversed. Exogenous irradiation with green, induces endogenous irradiation with red, and vice versa. A body with cancer disease will become chemically color “red”- Acid -(pH, Rh, pCO2, alkaline reserve), and in terms of energy, green (X-body-colored-ray). A healthy body will become chemically color “green”-Alkaline – (as evidenced by laboratory), and in terms of energy, red (visible by X-body-colored-ray). Sincerely yours, Dr. Viorel Bungau

    -In addition-
    Life balance: Darkness and Light – Water and Fire – Inn and Yang.

    Cytochrome oxidase structure has two atoms of copper. It is known that in conditions of acidosis (oxidative potential), the principle electronegativity metals, copper is removed from combinations of the Iron. So cytochrome oxidase will contain two atoms of iron instead of copper atoms, which changes its oxidation-reduction potential, but (most important), and color. If the copper was green, the iron is red, which radically change its absorption spectrum, based on the principle of complementary colors. If neoplastic cells, because acidosis is overactive acid form of cytochrome oxidase (red with iron atoms), which will absorb the additional green energy hydrogen atom (exclusively), the production of H20 , so water will prevail, in Schizophrenia , neuronal intracellular alkaline environment, will promote the basic form of cytochrome oxidase (green with copper atoms), which will oxidize only carbon atoms, the energy absorption of red (complementary) and production of CO2, so the fire will prevail. Drawn from this theory interdependent relationship between water and fire, of hydrogen(H2O) and carbon(CO2) ,in a controlled relationship with oxygen (O2). If photosynthesis is a process of reducing carbon oxide(CO2) and hydrogen oxide(H2O), by increasing electronegativity of C and H atoms, with the electrons back to oxygen, which will be released in the mitochondria is a process of oxidation of atoms C and H, derived from carbohydrates, with energy release and absorption of its selection (the color), by the structures involved, which is the nature of porphyrins, are photosensitive and colorful. It means that matter and energy in the universe are found in a relationship based on complementary colors, each color of energy, corresponding with a certain chemical structure. In my opinion, at the basis of malign transformation is a disturbance of energetical metabolism, which reached a level that cell can not correct (after having succeeded before, many times), disturbance that affects the whole body in different degrees and requires corection from outside starting from the ideea that the final biological oxidizing takes place through photochemical process with releasing and receieving energy. The final biological oxidation is achieved through a process of oxidation-reduction, while a photochemical process, based on the principle of complementary colors, if we accept as coenzymes involved, containing a metal atom gives them a certain color, depending on the state of oxidation or reduction (red ferment of Warburg with copper, all copper cerloplasmin blue, green chlorophyll magnesium, red iron hemoglobin,etc. If satisfied, the final biological oxidation is achieved by a photochemical mechanism (besides the oxidation-reduction), that energy is released based on complementary colors, means that we can control the final biological oxidation mechanism, irreversibly disrupted in cancer, by chromotherapy and correction of acid-base imbalance that underlies this disorder.We reached this conclusions studying the final biological oxidation, for understanding the biochemical mechanism of aerobic glycolysis in cancer. We found that cancer cell, energy metabolism is almost exclusively on hydrogen by oxidative dehydrogenation, due to excessive acidosis , coenzymes which makes carbon oxidation, as dormant (these coenzymes have become inactive). If we accept the nature of these coenzymes chloride (see Warburg ferment red), could be rectivate, by correcting acidosis (because that became leucoderivat), and by chromoterapie, on the basis of complementary colors. According to the principle electronegativity metals, under certain conditions the acid-base imbalance (acidosis), iron will replace copper in combination , cytocromoxidase became inactive (it contains two copper atoms) leading to changing oxidation-reduction potential, BUT THE COLOR FROM GREEN, TO REED, to block the final biological oxidation and the appearance of aerobic glycolysis.

    Malignant transformation occurs by energy metabolism imbalance in power generation purposes in the predominantly (exclusively) of the hydrogen atom of carbon oxidation is impossible. Thus at the cellular level will produce a multiplication (growth) exaggerated (exclusive), energy from hydrogen favoring growth, multiplication, at the expense of differentiation (maturation). Differentiation is achieved by energy obtained by oxidation of the carbon atom can not take, leading to carcinogenesis . The energy metabolism of the cell, an energy source is carbohydrate degradation, which is done by OXIDATIVE DEHYDROGENATION AND OXIDATIVE DECARBOXYLATION , to obtain energy and CO2 and H2O. In normal cells there is a balance between the two energy sources. If cancer cells, oxidation of the carbon atom is not possible, the cell being forced to summarize the only energy source available, of hydrogen. This disorder underlying malignant transformation of cells and affect the whole body, in various degrees, often managing to rebalance process, until at some point it becomes irreversible. The exclusive production of hydrogen energy will cause excessive multiplication, of immature cells, without functional differentiation. Exclusive carbon energy production will lead to hyperdifferentiation, hyperfunctional, multiplication is impossible. Normal cell is between two extremes, between some limits depending on the adjustment factors of homeostasis. Energy from energy metabolism is vital for cell (body). If the energy comes predominantly (or exclusively) by oxidation of the hydrogen atom, green energy, will occur at the structural level (biochemical), acidification of the cellular structures that will turn red, so WE HAVE MORPHOLOGICAL AND CHEMICAL STRUCTURES “RED”, WITH “GREEN” ENERGY. This background predisposes to accelerated growth, without differentiation, reaching up uncontrolled, anarchical. ENERGY STRUCTURE OF THE CELL BODY WOULD BE INN. If necessary energy cell derived mainly by oxidation of the carbon atom, red energy,cell structures will be colored green, will be alkaline(basic), so WE HAVE MORPHOLOGICAL AND CHEMICAL STRUCTURES “GREEN”, WITH “RED” ENERGY, on the same principle of complementarity. This context will lead hyperdifferentiation, hyperfunctional ,maturation, and grouth stops. ENERGY STRUCTURE OF THE CELL BODY WOULD BE YANG. If in photosynthesis, porphyrins chemicals group, whic be photosensitivity (their first feature), shows and a great affinity for metals with chelate forming and becoming colored (pigments of life), can absorb monochromatic light complementary, so if these pigments, which constitutes the group of chromoprotheine, in photosynthesis will achieve CO2 and H2O reduction the recovery of C, H respectively, and the issuance of and release of O, atoms as H and C that reduced the energy load, representing carbohydrates, is in the form of solar energy storage, in cellular energy metabolism, processes necessary life, energy will come from the degradation of substances produced in photosynthesis, the carbohydrates, by oxidative dehydrogenation and oxidative decarboxylation, through like substances, which form chelates with the metals, are colored, metals contained in the form of oxides of various colors(green Mg, red Fe, blue Cu,etc.),suffering from complementary color absorption process of reduction with H in case,if the oxidative dehydrogenation, when chelated metal pigment is red, becoming leucoderivat (colorless) by absorbing complementary color (green) of hydrogen, formation of H2O, or C, if the oxidative decarboxylation when chelated metallic pigment is green, energy absorbing additional, red energy of atom C, CO2 production, the process is identical. The process that lies at base cellular energy metabolism, takes place in the final biological oxidation, reducing the O atom in the form of metal oxide, in combination with photosensitive substance, porohyrin, colorful,absorbing complementary color, will reduce the O atom, with H and C, with the production of H2O and CO2. Green energy release of H atom in the oxidative dehydrogenation process, it is a process of”IRRADIATION MONOCHROMATIC ENDOGENOUS WITH GREEN”, and red energy release of C atom in the oxidative decarboxylation process, consists in an “IRRADIATION MONOCHROMATIC ENDOGENOUS WITH RED”. Porphyrin-metal combination in photosynthesis, the chelated form, by absorbing light in the visible spectrum, will be able to reduce to low and turn, C and H respectively, the state of oxide (CO2 and H2O),release of O. The final biological oxidation, the combination of metal-porphyrins in aerobically in the absence of light, will find in the oxidized state, so in the form of porphyrins and metal-oxide, will oxidize to C and H atom of hydrocarbonates, with formation of CO2 and H2O, or rather, will be reduced by C and H atom of hydrocarbonates,formation of CO2 and H2O, by absorbing energy produced by photosynthesis. If we can control the final biological oxidation, we can control cellular growth, thus multiplying, and on the other hand, maturation, so differentiation. Green energy will prevail if the cell (body) which multiplies (during growth), will in case of adult cell (functional) will prevail red energy . The two types of energy, that obtained by oxidative dehydrogenation , which will cause cell multiplication without differentiation , and that obtained by oxidative decarboxylation , which will be to stop proliferation, and will determine the differentiation (maturity, functionality). This process is carried out based on complementary colors, which are coenzymes oxidative dehydrogenation and oxidative decarboxylation is colored . It reveals the importance of acid-base balance, the predominance of the acidic or basic, as an acid structure (red), not only can gain energy from the carbon atom red (the principle of complementarity), but can not assimilate ( under the same principle). It must therefore acid-base balance of internal environment, and alkalinization his intake of organic substances by the electron donor. By alkalinization (addition of electrons) will occur neutralize acid structures, the red, they become leucoderivat, colorless, and inactive, while the basic, which because of acidosis became neutral, colorless and inactive, will be alkaline in electron contribution, will be in green, and will absorb red energy from the carbon atom. So, on two kinds of vital energy, it is clear correlation between the chemical structure of the cell(body),and type of energy that can produce and use. Thus a cell with acidic chemical structure, can produce only energy by oxidative dehydrogenation (green energy), because the acid can only be active coenzymes with acid chemical structure, red, will absorb the complementarity only green energy of hydrogen. Basic structures which should absorb red energy from carbon , are inactive due to acid environment, which in turn chemically in leucoderivat, so colorless structures, inactive. Conversion of these structures to normal, operation by alkalinization could be a long lasting process, therefore, we use parallel chromotherapy, based on the fact that these COENZYMES INVOLVED IN BIOLOGICAL OXIDATION FINALS ARE COLORED AND PHOTOSENSITIVE. Thus, exogenous irradiation with monochromatic green will neutralize, by complementarity, coenzymes red, acidic. In will reactivate alkaline coenzymes, which have become due acidosis leucoderivat, so colorless and inactive. Without producing CO2, carbonic anhydrase can not form H2CO3, severable and thus transferred through mitochondrial membrane. Will accumulate in the respiratory Flavin, OH groups, leading to excessive hydroxylation, followed by consecutive inclusion of amino (NH2). It is thus an imbalance between the hydrogenation-carboxylation and hydroxylation-amination, in favor of the latter. This will predominate AMINATION and HYDROXYLATION at the expense CARBOXYLATION and HYDROGENATION, leading to CONVERSION OF STRUCTURAL PROTEINS IN NUCLEIC ACIDS. Meanwhile, after chemical criteria not genetic, it synthesizes the remaining unoxidized carbon atoms, nucleic bases “de novo” by the same process of hydroxylation-amination, leading to THE SYNTHESIS OF NUCLEIC ACIDS “DE NOVO”. Sincerely yours, Dr. Viorel Bungau viorelbungau20@yahoo.com

  20. […] Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View? Author: Larry H. Bernstein, MD, FCAP https://pharmaceuticalintelligence.com/2012/10/17/is-the-warburg-effect-the-cause-or-the-effect-of-ca… […]

Case Study #2:

·      Knowing the tumor’s size and location, could we target treatment to THE ROI by applying…..

Author: Dror Nir, PhD

https://pharmaceuticalintelligence.com/2012/10/16/knowing-the-tumors-size-and-location-could-we-target-treatment-to-the-roi-by-applying-imaging-guided-intervention/

26 Responses

  1. GREAT work.

    I’ll read and comment later on

  2. Highlights of The 2012 Johns Hopkins Prostate Disorders White Paper include:

    A promising new treatment for men with frequent nighttime urination.
    Answers to 8 common questions about sacral nerve stimulation for lower urinary tract symptoms.
    Surprising research on the link between smoking and prostate cancer recurrence.
    How men who drink 6 cups of coffee a day or more may reduce their risk of aggressive prostate cancer.
    Should you have a PSA screening test? Answers to important questions on the controversial USPSTF recommendation.
    Watchful waiting or radical prostatectomy for men with early-stage prostate cancer? What the research suggests.
    A look at state-of-the-art surveillance strategies for men on active surveillance for prostate cancer.
    Locally advanced prostate cancer: Will you benefit from radiation and hormones?
    New drug offers hope for men with metastatic castrate-resistant prostate cancer.
    Behavioral therapy for incontinence: Why it might be worth a try.

    You’ll also get the latest news on benign prostatic enlargement (BPE), also known as benign prostatic hyperplasia (BPH) and prostatitis:
    What’s your Prostate Symptom Score? Here’s a quick quiz you can take right now to determine if you should seek treatment for your enlarged prostate.
    Your surgical choices: a close look at simple prostatectomy, transurethral prostatectomy and open prostatectomy.
    New warnings about 5-alpha-reductase inhibitors and aggressive prostate cancer.

  3. Promising technique.

    INCORE pointed out in detail about the general problem judging response and the stil missing quality in standardization:

    http://www.futuremedicine.com/doi/abs/10.2217/fon.12.78?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dwww.ncbi.nlm.nih.gov

    I did research in response evaluation and prediction for about 15y now and being honest: neither the clinical, nor the molecular biological data proved significant benefit in changing a strategy in patient diagnosis and / or treatment. I would state: this brings us back on the ground and not upon the sky. Additionally it means: we have to ´work harder on that and the WHO has to take responsibility: clinicians use a reponse classification without knowing, that this is just related to “ONE” experiment from the 70’s and that this experiment never had been rescrutinized (please read the Editorial I provided – we use a clinical response classification since more than 30 years worldwide (Miller et al. Cancer 1981) but it is useless !

  4. Dr. BB

    Thank you for your comment.
    Dr. Nir will reply to your comment.
    Regarding the Response Classification in use, it seems that the College of Oncology should champion a task force to revisit the Best Practice in use in this domain and issue a revised version or a new effort for a a new classification system for Clinical Response to treatment in Cancer.

  5. I’m sorry that I was looking for this paper again earlier and didn’t find it. I answered my view on your article earlier.

    This is a method demonstration, but not a proof of concept by any means. It adds to the cacophany of approaches, and in a much larger study would prove to be beneficial in treatment, but not a cure for serious prostate cancer because it is unlikely that it can get beyond the margin, and also because there is overtreatment at the cutoff of PSA at 4.0. There is now a proved prediction model that went to press some 4 months ago. I think that the pathologist has to see the tissue, and the standard in pathology now is for any result that is cancer, two pathologist or a group sitting together should see it. It’s not an easy diagnosis.

    Björn LDM Brücher, Anton Bilchik, Aviram Nissan, Itzhak Avital, & Alexander Stojadinovic. Tumor response criteria: are they appropriate? Future Oncol. (2012) 8(8), 903–906. 10.2217/FON.12.78. ISSN 1479-6694.

    ..Tumor heterogeneity is a ubiquitous phemomenon. In particular, there are important differences among the various types of gastrointestinal (GI) cancers in terms of tumor biology, treatment response and prognosis.

    ..This forms the principal basis for targeted therapy directed by tumor-specific testing at either the gene or protein level. Despite rapid advances in our understanding of targeted therapy for GI cancers, the impact on cancer survival has been marginal.

    ..Can tumor response to therapy be predicted, thereby improving the selection of patients for cancer treatment?

    ..In 2000 theNCI with the European Association for Research and Treatment of Cancer, proposed a replacement of 2D measurement with a decrease in the largest tumor diameter by 30% in one dimension. Tumor response as defined would translate into a 50% decrease for a spherical lesion

    ..We must rethink how we may better determine treatment response in a reliable, reproducible way that is aimed at individualizing the therapy of cancer patients.

    ..we must change the tools we use to assess tumor response. The new modality should be based on empirical evidence that translates into relevant and meaningful clinical outcome data.

    ..This becomes a conundrum of sorts in an era of ‘minimally invasive treatment’.

    ..integrated multidisciplinary panel of international experts – not sure that that will do it

    Several years ago i heard Stamey present the totality of his work at Stanford, with great disappointment over hsPSA that they pioneered in. The outcomes were disappointing.

    I had published a review of all of our cases reviewed for 1 year with Marguerite Pinto.
    There’s a reason that the physicians line up outside of her office for her opinion.
    The review showed that a PSA over 24 ng/ml is predictive of bone metastasis. Any result over 10 was as likely to be prostatitis, BPH or cancer.

    I did an ordinal regression in the next study with Gustave Davis using a bivariate ordinal regression to predict lymph node metastasis using the PSA and the Gleason score. It was better than any univariate model, but there was no followup.

    I reviewed a paper for Clin Biochemistry (Elsevier) on a new method for PSA, very different than what we are familiar with. It was the most elegant paper I have seen in the treatment of the data. The model could predict post procedural time to recurrence to 8 years.

    • I hope we are in agreement on the fact that imaging guided interventions are needed for better treatment outcome. The point I’m trying to make in this post is that people are investing in developing imaging guided intervention and it is making progress.

      Over diagnosis and over treatment is another issue altogether. I think that many of my other posts are dealing with that.

  6. Tumor response criteria: are they appropriate?
    Future Oncology 2012; 8(8): 903-906 , DOI 10.2217/fon.12.78 (doi:10.2217/fon.12.78)
    Björn LDM Brücher, Anton Bilchik, Aviram Nissan, Itzhak Avital & Alexander Stojadinovic
    Tumor heterogeneity is a problematic because of differences among the metabolic variety among types of gastrointestinal (GI) cancers, confounding treatment response and prognosis.
    This is in response to … a group of investigators from Sunnybrook Health Sciences Centre, University of Toronto, Ontario, Canada who evaluate the feasibility and safety of magnetic resonance (MR) imaging–controlled transurethral ultrasound therapy for prostate cancer in humans. Their study’s objective was to prove that using real-time MRI guidance of HIFU treatment is possible and it guarantees that the location of ablated tissue indeed corresponds to the locations planned for treatment.
    1. There is a difference between expected response to esophageal or gastric neoplasms both biologically and in expected response, even given variability within a class. The expected time to recurrence is usually longer in the latter case, but the confounders are – age at time of discovery, biological time of detection, presence of lymph node and/or distant metastasis, microscopic vascular invasion.
    2. There is a long latent period in abdominal cancers before discovery, unless a lesion is found incidentally in surgery for another reason.
    3. The undeniable reality is that it is not difficult to identify the main lesion, but it is difficult to identify adjacent epithelium that is at risk (transitional or pretransitional). Pathologists have a very good idea about precancerous cervical neoplasia.

    The heterogeneity rests within each tumor and between the primary and metastatic sites, which is expected to be improved by targeted therapy directed by tumor-specific testing. Despite rapid advances in our understanding of targeted therapy for GI cancers, the impact on cancer survival has been marginal.

    The heterogeneity is a problem that will take at least another decade to unravel because of the number of signaling pathways and the crosstalk that is specifically at issue.

    I must refer back to the work of Frank Dixon, Herschel Sidransky, and others, who did much to develop a concept of neoplasia occurring in several stages – minimal deviation and fast growing. These have differences in growth rates, anaplasia, and biochemical. This resembles the multiple “hit” theory that is described in “systemic inflammatory” disease leading to a final stage, as in sepsis and septic shock.
    In 1920, Otto Warburg received the Nobel Prize for his work on respiration. He postulated that cancer cells become anaerobic compared with their normal counterpart that uses aerobic respiration to meet most energy needs. He attributed this to “mitochondrial dysfunction. In fact, we now think that in response to oxidative stress, the mitochondrion relies on the Lynen Cycle to make more cells and the major source of energy becomes glycolytic, which is at the expense of the lean body mass (muscle), which produces gluconeogenic precursors from muscle proteolysis (cancer cachexia). There is a loss of about 26 ATP ~Ps in the transition.
    The mitochondrial gene expression system includes the mitochondrial genome, mitochondrial ribosomes, and the transcription and translation machinery needed to regulate and conduct gene expression as well as mtDNA replication and repair. Machinery involved in energetics includes the enzymes of the Kreb’s citric acid or TCA (tricarboxylic acid) cycle, some of the enzymes involved in fatty acid catabolism (β-oxidation), and the proteins needed to help regulate these systems. The inner membrane is central to mitochondrial physiology and, as such, contains multiple protein systems of interest. These include the protein complexes involved in the electron transport component of oxidative phosphorylation and proteins involved in substrate and ion transport.
    Mitochondrial roles in, and effects on, cellular homeostasis extend far beyond the production of ATP, but the transformation of energy is central to most mitochondrial functions. Reducing equivalents are also used for anabolic reactions. The energy produced by mitochondria is most commonly thought of to come from the pyruvate that results from glycolysis, but it is important to keep in mind that the chemical energy contained in both fats and amino acids can also be converted into NADH and FADH2 through mitochondrial pathways. The major mechanism for harvesting energy from fats is β-oxidation; the major mechanism for harvesting energy from amino acids and pyruvate is the TCA cycle. Once the chemical energy has been transformed into NADH and FADH2 (also discovered by Warburg and the basis for a second Nobel nomination in 1934), these compounds are fed into the mitochondrial respiratory chain.
    The hydroxyl free radical is extremely reactive. It will react with most, if not all, compounds found in the living cell (including DNA, proteins, lipids and a host of small molecules). The hydroxyl free radical is so aggressive that it will react within 5 (or so) molecular diameters from its site of production. The damage caused by it, therefore, is very site specific. The reactions of the hydroxyl free radical can be classified as hydrogen abstraction, electron transfer, and addition.
    The formation of the hydroxyl free radical can be disastrous for living organisms. Unlike superoxide and hydrogen peroxide, which are mainly controlled enzymatically, the hydroxyl free radical is far too reactive to be restricted in such a way – it will even attack antioxidant enzymes. Instead, biological defenses have evolved that reduce the chance that the hydroxyl free radical will be produced and, as nothing is perfect, to repair damage.
    Currently, some endogenous markers are being proposed as useful measures of total “oxidative stress” e.g., 8-hydroxy-2’deoxyguanosine in urine. The ideal scavenger must be non-toxic, have limited or no biological activity, readily reach the site of hydroxyl free radical production (i.e., pass through barriers such as the blood-brain barrier), react rapidly with the free radical, be specific for this radical, and neither the scavenger nor its product(s) should undergo further metabolism.
    Nitric oxide has a single unpaired electron in its π*2p antibonding orbital and is therefore paramagnetic. This unpaired electron also weakens the overall bonding seen in diatomic nitrogen molecules so that the nitrogen and oxygen atoms are joined by only 2.5 bonds. The structure of nitric oxide is a resonance hybrid of two forms.
    In living organisms nitric oxide is produced enzymatically. Microbes can generate nitric oxide by the reduction of nitrite or oxidation of ammonia. In mammals nitric oxide is produced by stepwise oxidation of L-arginine catalyzed by nitric oxide synthase (NOS). Nitric oxide is formed from the guanidino nitrogen of the L-arginine in a reaction that consumes five electrons and requires flavin adenine dinucleotide (FAD), flavin mononucleotide (FMN) tetrahydrobiopterin (BH4), and iron protoporphyrin IX as cofactors. The primary product of NOS activity may be the nitroxyl anion that is then converted to nitric oxide by electron acceptors.
    The thiol-disulfide redox couple is very important to oxidative metabolism. GSH is a reducing cofactor for glutathione peroxidase, an antioxidant enzyme responsible for the destruction of hydrogen peroxide. Thiols and disulfides can readily undergo exchange reactions, forming mixed disulfides. Thiol-disulfide exchange is biologically very important. For example, GSH can react with protein cystine groups and influence the correct folding of proteins, and it GSH may play a direct role in cellular signaling through thiol-disulfide exchange reactions with membrane bound receptor proteins (e.g., the insulin receptor complex), transcription factors (e.g., nuclear factor κB), and regulatory proteins in cells. Conditions that alter the redox status of the cell can have important consequences on cellular function.
    So the complexity of life is not yet unraveled.

    Can tumor response to therapy be predicted, thereby improving the selection of patients for cancer treatment?
    The goal is not just complete response. Histopathological response seems to be related post-treatment histopathological assessment but it is not free from the challenge of accurately determining treatment response, as this method cannot delineate whether or not there are residual cancer cells. Functional imaging to assess metabolic response by 18-fluorodeoxyglucose PET also has its limits, as the results are impacted significantly by several variables:

    • tumor type
    • sizing
    • doubling time
    • anaplasia?
    • extent of tumor necrosis
    • type of antitumor therapy and the time when response was determined.
    The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ characteristics, a greater challenge in an era of ‘minimally invasive treatment’.
    This listing suggests that for every cancer the following data has to be collected (except doubling time). If there are five variables, the classification based on these alone would calculate to be very sizable based on Eugene Rypka’s feature extraction and classification. But looking forward, time to remission and disease free survival are additionally important. Treatment for cure is not the endpoint, but the best that can be done is to extend the time of survival to a realistic long term goal and retain a quality of life.

    Brücher BLDM, Piso P, Verwaal V et al. Peritoneal carcinomatosis: overview and basics. Cancer Invest.30(3),209–224 (2012).
    Brücher BLDM, Swisher S, Königsrainer A et al. Response to preoperative therapy in upper gastrointestinal cancers. Ann. Surg. Oncol.16(4),878–886 (2009).
    Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer47(1),207–214 (1981).
    Therasse P, Arbuck SG, Eisenhauer EA et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J. Natl Cancer Inst.92(3),205–216 (2000).
    Brücher BLDM, Becker K, Lordick F et al. The clinical impact of histopathological response assessment by residual tumor cell quantification in esophageal squamous cell carcinomas. Cancer106(10),2119–2127 (2006).

    • Dr. Larry,

      Thank you for this comment.

      Please carry it as a stand alone post, Dr. Ritu will refer to it and reference it in her FORTHCOMING pst on Tumor Response which will integrate multiple sources.

      Please execute my instruction

      Thank you

    • Thank you Larry for this educating comment. It explains very well why the Canadian investigators did not try to measure therapy response!

      What they have demonstrated is the technological feasibility of coupling a treatment device to an imaging device and use that in order to guide the treatment to the right place.

      the issue of “choice of treatment” to which you are referring is not in the scope of this publication.
      The point is: if one treatment modality can be guided, other can as well! This should encourage others, to try and develop imaging-based treatment guidance systems.

  7. The crux of the matter in terms of capability is that the cancer tissue, adjacent tissue, and the fibrous matrix are all in transition to the cancerous state. It is taught to resect leaving “free margin”, which is better aesthetically, and has had success in breast surgery. The dilemma is that the patient may return, but how soon?

    • Correct. The philosophy behind lumpectomy is preserving quality of life. It was Prof. Veronesi (IEO) who introduced this method 30 years ago noticing that in the majority of cases, the patient will die from something else before presenting recurrence of breast cancer..

      It is well established that when the resection margins are declared by a pathologist (as good as he/she could be) as “free of cancer”, the probability of recurrence is much lower than otherwise.

  8. Dr. Larry,

    To assist Dr. Ritu, PLEASE carry ALL your comments above into a stand alone post and ADD to it your comment on my post on MIS

    Thank you

  9. Great post! Dr. Nir, can the ultrasound be used in conjunction with PET scanning as well to determine a spatial and functional map of the tumor. With a disease like serous ovarian cancer we typically see an intraperitoneal carcimatosis and it appears that clinicians are wanting to use fluorogenic probes and fiberoptics to visualize the numerous nodules located within the cavity Also is the technique being used mainy for surgery or image guided radiotherapy or can you use this for detecting response to various chemotherapeutics including immunotherapy.

    • Ultrasound can and is actually used in conjunction with PET scanning in many cases. The choice of using ultrasound is always left to the practitioner! Being a non-invasive, low cost procedure makes the use of ultrasound a non-issue. The down-side is that because it is so easy to access and operate, nobody bothers to develop rigorous guidelines about using it and the benefits remains the property of individuals.

      In regards to the possibility of screening for ovarian cancer and characterising pelvic masses using ultrasound I can refer you to scientific work in which I was involved:

      1. VAES (E.), MANCHANDA (R), AUTIER, NIR (R), NIR (D.), BLEIBERG (H.), ROBERT (A.), MENON (U.). Differential diagnosis of adnexal masses: Sequential use of the Risk of Malignancy Index and a novel computer aided diagnostic tool. Published in Ultrasound in Obstetrics & Gynecology. Issue 1 (January). Vol. 39. Page(s): 91-98.

      2. VAES (E.), MANCHANDA (R), NIR (R), NIR (D.), BLEIBERG (H.), AUTIER (P.), MENON (U.), ROBERT (A.). Mathematical models to discriminate between benign and malignant adnexal masses: potential diagnostic improvement using Ovarian HistoScanning. Published in International Journal of Gynecologic Cancer (IJGC). Issue 1. Vol. 21. Page(s): 35-43.

      3. LUCIDARME (0.), AKAKPO (J.-P.), GRANBERG (S.), SIDERI (M.), LEVAVI (H.), SCHNEIDER (A.), AUTIER (P.), NIR (D.), BLEIBERG (H.). A new computer aided diagnostic tool for non-invasive characterisation of malignant ovarian masses: Results of a multicentre validation study. Published in European Radiology. Issue 8. Vol. 20. Page(s): 1822-1830.

      Dror Nir, PhD
      Managing partner

      BE: +32 (0) 473 981896
      UK: +44 (0) 2032392424

      web: http://www.radbee.com/
      blogs: http://radbee.wordpress.com/ ; http://www.MedDevOnIce.com

       

  10. totally true and i am very thankfull for these briliant comments.

    Remember: 10years ago: every cancer researcher stated: “look at the tumor cells only – forget the stroma”. The era of laser-captured tumor-cell dissection started. Now , everyone knows: it is a system we are looking at and viewing and analyzing tumor cells only is really not enough.

    So if we would be honest, we would have to declare, that all data, which had been produced 13-8years ago, dealing with laser capture microdissection, that al these data would need a re-scrutinization, cause the influence of the stroma was “forgotten”. I ‘d better not try thinking about the waisted millions of dollars.

    If we keep on being honest: the surgeon looks at the “free margin” in a kind of reductionable model, the pathologist is more the control instance. I personally see the pathologist as “the control instance” of surgical quality. Therefore, not the wish of the surgeon is important, the objective way of looking into problems or challenges. Can a pathologist always state, if a R0-resection had been performed ?

    The use of the Resectability Classification:
    There had been many many surrogate marker analysis – nothing new. BUT never a real substantial well tought through structured analysis had been done: mm by mm by mm by mm and afterwards analyzing that by a ROC analysis. BUt against which goldstandard ? If you perform statistically a ROC analysis – you need a golstandard to compare to. Therefore what is the real R0-resectiòn? It had been not proven. It just had been stated in this or that tumor entity that this or that margin with this margin free mm distance or that mm distance is enough and it had been declared as “the real R0-classification”. In some organs it is very very difficult and we all (surgeons, pathologists, clinicians) that we always get to the limit, if we try interpretating the R-classification within the 3rd dimension. Often it is just declared and stated.

    Otherwise: if lymph nodes are negative it does not mean, lymph nodes are really negative, cause up to 38% for example in upper GI cancers have histological negative lymph nodes, but immunohistochemical positive lymph nodes. And this had been also shown by Stojadinovic at el analyzing the ultrastaging in colorectal cancer. So the 4th dimension of cancer – the lymph nodes / the lymphatic vessel invasion are much more important than just a TNM classification, which unfortunately does often not reflect real tumor biology.

    AS we see: cancer has multifactorial reasons and it is necessary taking the challenge performing high sophisticated research by a multifactorial and multidisciplinary manner.

    Again my deep and heartly thanks for that productive and excellent discussion !

    • Dr. BB,

      Thank you for your comment.

      Multidisciplinary perspectives have illuminated the discussion on the pages of this Journal.

      Eager to review Dr. Ritu’s forthcoming paper – the topic has a life of its own and is embodied in your statement:

      “the 4th dimension of cancer – the lymph nodes / the lymphatic vessel invasion are much more important than just a TNM classification, which unfortunately does often not reflect real tumor biology.”

    • Thank you BB for your comment. You have touched the core limitation of healthcare professionals: how do we know that we know!

      Do we have a reference to each of the test we perform?

      Do we have objective and standardise quality measures?

      Do we see what is out-there or are we imagining?

      The good news: Everyday we can “think” that we learned something new. We should be happy with that, even if it is means that we learned that yesterday’s truth is not true any-more and even if we are likely to be wrong again…:)

      But still, in the last decades, lots of progress was made….

  11. Dr. Nir,
    I thoroughly enjoyed reading your post as well as the comments that your post has attracted. There were different points of view and each one has been supported with relevant examples in the literature. Here are my two cents on the discussion:
    The paper that you have discussed had the objective of finding out whether real-time MRI guidance of treatment was even possible and if yes, and also if the treatment could be performed in accurate location of the ROI? The data reveals they were pretty successful in accomplishing their objective and of course that gives hope to the imaging-based targeted therapies.
    Whether the ROI is defined properly and if it accounts for the real tumor cure, is a different question. Role of pathologists and the histological analysis they bring about to the table cannot be ruled out, and the absence of a defined line between the tumor and the stromal region in the vicinity is well documented. However, that cannot rule out the value and scope of imaging-based detection and targeted therapy. After all, it is seminal in guiding minimally invasive surgery. As another arm of personalized medicine-based cure for cancer, molecular biologists at MD Anderson have suggested molecular and genetic profiling of the tumor to determine genetic aberrations on the basis of which matched-therapy could be recommended to patients. When phase I trial was conducted, the results were obtained were encouraging and the survival rate was better in matched-therapy patients compared to unmatched patients. Therefore, everytime there is more to consider when treating a cancer patient and who knows a combination of views of oncologists, pathologists, molecular biologists, geneticists, surgeons would device improvised protocols for diagnosis and treatment. It is always going to be complicated and generalizations would never give an answer. Smart interpretations of therapies – imaging-based or others would always be required!

    Ritu

    • Dr. Nir,
      One of your earlier comments, mentioned the non invasiveness of ultrasound, thus, it’s prevalence in use for diagnosis.

      This may be true for other or all areas with the exception of Mammography screening. In this field, an ultrasound is performed only if a suspected area of calcification or a lump has been detected in the routine or patient-initiated request for ad hoc mammography secondery to patient complain of pain or patient report of suspected lump.

      Ultrasound in this field repserents ascalation and two radiologists review.

      It in routine use for Breast biopsy.

    • Thanks Ritu for this supporting comment. The worst enemy of finding solutions is doing nothing while using the excuse of looking for the “ultimate solution” . Personally, I believe in combining methods and improving clinical assessment based on information fusion. Being able to predict, and then timely track the response to treatment is a major issue that affects survival and costs!

  12. […] Dror Nir authored a post on October 16th titled “Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-gu…” The article attracted a lot of comments from readers including researchers and oncologists and […]

  13. […] ted in this area; New clinical results supports Imaging-guidance for targeted prostate biopsy and Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imagin… Today I report on recent publication presenting the advantage of using targeted trans-perineal […]

  14. […] ted in this area; New clinical results supports Imaging-guidance for targeted prostate biopsy and Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-gu… Today I report on recent publication presenting the advantage of using targeted trans-perineal […]

  15. […] Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-gu… […]

Case Study #3:

  • Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/12/01/personalized-medicine-cancer-cell-biology-and-minimally-invasive-surgery-mis

 

This article generated a Scientific Exchange of 24 Comments, some scholarly comments are quite lengthy

24 Responses

  1. GREAT work.

    I’ll read and comment later on

  2. Highlights of The 2012 Johns Hopkins Prostate Disorders White Paper include:

    A promising new treatment for men with frequent nighttime urination.
    Answers to 8 common questions about sacral nerve stimulation for lower urinary tract symptoms.
    Surprising research on the link between smoking and prostate cancer recurrence.
    How men who drink 6 cups of coffee a day or more may reduce their risk of aggressive prostate cancer.
    Should you have a PSA screening test? Answers to important questions on the controversial USPSTF recommendation.
    Watchful waiting or radical prostatectomy for men with early-stage prostate cancer? What the research suggests.
    A look at state-of-the-art surveillance strategies for men on active surveillance for prostate cancer.
    Locally advanced prostate cancer: Will you benefit from radiation and hormones?
    New drug offers hope for men with metastatic castrate-resistant prostate cancer.
    Behavioral therapy for incontinence: Why it might be worth a try.

    You’ll also get the latest news on benign prostatic enlargement (BPE), also known as benign prostatic hyperplasia (BPH) and prostatitis:
    What’s your Prostate Symptom Score? Here’s a quick quiz you can take right now to determine if you should seek treatment for your enlarged prostate.
    Your surgical choices: a close look at simple prostatectomy, transurethral prostatectomy and open prostatectomy.
    New warnings about 5-alpha-reductase inhibitors and aggressive prostate cancer.

  3. Promising technique.

    INCORE pointed out in detail about the general problem judging response and the stil missing quality in standardization:

    http://www.futuremedicine.com/doi/abs/10.2217/fon.12.78?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dwww.ncbi.nlm.nih.gov

    I did research in response evaluation and prediction for about 15y now and being honest: neither the clinical, nor the molecular biological data proved significant benefit in changing a strategy in patient diagnosis and / or treatment. I would state: this brings us back on the ground and not upon the sky. Additionally it means: we have to ´work harder on that and the WHO has to take responsibility: clinicians use a reponse classification without knowing, that this is just related to “ONE” experiment from the 70′s and that this experiment never had been rescrutinized (please read the Editorial I provided – we use a clinical response classification since more than 30 years worldwide (Miller et al. Cancer 1981) but it is useless !

  4. Dr. BB

    Thank you for your comment.
    Dr. Nir will reply to your comment.
    Regarding the Response Classification in use, it seems that the College of Oncology should champion a task force to revisit the Best Practice in use in this domain and issue a revised version or a new effort for a a new classification system for Clinical Response to treatment in Cancer.

  5. I’m sorry that I was looking for this paper again earlier and didn’t find it. I answered my view on your article earlier.

    This is a method demonstration, but not a proof of concept by any means. It adds to the cacophany of approaches, and in a much larger study would prove to be beneficial in treatment, but not a cure for serious prostate cancer because it is unlikely that it can get beyond the margin, and also because there is overtreatment at the cutoff of PSA at 4.0. There is now a proved prediction model that went to press some 4 months ago. I think that the pathologist has to see the tissue, and the standard in pathology now is for any result that is cancer, two pathologist or a group sitting together should see it. It’s not an easy diagnosis.

    Björn LDM Brücher, Anton Bilchik, Aviram Nissan, Itzhak Avital, & Alexander Stojadinovic. Tumor response criteria: are they appropriate? Future Oncol. (2012) 8(8), 903–906. 10.2217/FON.12.78. ISSN 1479-6694.

    ..Tumor heterogeneity is a ubiquitous phemomenon. In particular, there are important differences among the various types of gastrointestinal (GI) cancers in terms of tumor biology, treatment response and prognosis.

    ..This forms the principal basis for targeted therapy directed by tumor-specific testing at either the gene or protein level. Despite rapid advances in our understanding of targeted therapy for GI cancers, the impact on cancer survival has been marginal.

    ..Can tumor response to therapy be predicted, thereby improving the selection of patients for cancer treatment?

    ..In 2000 theNCI with the European Association for Research and Treatment of Cancer, proposed a replacement of 2D measurement with a decrease in the largest tumor diameter by 30% in one dimension. Tumor response as defined would translate into a 50% decrease for a spherical lesion

    ..We must rethink how we may better determine treatment response in a reliable, reproducible way that is aimed at individualizing the therapy of cancer patients.

    ..we must change the tools we use to assess tumor response. The new modality should be based on empirical evidence that translates into relevant and meaningful clinical outcome data.

    ..This becomes a conundrum of sorts in an era of ‘minimally invasive treatment’.

    ..integrated multidisciplinary panel of international experts – not sure that that will do it

    Several years ago i heard Stamey present the totality of his work at Stanford, with great disappointment over hsPSA that they pioneered in. The outcomes were disappointing.

    I had published a review of all of our cases reviewed for 1 year with Marguerite Pinto.
    There’s a reason that the physicians line up outside of her office for her opinion.
    The review showed that a PSA over 24 ng/ml is predictive of bone metastasis. Any result over 10 was as likely to be prostatitis, BPH or cancer.

    I did an ordinal regression in the next study with Gustave Davis using a bivariate ordinal regression to predict lymph node metastasis using the PSA and the Gleason score. It was better than any univariate model, but there was no followup.

    I reviewed a paper for Clin Biochemistry (Elsevier) on a new method for PSA, very different than what we are familiar with. It was the most elegant paper I have seen in the treatment of the data. The model could predict post procedural time to recurrence to 8 years.

    • I hope we are in agreement on the fact that imaging guided interventions are needed for better treatment outcome. The point I’m trying to make in this post is that people are investing in developing imaging guided intervention and it is making progress.

      Over diagnosis and over treatment is another issue altogether. I think that many of my other posts are dealing with that.

  6. Tumor response criteria: are they appropriate?
    Future Oncology 2012; 8(8): 903-906 , DOI 10.2217/fon.12.78 (doi:10.2217/fon.12.78)
    Björn LDM Brücher, Anton Bilchik, Aviram Nissan, Itzhak Avital & Alexander Stojadinovic
    Tumor heterogeneity is a problematic because of differences among the metabolic variety among types of gastrointestinal (GI) cancers, confounding treatment response and prognosis.
    This is in response to … a group of investigators from Sunnybrook Health Sciences Centre, University of Toronto, Ontario, Canada who evaluate the feasibility and safety of magnetic resonance (MR) imaging–controlled transurethral ultrasound therapy for prostate cancer in humans. Their study’s objective was to prove that using real-time MRI guidance of HIFU treatment is possible and it guarantees that the location of ablated tissue indeed corresponds to the locations planned for treatment.
    1. There is a difference between expected response to esophageal or gastric neoplasms both biologically and in expected response, even given variability within a class. The expected time to recurrence is usually longer in the latter case, but the confounders are – age at time of discovery, biological time of detection, presence of lymph node and/or distant metastasis, microscopic vascular invasion.
    2. There is a long latent period in abdominal cancers before discovery, unless a lesion is found incidentally in surgery for another reason.
    3. The undeniable reality is that it is not difficult to identify the main lesion, but it is difficult to identify adjacent epithelium that is at risk (transitional or pretransitional). Pathologists have a very good idea about precancerous cervical neoplasia.

    The heterogeneity rests within each tumor and between the primary and metastatic sites, which is expected to be improved by targeted therapy directed by tumor-specific testing. Despite rapid advances in our understanding of targeted therapy for GI cancers, the impact on cancer survival has been marginal.

    The heterogeneity is a problem that will take at least another decade to unravel because of the number of signaling pathways and the crosstalk that is specifically at issue.

    I must refer back to the work of Frank Dixon, Herschel Sidransky, and others, who did much to develop a concept of neoplasia occurring in several stages – minimal deviation and fast growing. These have differences in growth rates, anaplasia, and biochemical. This resembles the multiple “hit” theory that is described in “systemic inflammatory” disease leading to a final stage, as in sepsis and septic shock.
    In 1920, Otto Warburg received the Nobel Prize for his work on respiration. He postulated that cancer cells become anaerobic compared with their normal counterpart that uses aerobic respiration to meet most energy needs. He attributed this to “mitochondrial dysfunction. In fact, we now think that in response to oxidative stress, the mitochondrion relies on the Lynen Cycle to make more cells and the major source of energy becomes glycolytic, which is at the expense of the lean body mass (muscle), which produces gluconeogenic precursors from muscle proteolysis (cancer cachexia). There is a loss of about 26 ATP ~Ps in the transition.
    The mitochondrial gene expression system includes the mitochondrial genome, mitochondrial ribosomes, and the transcription and translation machinery needed to regulate and conduct gene expression as well as mtDNA replication and repair. Machinery involved in energetics includes the enzymes of the Kreb’s citric acid or TCA (tricarboxylic acid) cycle, some of the enzymes involved in fatty acid catabolism (β-oxidation), and the proteins needed to help regulate these systems. The inner membrane is central to mitochondrial physiology and, as such, contains multiple protein systems of interest. These include the protein complexes involved in the electron transport component of oxidative phosphorylation and proteins involved in substrate and ion transport.
    Mitochondrial roles in, and effects on, cellular homeostasis extend far beyond the production of ATP, but the transformation of energy is central to most mitochondrial functions. Reducing equivalents are also used for anabolic reactions. The energy produced by mitochondria is most commonly thought of to come from the pyruvate that results from glycolysis, but it is important to keep in mind that the chemical energy contained in both fats and amino acids can also be converted into NADH and FADH2 through mitochondrial pathways. The major mechanism for harvesting energy from fats is β-oxidation; the major mechanism for harvesting energy from amino acids and pyruvate is the TCA cycle. Once the chemical energy has been transformed into NADH and FADH2 (also discovered by Warburg and the basis for a second Nobel nomination in 1934), these compounds are fed into the mitochondrial respiratory chain.
    The hydroxyl free radical is extremely reactive. It will react with most, if not all, compounds found in the living cell (including DNA, proteins, lipids and a host of small molecules). The hydroxyl free radical is so aggressive that it will react within 5 (or so) molecular diameters from its site of production. The damage caused by it, therefore, is very site specific. The reactions of the hydroxyl free radical can be classified as hydrogen abstraction, electron transfer, and addition.
    The formation of the hydroxyl free radical can be disastrous for living organisms. Unlike superoxide and hydrogen peroxide, which are mainly controlled enzymatically, the hydroxyl free radical is far too reactive to be restricted in such a way – it will even attack antioxidant enzymes. Instead, biological defenses have evolved that reduce the chance that the hydroxyl free radical will be produced and, as nothing is perfect, to repair damage.
    Currently, some endogenous markers are being proposed as useful measures of total “oxidative stress” e.g., 8-hydroxy-2’deoxyguanosine in urine. The ideal scavenger must be non-toxic, have limited or no biological activity, readily reach the site of hydroxyl free radical production (i.e., pass through barriers such as the blood-brain barrier), react rapidly with the free radical, be specific for this radical, and neither the scavenger nor its product(s) should undergo further metabolism.
    Nitric oxide has a single unpaired electron in its π*2p antibonding orbital and is therefore paramagnetic. This unpaired electron also weakens the overall bonding seen in diatomic nitrogen molecules so that the nitrogen and oxygen atoms are joined by only 2.5 bonds. The structure of nitric oxide is a resonance hybrid of two forms.
    In living organisms nitric oxide is produced enzymatically. Microbes can generate nitric oxide by the reduction of nitrite or oxidation of ammonia. In mammals nitric oxide is produced by stepwise oxidation of L-arginine catalyzed by nitric oxide synthase (NOS). Nitric oxide is formed from the guanidino nitrogen of the L-arginine in a reaction that consumes five electrons and requires flavin adenine dinucleotide (FAD), flavin mononucleotide (FMN) tetrahydrobiopterin (BH4), and iron protoporphyrin IX as cofactors. The primary product of NOS activity may be the nitroxyl anion that is then converted to nitric oxide by electron acceptors.
    The thiol-disulfide redox couple is very important to oxidative metabolism. GSH is a reducing cofactor for glutathione peroxidase, an antioxidant enzyme responsible for the destruction of hydrogen peroxide. Thiols and disulfides can readily undergo exchange reactions, forming mixed disulfides. Thiol-disulfide exchange is biologically very important. For example, GSH can react with protein cystine groups and influence the correct folding of proteins, and it GSH may play a direct role in cellular signaling through thiol-disulfide exchange reactions with membrane bound receptor proteins (e.g., the insulin receptor complex), transcription factors (e.g., nuclear factor κB), and regulatory proteins in cells. Conditions that alter the redox status of the cell can have important consequences on cellular function.
    So the complexity of life is not yet unraveled.

    Can tumor response to therapy be predicted, thereby improving the selection of patients for cancer treatment?
    The goal is not just complete response. Histopathological response seems to be related post-treatment histopathological assessment but it is not free from the challenge of accurately determining treatment response, as this method cannot delineate whether or not there are residual cancer cells. Functional imaging to assess metabolic response by 18-fluorodeoxyglucose PET also has its limits, as the results are impacted significantly by several variables:

    • tumor type
    • sizing
    • doubling time
    • anaplasia?
    • extent of tumor necrosis
    • type of antitumor therapy and the time when response was determined.
    The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ characteristics, a greater challenge in an era of ‘minimally invasive treatment’.
    This listing suggests that for every cancer the following data has to be collected (except doubling time). If there are five variables, the classification based on these alone would calculate to be very sizable based on Eugene Rypka’s feature extraction and classification. But looking forward, time to remission and disease free survival are additionally important. Treatment for cure is not the endpoint, but the best that can be done is to extend the time of survival to a realistic long term goal and retain a quality of life.

    Brücher BLDM, Piso P, Verwaal V et al. Peritoneal carcinomatosis: overview and basics. Cancer Invest.30(3),209–224 (2012).
    Brücher BLDM, Swisher S, Königsrainer A et al. Response to preoperative therapy in upper gastrointestinal cancers. Ann. Surg. Oncol.16(4),878–886 (2009).
    Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer47(1),207–214 (1981).
    Therasse P, Arbuck SG, Eisenhauer EA et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J. Natl Cancer Inst.92(3),205–216 (2000).
    Brücher BLDM, Becker K, Lordick F et al. The clinical impact of histopathological response assessment by residual tumor cell quantification in esophageal squamous cell carcinomas. Cancer106(10),2119–2127 (2006).

    • Dr. Larry,

      Thank you for this comment.

      Please carry it as a stand alone post, Dr. Ritu will refer to it and reference it in her FORTHCOMING pst on Tumor Response which will integrate multiple sources.

      Please execute my instruction

      Thank you

    • Thank you Larry for this educating comment. It explains very well why the Canadian investigators did not try to measure therapy response!

      What they have demonstrated is the technological feasibility of coupling a treatment device to an imaging device and use that in order to guide the treatment to the right place.

      the issue of “choice of treatment” to which you are referring is not in the scope of this publication.
      The point is: if one treatment modality can be guided, other can as well! This should encourage others, to try and develop imaging-based treatment guidance systems.

  7. The crux of the matter in terms of capability is that the cancer tissue, adjacent tissue, and the fibrous matrix are all in transition to the cancerous state. It is taught to resect leaving “free margin”, which is better aesthetically, and has had success in breast surgery. The dilemma is that the patient may return, but how soon?

    • Correct. The philosophy behind lumpectomy is preserving quality of life. It was Prof. Veronesi (IEO) who introduced this method 30 years ago noticing that in the majority of cases, the patient will die from something else before presenting recurrence of breast cancer..

      It is well established that when the resection margins are declared by a pathologist (as good as he/she could be) as “free of cancer”, the probability of recurrence is much lower than otherwise.

  8. Dr. Larry,

    To assist Dr. Ritu, PLEASE carry ALL your comments above into a stand alone post and ADD to it your comment on my post on MIS

    Thank you

  9. Great post! Dr. Nir, can the ultrasound be used in conjunction with PET scanning as well to determine a spatial and functional map of the tumor. With a disease like serous ovarian cancer we typically see an intraperitoneal carcimatosis and it appears that clinicians are wanting to use fluorogenic probes and fiberoptics to visualize the numerous nodules located within the cavity Also is the technique being used mainy for surgery or image guided radiotherapy or can you use this for detecting response to various chemotherapeutics including immunotherapy.

    • Ultrasound can and is actually used in conjunction with PET scanning in many cases. The choice of using ultrasound is always left to the practitioner! Being a non-invasive, low cost procedure makes the use of ultrasound a non-issue. The down-side is that because it is so easy to access and operate, nobody bothers to develop rigorous guidelines about using it and the benefits remains the property of individuals.

      In regards to the possibility of screening for ovarian cancer and characterising pelvic masses using ultrasound I can refer you to scientific work in which I was involved:

      1. VAES (E.), MANCHANDA (R), AUTIER, NIR (R), NIR (D.), BLEIBERG (H.), ROBERT (A.), MENON (U.). Differential diagnosis of adnexal masses: Sequential use of the Risk of Malignancy Index and a novel computer aided diagnostic tool. Published in Ultrasound in Obstetrics & Gynecology. Issue 1 (January). Vol. 39. Page(s): 91-98.

      2. VAES (E.), MANCHANDA (R), NIR (R), NIR (D.), BLEIBERG (H.), AUTIER (P.), MENON (U.), ROBERT (A.). Mathematical models to discriminate between benign and malignant adnexal masses: potential diagnostic improvement using Ovarian HistoScanning. Published in International Journal of Gynecologic Cancer (IJGC). Issue 1. Vol. 21. Page(s): 35-43.

      3. LUCIDARME (0.), AKAKPO (J.-P.), GRANBERG (S.), SIDERI (M.), LEVAVI (H.), SCHNEIDER (A.), AUTIER (P.), NIR (D.), BLEIBERG (H.). A new computer aided diagnostic tool for non-invasive characterisation of malignant ovarian masses: Results of a multicentre validation study. Published in European Radiology. Issue 8. Vol. 20. Page(s): 1822-1830.

      Dror Nir, PhD
      Managing partner

      BE: +32 (0) 473 981896
      UK: +44 (0) 2032392424

      web: http://www.radbee.com/
      blogs: http://radbee.wordpress.com/ ; http://www.MedDevOnIce.com

  10. totally true and i am very thankfull for these briliant comments.

    Remember: 10years ago: every cancer researcher stated: “look at the tumor cells only – forget the stroma”. The era of laser-captured tumor-cell dissection started. Now , everyone knows: it is a system we are looking at and viewing and analyzing tumor cells only is really not enough.

    So if we would be honest, we would have to declare, that all data, which had been produced 13-8years ago, dealing with laser capture microdissection, that al these data would need a re-scrutinization, cause the influence of the stroma was “forgotten”. I ‘d better not try thinking about the waisted millions of dollars.

    If we keep on being honest: the surgeon looks at the “free margin” in a kind of reductionable model, the pathologist is more the control instance. I personally see the pathologist as “the control instance” of surgical quality. Therefore, not the wish of the surgeon is important, the objective way of looking into problems or challenges. Can a pathologist always state, if a R0-resection had been performed ?

    The use of the Resectability Classification:
    There had been many many surrogate marker analysis – nothing new. BUT never a real substantial well tought through structured analysis had been done: mm by mm by mm by mm and afterwards analyzing that by a ROC analysis. BUt against which goldstandard ? If you perform statistically a ROC analysis – you need a golstandard to compare to. Therefore what is the real R0-resectiòn? It had been not proven. It just had been stated in this or that tumor entity that this or that margin with this margin free mm distance or that mm distance is enough and it had been declared as “the real R0-classification”. In some organs it is very very difficult and we all (surgeons, pathologists, clinicians) that we always get to the limit, if we try interpretating the R-classification within the 3rd dimension. Often it is just declared and stated.

    Otherwise: if lymph nodes are negative it does not mean, lymph nodes are really negative, cause up to 38% for example in upper GI cancers have histological negative lymph nodes, but immunohistochemical positive lymph nodes. And this had been also shown by Stojadinovic at el analyzing the ultrastaging in colorectal cancer. So the 4th dimension of cancer – the lymph nodes / the lymphatic vessel invasion are much more important than just a TNM classification, which unfortunately does often not reflect real tumor biology.

    AS we see: cancer has multifactorial reasons and it is necessary taking the challenge performing high sophisticated research by a multifactorial and multidisciplinary manner.

    Again my deep and heartly thanks for that productive and excellent discussion !

    • Dr. BB,

      Thank you for your comment.

      Multidisciplinary perspectives have illuminated the discussion on the pages of this Journal.

      Eager to review Dr. Ritu’s forthcoming paper – the topic has a life of its own and is embodied in your statement:

      “the 4th dimension of cancer – the lymph nodes / the lymphatic vessel invasion are much more important than just a TNM classification, which unfortunately does often not reflect real tumor biology.”

    • Thank you BB for your comment. You have touched the core limitation of healthcare professionals: how do we know that we know!

      Do we have a reference to each of the test we perform?

      Do we have objective and standardise quality measures?

      Do we see what is out-there or are we imagining?

      The good news: Everyday we can “think” that we learned something new. We should be happy with that, even if it is means that we learned that yesterday’s truth is not true any-more and even if we are likely to be wrong again…:)

      But still, in the last decades, lots of progress was made….

  11. Dr. Nir,
    I thoroughly enjoyed reading your post as well as the comments that your post has attracted. There were different points of view and each one has been supported with relevant examples in the literature. Here are my two cents on the discussion:
    The paper that you have discussed had the objective of finding out whether real-time MRI guidance of treatment was even possible and if yes, and also if the treatment could be performed in accurate location of the ROI? The data reveals they were pretty successful in accomplishing their objective and of course that gives hope to the imaging-based targeted therapies.
    Whether the ROI is defined properly and if it accounts for the real tumor cure, is a different question. Role of pathologists and the histological analysis they bring about to the table cannot be ruled out, and the absence of a defined line between the tumor and the stromal region in the vicinity is well documented. However, that cannot rule out the value and scope of imaging-based detection and targeted therapy. After all, it is seminal in guiding minimally invasive surgery. As another arm of personalized medicine-based cure for cancer, molecular biologists at MD Anderson have suggested molecular and genetic profiling of the tumor to determine genetic aberrations on the basis of which matched-therapy could be recommended to patients. When phase I trial was conducted, the results were obtained were encouraging and the survival rate was better in matched-therapy patients compared to unmatched patients. Therefore, everytime there is more to consider when treating a cancer patient and who knows a combination of views of oncologists, pathologists, molecular biologists, geneticists, surgeons would device improvised protocols for diagnosis and treatment. It is always going to be complicated and generalizations would never give an answer. Smart interpretations of therapies – imaging-based or others would always be required!

    Ritu

    • Dr. Nir,
      One of your earlier comments, mentioned the non invasiveness of ultrasound, thus, it’s prevalence in use for diagnosis.

      This may be true for other or all areas with the exception of Mammography screening. In this field, an ultrasound is performed only if a suspected area of calcification or a lump has been detected in the routine or patient-initiated request for ad hoc mammography secondery to patient complain of pain or patient report of suspected lump.

      Ultrasound in this field repserents ascalation and two radiologists review.

      It in routine use for Breast biopsy.

    • Thanks Ritu for this supporting comment. The worst enemy of finding solutions is doing nothing while using the excuse of looking for the “ultimate solution” . Personally, I believe in combining methods and improving clinical assessment based on information fusion. Being able to predict, and then timely track the response to treatment is a major issue that affects survival and costs!

Case Study #4:

  • Judging the ‘Tumor response’-there is more food for thought

https://pharmaceuticalintelligence.com/2012/12/04/judging-the-tumor-response-there-is-more-food-for-thought/

13 Responses

  1. Dr. Sanexa
    you have brought up an interesting and very clinically relevant point: what is the best measurement of response and 2) how perspectives among oncologists and other professionals differ on this issues given their expertise in their respective subspecialties (immunologist versus oncologist. The advent of functional measurements of tumors (PET etc.) seems extremely important in the therapeutic use AND in the development of these types of compounds since usually a response presents (in cases of solid tumors) as either a lack of growth of the tumor or tumor shrinkage. Did the authors include an in-depth discussion of the rapidity of onset of resistance with these types of compounds?
    Thanks for the posting.

  2. Dr. Williams,
    Thanks for your comment on the post. The editorial brings to attention a view that although PET and other imaging methods provide vital information on tumor growth, shrinkage in response to a therapy, however, there are more aspects to consider including genetic and molecular characteristics of tumor.
    It was an editorial review and the authors did not include any in-depth discussion on the rapidity of onset of resistance with these types of compounds as the focus was primarily on interpreting tumor response.
    I am glad you found the contents of the write-up informative.
    Thanks again!
    Ritu

  3. Thank you for your wonderful comment and interpretation. Dr.Sanexa made a brilliant comment.

    May I allow myself putting my finger deeper into this wound ? Cancer patients deserve it.

    It had been already pointed out by international experts from Munich, Tokyo, Hong-Kong and Houston, dealing with upper GI cancer, that the actual response criteria are not appropriate and moreover: the clinical response criteria in use seem rather to function as an alibi, than helping to differentiate and / or discriminate tumor biology (Ann Surg Oncol 2009):

    http://www.ncbi.nlm.nih.gov/pubmed/19194759

    The response data in a phase-II-trial (one tumor entity, one histology, one treatment, one group) revealed: clinical response evaluation according to the WHO-criteria is not appropriate to determine response:

    http://www.ncbi.nlm.nih.gov/pubmed/15498642

    Of course, there was a time, when it seemed to be useful and this also has to be respected.

    There is another challenge: using statistically a ROC and resulting in thresholds. This was, is and always be “a clinical decision only” and not the decision of the statistician. The clinician tells the statistician, what decision, he wants to make – the responsibility is enormous. Getting back to the roots:
    After the main results of the Munich-group had been published 2001 (Ann Surg) and 2004 (J Clin Oncol):

    http://www.ncbi.nlm.nih.gov/pubmed/11224616

    http://www.ncbi.nlm.nih.gov/pubmed/14990646

    the first reaction in the community was: to difficult, can’t be, not re-evaluated, etc.. However, all evaluated cut-offs / thresholds had been later proven to be the real and best ones by the MD Anderson Cancer Center in Houston, Texas. Jaffer Ajani – a great and critical oncologist – pushed that together with Steve Swisher and they found the same results. Than the upper GI stakeholders went an uncommon way in science: they re-scrutinized their findings. Meanwhile the Goldstandard using histopathology as the basis-criterion had been published in Cancer 2006.

    http://www.ncbi.nlm.nih.gov/pubmed/16607651

    Not every author, who was at the authorlist in 2001 and 2004 wanted to be a part of this analysis and publication ! Why ? Everyone should judge that by himself.

    The data of this analysis had been submitted to the New England Journal of Medicine. In the 2nd review stage process, the manuscript was rejected. The Ann Surg Oncol accepted the publication: the re-scrutinized data resulted in another interesting finding: in the future maybe “one PET-scan” might be appropriate predicting the patient’s response.

    Where are we now ?

    The level of evidence using the response criteria is very low: Miller’s (Cancer 1981) publication belonged to ”one single” experiment from Moertel (Cancer 1976). During that time, there was no definition of “experiences” rather than “oncologists”. These terms had not been in use during that time.

    Additionally they resulted in a (scientifically weak) change of the classification, published by Therasse (J Natl Cancer Inst 2000). Targeted therapy did not result in a change so far. In 2009, the international upper GI experts sent their publication of the Ann Surg Oncol 2009 to the WHO but without any kind of reaction.

    Using molecular biological predictive markers within the last 10years all seem to have potential.

    http://www.ncbi.nlm.nih.gov/pubmed/20012971

    http://www.ncbi.nlm.nih.gov/pubmed/18704459

    http://www.ncbi.nlm.nih.gov/pubmed/17940507

    http://www.ncbi.nlm.nih.gov/pubmed/17354029

    But, experts are aware: the real step breaking barriers had not been performed so far. Additionally, it is very important in trying to evaluate and / predict response, that not different tumor entities with different survival and tumor biology are mixed together. Those data are from my perspective not helpful, but maybe that is my own Bias (!) of my view.

    INCORE, the International Consortium of Research Excellence of the Theodor-Billroth-Academy, was invited publishing the Editorial in Future Oncology 2012. The consortium pointed out, that living within an area of ‘prove of principle’ and also trying to work out level of evidence in medicine, it is “the duty and responsibility” of every clinician, but also of the societies and institutions, also of the WHO.

    Complete remission is not the only goal, as experts dealing with ‘response-research’ are aware. It is so frustrating for patients and clinicians: there is a rate of those patients with complete remission, who develop early recurrence ! This reflects, that complete remission cannot function as the only criterion describing response !

    Again, my heartly thanks, that Dr.Sanexa discussed this issue in detail.
    I hope, I found the way explaining the way of development and evaluating response criteria properly and in a differentiated way of view. From the perspective of INCORE:

    “an interdisciplinary initiative with all key stake¬holders and disciplines represented is imperative to make predictive and prognostic individualized tumor response assessment a modern-day reality. The integrated multidisciplinary panel of international experts need to define how to leverage existing data, tissue and testing platforms in order to predict individual patient treatment response and prognosis.”

  4. Dr. Brucher,

    First of all thanks for expressing your views on the ‘tumor response’ in a comprehensive way. You are the first author of the editorial review one of the prominent people who has taken part in the process of defining tumor response and I am glad that you decided to write a comment on the writeup.
    The topic has been explained well in an immaculate manner and that it further clarifies the need for the perfect markers that would be able to evaluate and predict tumor response. There are, as you mentioned, some molecular markers available including VEGF, cyclins, that have been brought to focus in the context of squamous cell carcinoma.

    It would be great if you could be the guest author for our blog and we could publish your opinion (comment on this blog post) as a separate post. Please let us know if it is OK with you.

    Thanks again for your comment
    Ritu

  5. Thank you all to the compelling discussions, above.

    Please review the two sources on the topic I placed at the bottom of the post, above as post on this Scientific Journal,

    All comments made to both entries are part of thisvdiscussion, I am referring to Dr. Nir’s post on size of tumor, to BB comment to Nir’s post, to Larry’ Pathologist view on Tumors and my post on remission and minimally invasive surgery (MIS).

    Great comments by Dr. Williams, BB and wonderful topic exposition by Dr. Ritu.

  6. Aviva,
    Thats a great idea. I will combine all sources referred by you, the post on tumor imaging by Dr. Nir and the comments made on the these posts including Dr. Brucher’s comments in a new posts.
    Thanks
    Ritu

    • Great idea, ask Larry, he has written two very long important comments on this topic, one on Nir’s post and another one, ask him where, if it is not on MIS post. GREAT work, Ritu, integration is very important. Dr, Williams is one of our Gems.

    • Assessing tumour response it is not an easy task!Because tumours don’t change,but happilly our knowlege(about them) does really change,is everchanging(thans god!).In the past we had the Recist Criteria,then the Modified Recist Criteria,becausa of Gist and other tumors.At this very moment,these are clearly insuficient.We do need more new validated facing the reality of nowadays. A great, enormoust post Dr. Ritu! Congratulations!

 

Conclusions

The Voice of Aviva Lev-Ari, PhD, RN:

The relevance of the Scientific Agora to Medical Education is vast. The Open Access Journal allows EVERY Scientist on the internet the GLOBAL reach and access to Open Access published scientific contents NOT only to the subscription payer base of Journals. If you don’t have a HIGH FEE subscription you get NO access to content in the Journal, you can’t participate in Multiple Comment Exchanges. In the Medical Education context – COMMENTS are the medium to debate with peers. 

Multiple Comment Exchanges on Four articles in the Journal, above, demonstrate the vibrancy of the scientific discussion, the multiplicity of perspectives, the subjectivity of the contribution to the debate and the unique expertise and clinical experience expressed by each Scientist.

 .


A new mechanism of action to attack in the treatment of coronary artery disease (CAD), Novartis developed Ilaris (canakinumab), a human monoclonal antibody targeting the interleukin-1beta innate immunity pathway

Reporter: Aviva Lev-Ari, PhD, RN

 

Speaking at an ESC press briefing, Ridker said, “This is what personalized predictive medicine is all about.” Once a patient has experienced an MI, there is always residual risk of recurrence. Thus, he suggested that residual risk can be divided into

  • residual lipid-driven risk and
  • residual inflammatory-driven risk.

canakinumab might prove to be most useful if it were given to an identified high-responder group. Findings in the hs-CRP responders:

Patients whose hs-CRP declined to 1.8 mg/L or less had a much more robust response. In that subgroup, the number needed to treat to prevent a primary endpoint event was 50 at 2 years and 30 at 3.7 years.

He noted that after a single injection responders have a significant reduction in highly sensitive-CRP and it is those patients who would benefit from continuing on treatment.

“Maybe that first dose could be free,” Ridker added.

Co-investigator, Peter Libby, MD, of Massachusetts General Hospital, put it this way: 30 days after an MI, when a patient is on statin therapy and stable,

  • physicians could check LDL and then initiate more aggressive statin therapy if it is not well-controlled. Similarly,
  • physicians should check hs-CRP, and if it is elevated — 2.0 mg/L or higher — initiating anti-inflammatory therapy targeting interleukin-1 beta would be an option

Interestingly, the treatment had no effect on lipids, which suggests that the benefit was all attributable to the anti-inflammatory activity. 

In the Canakinumab Anti-inflammatory Thrombosis Outcomes Study (CANTOS), 150 mg of canakinumab every 3 months reduced high-sensitivity C-reactive protein (hs-CRP) levels by an average of 37% compared with placebo and achieved a 15% reduction in cardiovascular events — mostly MIs — compared with placebo, Paul Ridker, MD, reported here at the European Society of Cardiology 2017 congress.

The CANTOS findings were simultaneously published online by the New England Journal of Medicine.

After a median follow-up of 3.7 years, the event rate was 4.5 per 100 person-years in the placebo group versus 3.86 events per 100 person-years in the canakinumab 150 mg group. Two other arms — canakinumab 50 mg and 300 mg — also achieved reductions in events (4.11 and 3.90 per 100 person-years, respectively) but only the 150-mg dose achieved a statistically significant reduction.

There was no reduction in mortality. The trial recruited patients who had a history of MI and a hs-CRP level of 2.0 mg/L or higher.

  • There was no significant difference in all-cause mortality (HR for all canakinumab doses versus placebo, 0.94; 95% CI 0.83-1.06; P=0.31).

Benefits of Anti-inflammatory Canakinumab

although there was no cardiovascular mortality benefit, there was 30% reduction in need for bypass surgery, angioplasty, and heart failure — all of which means a significant improvement in quality of life. And treatment was also associated with a reduction in gout, rheumatoid arthritis, and osteoarthritis, he said.

Cancer Benefit

There was an apparent decrease in risk of cancer, a finding that was elucidated in a Lancet paper also published today. In the cancer analysis, also authored by Ridker, total cancer mortality was lower only in the 300-mg group, but “[i]ncident lung cancer (n=129) was significantly less frequent in the 150 mg (HR 0.61 [95% CI 0.39–0.97]; P=0.034) and 300 mg groups (HR 0.33 [95% CI 0.18–0.59] P<0.0001.”

Negative findings

  • Canakinumab was associated with a higher incidence of fatal infection than placebo — the rate was 0.18 in the 3,344 patient placebo group versus 0.32 among the 6,717 patients who received any dose of the drug, which worked out to 23 deaths versus 78 deaths (P=0.02).
  • VIEW VIDEO

Study Author Paul M. Ridker. Interviewed by Peggy Peck, Editor-in-Chief of MedPage Today

https://www.medpagetoday.com/meetingcoverage/esc/67529

  • VIEW VIDEO

Clinical Impact or No Clinical Impact

Anthony DeMaria, MD discusses the major trials from ESC and what impact, if any, they will have on clinical practice.
Benefit vs Price
On June 28 heart failure specialist Milton Packer, MD, wrote this in his MedPage Today blog: “My prediction: [canakinumab] may cost $64,000 for a 15-20% reduction in the risk of a major cardiovascular event, without decreasing cardiovascular death by itself.
Amgen’s Repatha (evolocumab) is a PCSK9 inhibitor that aggressively lowers lipids and is approved for patients who fail statin therapy, including patients with heterozygous or homozygous familial hypercholesterolemia. But while the lipid reductions with the PCSK9 therapy are impressive, and the FOURIER trial found a 15% reduction in events with treatment, neither evolocumab nor alirocumab (Praluent), a PCSK9 inhibitor from Sanofi/Regeneron have achieved wide uptake as payers balk at the high price tags for the drugs.
Other anti-inflammatory agents:
Ridker said. For example, “we have a [National Heart, Lung, and Blood Institute] trial of methotrexate (RA agent) that is on-going. If that proves to be effective, it would be only pennies per treatment.” At the press conference, Ridker said the methotrexate trial has “randomized about 4,000 patients, and we will need to get to 7,000 so it will be a few years before we have results.”

SOURCE

https://www.medpagetoday.com/meetingcoverage/esc/67529

176 articles on monoclonal antibody

https://pharmaceuticalintelligence.com/?s=monoclonal+antibody


The Convergence of Medical Devices & Drugs: Advances in Drug Delivery May 3, 2018 12:00 PM – 5:00 PM, Westin Hotel, Waltham, MA

Westin Waltham Boston 
70 3rd Avenue Waltham MA US 02451

MassBio’s second annual Medical Device Event will focus on opportunities and advances in drug delivery, including the unique developmental and regulatory challenges these products face, the many scientific advances in the space and new opportunities for funding.  Panelists will discuss innovation and commercialization strategies.

Advances in drug delivery technologies are improving the safety and efficacy of new and existing therapies. The success of many new therapies in development is contingent on the development of effective delivery systems.   Traditional drug delivery methods won’t work for some compounds and biologics.   Stability issues create challenges for storage and transport.  There are opportunities for combination drug delivery products to extend the patent life of drugs on the market.  From diffusion based polymer systems to complex delivery devices utilizing diagnostic sensors and sophisticated control systems for precise and timely delivery of life-saving agents, a diverse set of scientific and engineering disciplines are being brought to bear within this space.  However, combination products involve components that would normally be developed under different types of regulations, design criteria, and controls.  This symposium will explore many of the diverse aspects impacting drug delivery products.

This event will feature an active exhibit hall, panel discussions, a keynote speaker and networking sessions. This is an excellent opportunity for companies to reach a diverse audience that represents nearly every aspect of the life sciences industry, including academic researchers, entrepreneurs, device engineers and biopharma executives.

Clinicians will discuss the medical challenges for which drug delivery innovations have provided a unique solution.  Academic researchers will discuss scientific advances which may lead to breakthrough products.   Entrepreneurs will discuss strategies for funding new product ventures, and development issues specific to drug delivery products.  Corporate speakers will discuss the challenges across the value chain of manufacturing and selling combination products globally.  Regulatory speakers will address current thinking and approaches to drug delivery products within government agencies, both US and internationally.

SOURCE

https://www.massbio.org/events/the-convergence-of-medical-devices-and-drugs-advances-in-drug-delivery-2624?utm_campaign=med-device-18&utm_medium=email&utm_source=email-signature&utm_content=&utm_term=

Registration

12:00 pm  12:30 pm

Opening Remarks

12:30 pm  12:45 pm

Keynote Presentation

12:45 pm  1:15 pm

Innovation & Development Panel

1:30 pm  2:45 pm

Networking Break

2:45 pm  3:15 pm

Commercialization Pathways Panel

3:15 pm  4:30 pm

Networking Reception

4:30 pm  5:30 pm

Speakers

  • Jessica Ballinger, Chief Operating Officer, Lyndra
  • Maria Berkman, MD, MBA, Director and Head of MedTech practice, Broadview Ventures
  • Kristina Bieker-Brady, Ph.D., Partner, McDermott Will & Emery LLP
  • Benjamin S. Bleier, MD, FACS, FARS, Associate Professor, Director of Endoscopic Skull Base Surgery, Co-Director Center for Thyroid Eye Disease and Orbital Surgery, Massachusetts Eye and Ear Infirmary, Harvard Medical School
  • Brent Buchine, Ph.D., Co-Founder and CTO, Windgap Medical, Inc.
  • Michael J. Cima, Ph.D., Associate Dean of Innovation, MIT
  • Bob Coughlin, President & CEO, MassBio
  • Harry Glorikian, General Partner, New Ventures Funds
  • Paul Just, PharmD, Senior Principal, Medical Device Health Economics, ICON plc
  • Maria Palasis, President and CEO, 480 Biomedical, Inc.
  • Pamela J. Weagraff, Director, MedTech Regulatory, IQVIA
  • Andrew Wright, Vice President, Digital Medicine & Medical Device Division, Otsuka Pharmaceutical Companies

2018 CHI’s BioIT World conference & Expo, May 15 – 17, 2018, Boston, MA – Seaport World Trade Center

http://www.bio-itworldexpo.com/

LPBI Group will cover Track 7: NGS in Real Time

@pharma_BI

@AVIVA1950

Aviva Lev-Ari, PhD, RN will be in attendance

 

 

 

 

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2018 Plenary Keynote Speakers

Mark BoguskiMark Boguski, MD, PhD
Executive Vice President and Chief Medical Officer, Liberty BioSecurity
tanya cashTanya Cashorali
Founder, TCB Analytics 
John ReyndersJohn Reynders, PhD
Vice President, Data Sciences, Genomics, and Bioinformatics, Alexion Pharmaceuticals, Inc.

 

Jerald SchindlerJerald Schindler, DrPH
Vice President, Biostatistics, Merck Research Laboratories (Retired)
Yu LihuaLihua Yu, PhD
Chief Data Science Officer, H3 Biomedicine

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TUESDAY, MAY 15

7:00 am Workshop Registration Open and Morning Coffee

 

8:00 – 11:30 Recommended Morning Pre-Conference Workshops*

W4. Introduction to Scalable and Reproducible RNA-Seq Data Processing, Analysis, and Result Reporting Using AWS, R, knitr, and LaTex

12:30 – 4:00 pm Recommended Afternoon Pre-Conference Workshops*

W13. Leveraging Cloud Technologies to Enable Large-Scale Integration of Human Genome and Clinical Outcomes Data

* Separate registration required.

2:00 – 6:30 Main Conference Registration Open

4:00 PLENARY KEYNOTE SESSION

Click here for detailed information

5:00 – 7:00 Welcome Reception in the Exhibit Hall with Poster Viewing

WEDNESDAY, MAY 16

7:00 am Registration Open and Morning Coffee

8:00 PLENARY KEYNOTE SESSION

Click here for detailed information

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

LARGE-SCALE RNA-SEQ AND GENE EXPRESSION VARIABILITY

10:50 Chairperson’s Remarks

11:00 KEYNOTE PRESENTATION: RNA-Seq X: Look Back and Look Ahead

Shanrong Zhao, PhD, Director, Computational Biology and Bioinformatics, Pfizer, Inc.

Since Dr. Mortazavi published his groundbreaking research entitled “Mapping and Quantifying Mammalian Transcriptomes by RNA-Seq” in Nature Methods in 2008, RNA-seq has evolved rapidly and revolutionized biological research, drug development and clinical diagnostics. 2018 is the 10-year anniversary of RNA-seq, and it’s the right time to look back and look forward.

11:30 LCA: A Robust and Scalable Algorithm to Reveal Subtle Diversity in Large-Scale Single-Cell RNA Sequencing Data

Xiang Chen, PhD, Assistant Member, Department of Computational Biology, St. Jude Children’s Research Hospital

We developed Latent Cellular Analysis (LCA), a machine learning based single-cell RNA sequencing (scRNA-seq) analytical pipeline that combines similarity measurement by latent cellular states and a graph based clustering algorithm featuring dual-space model search for both the optimal number of subpopulations and the informative cellular states distinguishing them. LCA has proved to be robust, accurate and powerful by comparison to multiple state-of-the-art computational methods on large-scale real and simulated scRNA-seq data.

12:00 pm Presentation to be Announced

 

12:15 RSEQREP: An Open-Source Cloud-Enabled Framework for Reproducible RNA-Seq Data Processing, Analysis & Result Reporting

Johannes Goll, Director, Bioinformatics, The Emmes Corporation

RSEQREP (RNA-Seq Reports) is a new open-source cloud-enabled framework that allows researchers to execute start-to-end RNA-Seq analysis to characterize transcriptomics changes in human cells following treatment. It outputs dynamically generated reports using R and LaTeX. We provide results for a published RNA-Seq study to characterize transcriptomics changes following influenza vaccination.

12:30 Session Break

WuXi_Nextcode_notagline12:40 Luncheon Presentation I: Querying of 100k Genomes Using Google Cloud

Hákon Gudbjartsson, PhD, Chief Informatics Officer, WuXi NextCODE

Hákon Gudbjartsson will demonstrate the power of the GOR database in real time. GORdb is used to organize, mine and share massive genome datasets, providing a global architecture for the largest precision medicine efforts worldwide. It’s designed to enable fast, computationally-efficient use of sequence data, and allows for the query and application of data in the context of reference sets.

1:10 Luncheon Presentation II (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own

1:40 Session Break

OPTIMIZING GENE BASES WITH CODON USAGE

1:50 Chairperson’s Remarks

Leonard Lipovich, PhD, Associate Professor with Tenure, Center for Molecular Medicine and Genetics, Wayne State University

1:55 Analysis of Codon Optimized Therapeutic Proteins Using Ribosome Profiling

Chava Kimchi-Sarfaty, PhD, Research Chemist, Principal Investigator, OTAT Acting Deputy Associate Director for Research, Division of Plasma Protein Therapeutics, Office of Tissues and Advanced Therapies, FDA | CBER | OTAT

Codon optimization is a genetic engineering technique used to improve the yield of recombinant therapeutic proteins. Despite being used ubiquitously to increase protein expression, codon optimization requires widespread substitution of synonymous codons across the native expression sequence. This degree of genetic manipulation can carry consequences, including altered conformation of the recombinant product. These unforeseen modifications can have impacts on protein function and health outcomes, and are of high regulatory importance. To study these techniques, we have used ribosome profiling, a technique used to characterize the translation pattern of the ribosome across the mRNA transcript. In this technique, actively translating ribosomes are cross‐linked to mRNA and is followed by nuclease digestion of mRNA not protected by a ribosome, generating short mRNA fragments (called “ribosome footprints”). These fragments are sequenced and aligned to generate a differential coverage map across portions of the transcript. This technique provides insight into the relative translation efficiency in a given area of the transcript. We have analyzed the ribosome profiling data for relationships to codon usage. By identifying regions of differential ribosome profiling patterns between wild type and codon optimized transcripts, we aim to create a method of selecting regions to leave unmodified, allowing recombinant proteins to benefit from increased expression while maintaining the integrity and safety of the protein product. Codon optimization as a technique relies heavily on accurate codon usage statistics of the organism in question, to identify rare codons to be replaced with common codons for an increase in translation efficiency. However, previous databases containing this information were either outdated or limited in scope. To address this gap in knowledge, we constructed a new database containing codon usage tables for all the species in GenBank and RefSeq. We designed a program in Python to download, parse, and organize all the sequence data available in these two repositories, and in Javascript designed an accessible web portal available to the public to query the new database. The new HIVE‐CUTs database contains substantially more organisms and coding sequence data and is a dramatic improvement upon prior databases. This tool will aid in the effective implementation of codon optimization techniques and other areas of recombinant protein design.

2:25 Multidimensional Global Proteogenomics Identifies Persistent Ribosomal In-Frame Mis-Translation of Stop Codons as Amino Acids in Multiple Open Reading Frames from a Human Breast Cancer Long Non-Coding RNA

Leonard Lipovich, PhD, Associate Professor with Tenure, Center for Molecular Medicine and Genetics, Wayne State University

Two-thirds of the ~60,000 human genes (www.gencodegenes.org) do not encode known proteins, and aside from long non-coding RNA (lncRNA) genes with recently characterized functions, the possibility that these poorly understood genes’ transcripts serve as de-facto unconventional messenger RNAs has not been formally excluded. Our group was the first to use direct evidence from protein mass spectrometry, preceding efforts that employed indirect evidence from ribosome profiling, to demonstrate that specific lncRNAs are recurrently and nonrandomly translated in human cells (Bánfai et al 2012, Genome Research 22:1646-1657). In our current study, we integrated RNAseq, ribosome profiling, and mass spectrometry to globally assess lncRNA translation in human estrogen receptor alpha positive MCF7 breast cancer cells. We identified 27 peptides, mapping to multiple sense-strand open reading frames (ORFs) of the lncRNA gene MMP24-AS1, united by a novel and highly unconventional property: the existence of these peptides can only be explained by stop-to-nonstop in-frame replacements of specific UAG and UGA (but not UAA) stop codons by amino acids. This result, validated by the absence of any genomic mutations, polymorphisms, and RNA editing events in genomic and cDNA targeted resequencing, represents an unprecedented apparent gene-specific violation of the Genetic Code in human breast cancer cells, and hints at a new mechanism enhancing the combinatorial complexity of the cancer proteome.
[Note 1: This work has been funded in its entirety by the NIH Director’s New Innovator Award 1DP2-CA196375 to LL.]
[Note 2: This project encompasses collaborations. A full listing of co-authors will be shown during the talk.]

Seven Bridges Genomics2:55 CO-PRESENTATION: Workflow Optimization for NGS Discovery – How to Drive BIX Insights

Jack DiGiovanna, PhD, General Manager, NGS Applications and Services, Seven Bridges

Isaac M. Neuhaus, PhD, Director, Computational Genomics, Bristol Myers Squibb

3:25 Refreshment Break in the Exhibit Hall with Poster Viewing

NGS DATA ANALYSIS, INTEGRATION, INTERPRETATION, AND VISUALIZATION

4:00 Variant Query Tool: Drag & Drop for a Scalable, Server-Less, Web UI to Querying Annotated Variants

William Van Etten, Senior Scientific Consultant, BioTeam

It’s a challenge to build an environment that provides real-time querying of reads and annotated variants for genomics research, requiring significant human and computational resources. Whether tens or thousands of genomes, the barrier to entry can be high for the biologists/geneticist, who might not also be computer scientist. BioTeam has developed a simple tool that leverages several AWS services (S3, Athena, Lambda, Cognito, IAM, CloudWatch) to enable a biologists/geneticist to drag & drop VCF and BAM files onto an S3 bucket, then point their web browser at this bucket, to provide a scalable, server-less, web UI to querying the reads and annotated variants within these files. We aim to demonstrate, explain, and promote what we’ve learned from this proof of concept software development in the hope that others might benefit from our experience.

 4:30 Building a GXP Validated Platform for NGS Analysis Pipelines

Anthony Rowe, PhD, Business Technology Leader, R&D IT, Janssen R&D LLC

An NGS applications approach the clinic the bioinformatics pipelines used to analyze the data have to be validated to demonstrate their correctness. This talk will present Janssen approach to deploying validated NGS applications with specific focus in microbiome metagnomics.

Sapio Sciences5:00 LIMS or ELN, Which Do You Need?

Kevin Cramer, CEO, Sapio Sciences

Both Biotech and Pharma need Laboratory Information Management (LIMS) and Electronic Lab Notebook (ELN) capabilities. Sapio has eliminated the barriers between these two product areas by leveraging its more than decade of unique experience offering both LIMS and ELN solutions and combining the key features of each solution into one, best of breed, product: Exemplar ELN Pro.

5:15 Sponsored Presentation (Opportunity Available)

5:30 Best of Show Awards Reception in the Exhibit Hall with Poster Viewing

7:00 – 10:00 Bio-IT World After Hours @Lawn on D

THURSDAY, MAY 17

7:30 am Registration Open and Morning Coffee

8:00 PLENARY KEYNOTE SESSION & AWARDS PROGRAM

Click here for detailed information

9:45 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced

APPLICATION OF NGS TO ONCOLOGY, IMMUNOLOGY, DIAGNOSTICS, AND THERAPEUTIC DEVELOPMENT

10:30 Chairperson’s Remarks

10:40 Instantiating a Single Point of Truth for Genomic Reference Data

David Herzig, Scientist, Research Informatics, Roche Pharmaceuticals

This talk will exemplify how expression and mutation data were made actionable by consolidating a scattered landscape of genomic reference data into a real SPoT.

11:10 A Network-Based Approach to Understanding Drug Toxicity

Yue Webster, PhD, Principal Research Scientist, Informatics Capabilities, Research IT, Eli Lilly and Company

Despite investment in toxicogenomics, nonclinical safety studies are still used to predict clinical liabilities for new drug candidates. Network-based approaches for genomic analysis help overcome challenges with whole-genome transcriptional profiling using limited numbers of treatments for phenotypes of interest. Herein, we apply co-expression network analysis to safety assessment using rat liver gene expression data to define 415 modules, exhibiting unique transcriptional control, organized in a visual representation of the transcriptome. Compared to gene-level analysis alone, the network approach identifies significantly more phenotype-gene associations, including established and novel biomarkers of liver injury.

11:40 Sponsored Presentation (Opportunity Available)

12:10 pm Session Break

12:20 Luncheon Presentation (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own

1:20 Dessert Refreshment Break in the Exhibit Hall with Poster Viewing

DATA MINING FOR DISEASE CLASSIFICATION

1:55 Chairperson’s Remarks

John Methot, Director, Health Informatics Architecture, Dana-Farber Cancer Institute

2:00 Disease Classification in the Era of Data-Intensive Medicine

Kanix Wang, PhD, Research Professional, Booth School of Business, Institute for Genomics & Systems Biology, University of Chicago

We used insurance claims for over one-third of the U.S. population to create a subset of 128,989 families (481,657 unique individuals). Using these data, we estimated the heritability and familial environmental patterns of 149 diseases. We then computed the environmental and genetic disease classifications for a set of 29 complex diseases after inferring their pairwise genetic and environmental correlations.

2:30 Enviro-Geno-Pheno State Approach and State-Based Biomarkers for Differentiation, Prognosis, Subtypes, and Staging

Lei Xu, PhD, Director, Centre for Cognitive Machines and Computational Health; Zhiyuan Chair Professor, Department of Computer Science and Engineering, Shanghai Jiao Tong University

In the joint space of geno-measures, pheno-measures, and enviro-measures, one point represents a bio-system behavior and a subset of points that locate adjacently and share a common system status represents a ‘state’. The system is characterized by such states learned from samples. This enviro-geno-pheno state is considered a biomarker, indicating ‘health/normal’ versus ‘risk/abnormal’ together with its associated enviro-geno-pheno condition.

3:00 PANEL DISCUSSION: Can We Improve Breast Cancer Patient Outcomes through Artificial Intelligence?

Maya Said, ScD, President & CEO, Outcomes4me, Inc. (Moderator)

Panelists:
Regina Barzilay, PhD, MacArthur Fellow and Delta Electronics Professor, Massachusetts Institute of Technology (MIT) Department of Electrical Engineering and Computer Science; Member, Computer Science and Artificial Intelligence Laboratory, MIT

Fionnuala (Finn) Doyle, Vice President and Global Head of Policy and Healthcare Systems, Novartis

Kevin Hughes, MD, Co-Director, Avon Breast Evaluation Program, Massachusetts General Hospital; Associate Professor of Surgery, Harvard Medical School; Medical Director, Bermuda Cancer Genetics Risk Assessment Clinic

Newly diagnosed cancer patients attempting to understand their treatment options face the overwhelming task of filtering an information deluge, much of which is irrelevant, outdated and occasionally inaccurate. Additionally, matching their diagnosis to best-in-class treatments or potential clinical trials, while simultaneously learning to navigate an extremely complex healthcare system is daunting, even for the most highly trained physicians. We will explore various platforms aimed at improving patient outcomes by leveraging technology to help educate, track, and connect patients with personalized resources while simultaneously working to improve the care continuum and the development of new treatments. We will explore the nexus of healthcare networks and their IT systems, clinical decision-making and delivery, R&D, and patients, for whom we all create our innovation solutions. Attendees will be interested to understand how various groups are working to increase value across the entire system by bringing laboratory, clinical and pharmaceutical science, real-world evidence and patient-reported data together with technology and artificial intelligence to solve health challenges. These approaches offer the opportunity to generate deeper insights into how therapies perform in the real world and harness that understanding to improve efficiency, effectiveness, value, and ultimately, patient care.

4:00 Conference Adjourns

SOURCE

http://www.bio-itworldexpo.com/next-gen-sequencing-informatics/


Synopsis for AI & Machine Learning in Clinical Trials, APRIL 12, 2018 PFIZER INNOVATION RESEARCH LAB – CAMBRIDGE, MA

 

Aviva Lev-Ari, PhD, RN, Director and Founder of  LPBI Group

will attend and cover in Real Time the Conference 

@pharma_BI

@AVIVA1950

  • Tweets for AI and Machine Learning in Clinical Trials April 12th, 2018 hosted at Pfizer’s Innovation Research Lab in Cambridge, MA @AVIVA1950 @pharma_BI

https://pharmaceuticalintelligence.com/2018/04/12/tweets-for-ai-and-machine-learning-in-clinical-trials-april-12th-2018-hosted-at-pfizers-innovation-research-lab-in-cambridge-ma-aviva1950-pharma_bi/

About Aviva Lev-Ari, PhD, RN and LPBI Group

 

 

AI and Machine Learning in Clinical Trials

April 12th, 2018 hosted at Pfizer’s Innovation Research Lab in Cambridge, MA

1 Portland St, Cambridge, MA 02139

With case studies from Pfizer, Novartis, Merck, AstraZeneca, MIT, Takeda, Sanofi & more, you will not
want to miss the latest in leveraging AI and Machine Learning in Clinical Trials.

#Pfizer #Merck #Sanofi #AstraZeneca #Novartis #Takeda #BMS #Biogen #GSK #MIT #Medable #Saama #RapidMiner

100+ innovators, data scientists, informatics, senior clinical trials execs &amp; tech experts will convene to
discuss advances in artificial intelligence, machine learning, &amp; clinical study data analytics.

Faculty of Advisors and Speakers:

Dan Karlin, Head of Digital Medical, Informatics, Regulatory Strategy, Pfizer
Joseph Lehar, Exec. Dir, Computational Biology, Merck
David Tester, Head, Data Sciences &amp; Engineering, Chief Data Office, Sanofi
Bhaskar Dutta, Principal Scientist, Advanced Analytics Center, AstraZeneca
Jonas Dorn, Project Manager, Digital Health, Novartis
Jyoti Shah, Assoc. Dir, Data Development, Merck
Raj Bandaru, Sr. Director, Data Sciences Strategy, Sanofi
Ronald Dorenbos, Assoc. Dir, Materials Innovation, Takeda
Zeshan Farooqui, Sr. Clinical Site Manager, BMS
Shwen Gwee, Head, Digital Strategy, Global Clinical Ops, Biogen
Munther Baara, Head, New Clinical Paradigm, Pfizer
Shyamal Patel, Sr. Manager, PfIRe Lab, Pfizer
Bill Tobia, Lead Clinical Research Instructor, GSK
Regina Barzilay, Delta Electronics Professor, MIT
Amir Lahav, Digital Innovation Lead, Pfizer
Michelle Longmire, CEO, Medable
Karim Damji, SVP Product and Marketing, Saama
Malai Sankarasubbu, VP, AI Innovation, Saama
Ingo Mierswa, Founder/President, RapidMiner

You can take a look at the latest agenda here: http://panagorapharma.com/ai/schedule/

You can register at the following link using the promo code BOSTONBIOTECH25 for 25% off
registrations: https://panagorapharma.com/ai/registration/

If you have any other questions, you can reach out to the organizer:

Doug Lavender
CoFounder
PanAgora Pharma
Doug@panagoraconferences.com
Phone: 203-253- 6401

 

CORE THEMES:

1. An Exploration of Machine Learning for Clinical Study Data
2. Natural Language Processing (NLP) for Patient Voice Analysis via Social Channels
3. Machine Learning and Artificial Intelligence for Recruitment
4. The Potential of Machine Learning and AI for Adverse Event Identification
5. Real-time Patient Data Analysis

AGENDA for Thursday, April 12th, 2018

8:00 – 9:00 am Conference Registration Open in Pfizer Lobby – 1 Portland Street, Cambridge, MA

9:00 – 9:10 am Opening Remarks from Conference Chairman

Robert “Joe” Mather, Executive Director, Head of Digital Collaborations, Pfizer

9:10 – 9:50 am KEYNOTE PANEL: AI & ML to Support Clinical Trials – Where do we begin?
The internet of things, mHealth, wearable and sensor-enabled devices present an
unprecedented opportunity for accelerated data collection. What does it mean for life
sciences – are we prepared to handle the influx of data, and create valuable visibility to
accelerate trials? Where should we start? What are the best current applications? How can
we leverage AI and Machine Learning for Adverse Event Identification?

David Tester, Head, Data Science & Engineering, Chief Data Office, Sanofi

  • Do exploratory AI & ML outside the context of Clinical Trials 1st

Joseph Lehar, Executive Director, Computational Biology, Merck

  • Oncology – images of response to treatment are complex, Pathology is assisted by AI
  • AI can assist in cell classification
  • Biggest opportunity of AI %& ML in Immunology, use non invasive medium even behavioral indicators
  • Informed Consent in Clinical Trials
  • Development of AI models to avoid bias
  • Monitoring the Trials identify signals

Bhaskar Dutta, Principal Scientist, Advanced Analytics Center, AstraZeneca

  • Structure exploration in first study, signals used in second study
  • Even in Informatics groups there can be and there is resistance to acceptance of AI and ML
  • 80%-90% clean the data holistic data view integration and Privacy
  • pooling data sets across companies for benefits of sampling: Parkinson Disease case
  • Patients Voice in a Biomarker study as partners vs Patients as Customers

Moderator: Robert “Joe” Mather, Exec. Dir, Head of Digital Collaborations, Pfizer

  • Data sharing across the organization
  • How the audience feel about sharing code not only data

 

9:50 – 10:20 am CASE STUDY: Making Sense of Sensor Data: A Case Study in Data Quality Evaluation

Bhaskar Dutta, Principal Scientist, Advanced Analytics Center, AstraZeneca

  • Making sense of sensor data – 40 clinical data scientists and expanding
  • Tactical impact, Strategic build, Horizon Scanning &evaluaiton capabilities, Quantitative Solutions
  • % of Healthcare spending of GDP: LOWER THE % BY DIGITAL TECHNOLOGIES
  • Improve adherence no need of new drugs
  • 70% of Patients are interested in Monitoring their Health digitally
  • wearable sensors – will increase the quality of monitoring
  • Burden of Chronic disease: i.e., Asthma (23Millions), Diabetes (29Million)
  • COst direct and Indirect
  • Patient Needs
  • Challenging in using digital solutions: Lack of integration,
  • Values: to Patients, to HCP, Pharma: Drug discovery, Drug Cost
  • Digital-solutions Lifecycle: Pharma perspective: Need characterization, device sensor characterization,
  • at AstraZeneca: Project – iPREDICT – individualize PREdiction of DIsease Control using digital sensor Technology
  • Device Brands and their Price to Consumer: ZephyrBioPatch, Garmin Vivosmart, MS Band 2, GoBe, HealthPatch MD, BodyGardian, BioPatch
  • Usability Survey: Ease of setting up, Ease of use, 1st impression, comfort, likely to recommend
  • Data capturing: Missing, quality of recording – data quality evaluation: signal to noise ratio
  • poor compliance
  • Data Privacy – GPS data is the most PRIVATE: de-identification of IDs, GPS can generate identifiable data
  • Integration with other data streams
  • Six different Groups: Patient cnetrality, Applications Usability,
  • They are hiring in the MD area

 

10:20 – 10:50 am Using AI and Machine Learning to Improve Clinical Trials

• Clinical trial dedicated mobile apps can improve patient experience in clinical trials and
increase data collection and yield,
• Advanced analytics on patient data
§ HIPAA compliance, data collection & analysis

Michelle Longmire, CEO, Medable

  • Enabling Direct personalized medicine
  • current process: 1-5 drugs >$2Bil, 12 years
  • Apply AI in a Case study on mild cognitive impairment:
  1. Recruitment,
  2. Trial (drug efficacy)
  3. Endpoint (crude assessment)
  • AI – From Engagement to Insight:
  1. Trial Process, – identify Patients in populations before onset of disease
  2. Discovery, – Adaptive Trials
  3. Transformation – Digitome, Digital Biomarkers
  • Input: Patient reported data – to measure daily progress
  • Probabilistic condition for algorithm development
  • Input: Smartphone sensors: 6-minute walk
  • Input: Contextual data – Location, air quality, weather, disease & crime
  • Input: VOICE: Google Home, Amazon Alexa, Apple: Siri
  • Input: Devices: fitbit, Tomtom, biovation – Swiss company – 6 paramenters per second: Cognition applications
  • Bayesian Nets: Conditional probabilities
  • Deep learning: Pathern in data : Problem/data
  • Partnering with other Medical Centers

MEDABLE INSIGHT: Signature of Digitome

  • AI platform
  • Choose form anumber of Neural Networks (NN) ‘pattern’ to allow
  • Train Multiple NN, Time series Data, Visualization: View Data
  • Cerebrum Demo: Correlate patterns

10:50 – 11:10 am NETWORKING COFFEE AND REFRESHMENT BREAK

11:10 – 11:40 am CASE STUDY: Machine Learning for Clinical Study Data

Shyamal Patel, Sr. Manager, PfIRe Lab, Pfizer

SEE Digital Biomarkers Journal

  • DIGITAL biomarkers: from algorithms to Endpoints
  • Algorithms (gait speed, HR)–>> Biomarkers (Change is stat is it change in Disease stage?)–>>> Endpoints (relevant for target)
  • Wearable devices are tight coupled on body for continuous monitoring
  • smartphone: Sensor
  • connect devices
  • iPhone – Sensor packed powerhouse: Movement, Location, Context, Emotion (Camera, microphone)
  • 70% of data is unstructured: Text, image, video  – SOURCE: IBM
  • Why use AI for building digital biomarkers: AI: Data _ Answers =Rules vs classic Programming: Data + rules = Answers
  • AI enables:
  1. Learn efficintly large data sets
  2. make updates when more data becomes available
  3. Deploy at scale across platforms

DEEP Learning: automated driving, Object recognition, robotics, speech recognition

Case Study 1: Implement Heuristic algorithms (published in literature) Evaluate Performance (agreement with clinical ratings under controlled conditions) Train Machine Learning Models (Annotation as ground truth) to AI models

  • detect hand tremor – Quantify Tremor

Outcomes: 

  1. achieve significant reduction in false positive rate
  2. strong agreement with ratings provided by trained clinical raters

Case Study 2: Mining the sound signal for biomarkers

Outcomes:

  1. 85% accuracy in hackaton

Evaluating AI driven Digital Biomarkers:

Accuracy – Problem: Over fitting

Speed

Explainability – How does the model works? – understand the trade offfs

Scalability – do not be a hammer looking for a nail

 

11:40 – 12:10 pm Accelerating Clinical Trials using Natural Language Understanding

Pharma has a big text problem. Lots of useful information buried in unstructured data
formats that is difficult to use. Natural Language Understanding will help to turn what was
once unusable data into meaningful insights that can be applied to the clinical trial
development continuum. NLU engines also open up the possibility for users to have a more
interactive relationship with their vast data stores using speech or chat messaging in a
conversational experience
Come and see how we are using Natural Language Understanding to solve problems:
• Adverse events in the real world and clinical trials
• Better matched patients for on-going clinical trials
• Hidden associations from interactions between physiology, therapies, and clinical
outcomes

Karim Damji, SVP Product, Saama
Malai Sankarasubbu, VP of AI Research, Saama

  • Too many variations
  • ADE – Adverse Drug Event extraction from Biomedical Text

Data Manager: Delivers Clinical Data Analytics as a Service using Saama platform 

Implementation of dashboard: Smart Assistant for Clinical Operations:

  • Initiate a conversation over multiple natural channels of engagement
  • Identify intent and entity Need for NLU engine !!!!!
  1. Intent extractor
  2. Entity Extractor
  3. Conversation Experience (CX): One question per one answer – not a good CX

Saama: ChatBot Voice interaction

  • Rank studies on Pancreatic Cancer in ClinicalTrials.gov by Inclusion vs Exclusion Criteria
  • Entity extraction and Patinet matching for EHR Data
  1. Protein
  2. Chemical compound
  3. Organism
  4. Environment
  5. Tissue
  6. Disease/phenotype
  7. Gene Ontology Term

12:10 – 12:40 pm CASE STUDY: Bringing Digital Health and Artificial Intelligence to Merck

Merck is building up digital health capabilities to increase patient engagement, improve trial
performance, and develop clearer disease phenotypes. I will describe some efforts across
the organization in this area & provide examples of smart trials / AI collaborations underway.

Joseph Lehar, Executive Director, Computational Biology, Merck

  • Digital health innovations at Merck
  1. quantitative phyenotypes – clearer disease signals
  2. trial performance – more effective and more efficient
  3. Patient outcomes – Better ones
  4. Data analytics & Infrastructure – enabling 1,2,3
  • Smart trials: pacient-centric studies
  • Pilot studies: Smart dosing, sampling and analytics
  • at home vs at clinic
  • smart pill packs daily blood spot for PK/DNA, e-Diary
  • less expensive sampling
  • Key findings: More trials should have smart monitoring
  • Future expansion: Better, more relevant, wider: Less invasive , Apply to active clinical trials , scale up to larger populations
  • Collaborate with big Technology companies on AI
  • Flexible, scientific partnerships
  • Projects with like success sooner
  • Projects underway or being actively planned
  • Value-based models on Trials outcomes
  • Cross functional collaborations: Organizations, Projects: i.e., Oncology, Objectives

 

12:40 – 1:00 pm SINEQUA PRESENTATION

Jeff Evernham, Sinequa

evernham@sinequa.com

  • Content of the data: Expand, Link, Enrich, Improve
  • Data set Index
  • Row IndexStructured and Unstructured (Textual)
  • DIscovery: Common variables across all data sets
  • Cognitive Analytics: SEARCH, NLP, Integrated ML
  • Single study –>> Multiple Studies –> numerical variables –>> Enriched categorical variables Unstructured data

1:00 – 1:50 pm EXECUTIVE NETWORKING LUNCHEON

1:50 – 2:15 pm CASE STUDY: We want to teach a machine to think like a physician, but how do we tell how

a physician thinks?
Inter- and intra-rater variability can severely impact the data quality of our clinical trials. If we
could teach machine learning algorithms to assess patients like experienced physicians, we
would have every patient assessed the exact same way across all the sites in a clinical trial.
As a bonus, we could make these medical assessments available in underserved areas of the
world. However, how can we train a machine learning algorithm on data annotated by
humans, if we know that those human annotations are unreliable? We will present a
framework, and the journey that led us to it, that allows combining the judgments of
multiple human raters into one consensus scale and thus provide high quality ground truth,
an aspect of machine learning that doesn’t always get the attention it deserves.

Jonas Dorn, Digital Solutions Director, Novartis

  • Rater consistency is limited given by n-Raters to K-Patients – Human consistency is limited: Disease severity score assigned
  • ML –>> Scores are generated
  • What is ground truth to be considered GOOD?
  • Comparative video rating
  • Converting ranking into scores, “true Score”
  • True score + uncertainty + rater consistency – compare realization – compare realization to threshold, comes with uncertainty
  • Combine all rating by all doctores = continuous consensus score (with uncertainties) vs Coarse ratings (raw/consensus)
  • Create consistent score through comparisons
  • Conclusion: Humans are bad at absolute ratings but good at comparison
  • Comparison-based enable virtual rating

2:15 – 2:45 pm PANEL DISCUSSION: Hearing the Voice of the Patient – How Ambient Listening Devices and Artificial Intelligence Can Improve the Clinical Trial Experience

The healthcare industry, and in particular, the clinical research sector, has recently focused
its attention on achieving “patient-centricity”. Driven by the desire to better engage clinical
trial volunteers, coupled by the need to demonstrate value-added medical products, this
has become much more than the latest buzz word. However, once the trial begins, the
patient oftentimes may feel isolated in the process – quite simply, they need to ask
questions and receive answers that they can understand. Is this an opportunity to effectively & efficiently use ambient listening devices?

How can we leverage AI and Machine Learning for the detection of adverse events, using NLP and other strategies for analysis?
Amir Lahav, Digital Innovation Lead, Rare Disease Research Unit, Pfizer

  • speech technology – voice activated mechanism
  • voice recording for Ataxia Patients – for interaction with Patients
  • Accustic pattern recognition analysis of Human voice detects Asthman or CVD in Patient : voice for detection of disease: Stroke Patient,

Zeshan Farooqui, Sr. Clinical Site Manager, Bristol-Myers Squibb

Malai Sankarasubbu, VP of AI Research, Saama

  • Multiple Indexes

Moderated by: Bill Tobia, Lead Clinical Research Instructor, GSK

Voice of patient on audio technology

2:45 – 3:15 pm CASE STUDY: Clinical Data Integration from Translational Modeling Using Machine

Learning

Raj Bandaru, Sr. Director, Sr. Director, Translational Informatics, Sanofi

  • Clinical Data Integration for Translational Modeling
  • Challenges of Data Discovery Integration of Clinical Data
  • Automated Data Cataloging
  • Data DIscovery – 80% effort
  • Crawler – Bayesian machine learning – >> data Catalog (Index) –>>  Meta Data (Information) –>>> Elastic Data– >> synonyms and hierarchhical search –>. Ontologies and Access Management
  • Probabilistic model –>> no need for complete ontologies
  • self learning, self maintaining, meta data management, Data on demand, LOW of no IT support, cost a fraction of dat integration projects
  • GOAL: develop a classifier that predicts data class and relevnce to the question being asked
  • Metadata driven Risk-based De-Identification Strategy: Internal Use, External Use
  • Data Analytics Ask a question using Amazon Alexa
  • Data science and knowledge management Team

2:50 – 3:10PM Moving beyond Actigraphy: Using AI to make sense of multi-parameter wearable sensor data

Chris Economos, VP of Business Development, PhysIQ – AI for Personalized Anomaly Detection

  • Contnuous Biosensor Data +Deep Learning to Potentially DIagnose Heart Hailure Likelihood of Heart FAilure derived from Activity Alone: Heart Failure vs Normal Vs Cancer Treatment vs COPD
  • Activity + HR: Heart Failure vs Normal Vs Cancer Treatment vs COPD
  • “baseline” vs “estimates”
  • the difference is “Residuals”
  • Actual, RR, HR, Higher than Expected: Deterioration vs Improvement
  • Chris Economos, VP of Business Development, PhysIQ Case Study: Phase 3 Cardiovascular Clinical Trial: 600 patients, 97 sites, 14 countries, 9 languages 2 CROs
  • All Causes Hospitalization vs Worsening HF Hospitalization
  • Application of AI to data detection of exacerbation

3:15 – 3:35 pm NETWORKING COFFEE AND REFRESHMENT BREAK

3:35 – 4:05 pm Learning Disease Progression and Patient Stratification Models from Images and Text

 

Regina Barzilay, Delta Electronics Professor, MIT EECS, MIT Koch Institute for
Integrative Cancer Research

  • Predict recurrences, sensitivity to Treatment, LCIS – Lobar Carcinoma In-Situ
  • Enabling New Science – NLP Atypia – 7000 cases
  • Reducing Over-treatment – 87% excision are of benign tissue
  • 31% cancers were visible a year prior to cancer
  • Interpretable Neural Models
  • Multi-Task Representation Learning: Small sample size: Task “N” Tumor Size change GOALS: Correlate similar tasks

 

4:05 – 4:25 pm How AI will transform Clinical Trials

Ronald Dorenbos, Associate Director, Materials & Innovation, Takeda

  • Patient’s Perspective: AI can help patients to get better faster, present the disease
  • Future of clinical Trials: Personalization, Patients becoming the point-of-care, Adherence, Healthier Life Style
  • patient acceptance and adoption of digital health and AI are growing
  • In Pharma: SImulation Modeling, Predicting reaction to therapies Virtual Clinical Trials

 

4:25 – 5:00 pm PANEL DISCUSSION: How to make all the Data Machine Learnable?

Raj Bandaru, Sr. Director, Data Sciences Strategy, Sanofi

  • advises to use models that will signal noise vs clean the data upfront with endless effort

Jonas Dorn, Digital Solutions Director, Novartis

  • Cleaning data MUST be done before modeling
  • At present AI will not change the WOrld as fast, future of AI will move slowly

Ingo Mierswa, Founder and President, RapidMiner

  • missing data is not an excuse, it worth a chance
  • Data Engineering and Data modeling is separate in hands of two groups, optimal modeling requires one group, cooperation and validation both groups need be involved along the entire cycle
  • Support the RIGHT to own the data

Jyoti Shah, Associate Director, Data Development, Merck

  • A lot of data and high quality of Data
  • Digital technology – data collected by machine becomes part of the process
  • Patients Centers will disctate the pace of AI adoption, they want to own data

Moderated by: Munther Baara, Head, New Clinical Paradigm, Pfizer

5:00 – 6:30 pm Networking Drinks Reception / END OF CONFERENCE

SOURCE

http://panagorapharma.com/ai/schedule/