Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Curator: Aviva Lev-Ari, PhD, RN

This is our own representation of Experts on our Team expressing Scientific Opinions and Comments on their Peers’ Scientific work

presented from our Research Category on 

Interviews with Scientific Leaders

here are our members of the Team on Cancer Biology

Scientific Leaders @ http://pharmaceuticalintelligence.com

 

Dr. Ritu Saxena –  On Personalized Medicine gearing up to tackle cancer

According to the American Cancer Society, the probability that an individual will develop or die from cancer over the course of a lifetime (lifetime risk) in the United States is less than a 1 in 2 for men; and a little more than 1 in 3 for women. Thanks to passionate and committed researchers like Dr. Tsimberidou, personalized medicine-based cancer treatments might take us a few steps closer to curing the disease.  Dr. Tsimberidou concludes, “We have to develop innovative treatment protocols and to offer the best treatment possible for each of our patients”.

In:

Personalized medicine gearing up to tackle cancer

https://pharmaceuticalintelligence.com/2013/01/07/personalized-medicine-gearing-up-to-tackle-cancer/

 

Dr. Tilda Barlyia – On James Watson’s Examination of The “Cancer establishments”

In reply to cancer biologist Robert Weinberg of MIT

I would like to add something regarding this comment and I quote “the main reason drugs that target genetic glitches are not cures is that cancer cells have a work-around. If one biochemical pathway to growth and proliferation is blocked by a drug such as AstraZeneca‘s Iressa or Genentech’s Tarceva for non-small-cell lung cancer, said cancer biologist Robert Weinberg of MIT, the cancer cells activate a different, equally effective pathway”

“I think this is why some researching are aiming to find a drug that targets a common denominator of multiple pathways rather that “just” a specific pathway as many cancer cells activate a different equal pathway.”

In:

The “Cancer establishments” examined by James Watson, co-discoverer of DNA w/Crick, 4/1953

January 9, 2013

https://pharmaceuticalintelligence.com/2013/01/09/the-cancer-establishments-examined-by-james-watson-co-discover-of-dna-wcrick-41953/

 

Dr. Stephen Williams – On James Watson’s Examination of The “Cancer establishments”

I remember back in the 90s when big pharmas were talking about developing farnesyltransferase inhibitors (the enzyme that puts the modification on ras) as well as myc inhibitors as a sliver bullet for cancer therapy but I have not heard much else.

And as far as personlized medicine, yes personalized medicine does have a role to play and can be very effective but remember we are only talking about  maybe 10% of cases for a tumor type.

Kudos to both Watson and Weinstein for stating we really need to delve into tumor biology to determine functional pathways (like metabolism) which are a common feature of the malignant state

In:

The “Cancer establishments” examined by James Watson, co-discoverer of DNA w/Crick, 4/1953

January 9, 2013

https://pharmaceuticalintelligence.com/2013/01/09/the-cancer-establishments-examined-by-james-watson-co-discover-of-dna-wcrick-41953/

 

 

Pierluigi Scalia MD, PhD  — On Molecular Pathology and Personalized Medicine

Commissioned Comment by Dr. Aviva Lev-Ari

The nanotechnology field certainly provides plenty of opportunity in the field of personalized cancer treatments (Rx). One comment I wanted to make due to the high relevance and implication is in the definition of Personalized Medicine” at large. I believe you are correct to define it as a “movement” within modern medicine as it has been so far. However, I believe we have all the multidisciplinary knowledge we need to move that concept to a real science and a specific operating system in the way we do think and apply medical knowledge.

Even though your definition is definitely correct, I would provide an operating version which I believe can help many to understand WHAT are the minimum requirements to classify a Cancer treatment as part of a “personalized” cancer treatment.
My take on that (which i have expressed elsewhere) is that:

“Personalized Cancer Medicine is that field of medicine using a next-generation diagnostic procedure (or a minimum cancer gene-drivers screening panel) in order to define a key number of cancer abnormalities in each patient clinical specimen for which a targeted therapy or smart integrated approach provides a definite survival advantage versus current conventional medicine”.

This operational definition anticipates the concept of applied pharmacogenomics that is currently more of a research area rather than a clinically mature field.

On the other hand, it leads us to that limiting factor towards the adoption of personalized treatments which is the evolution in molecular pathology with full adoption of genomics as the routine way to screen for a patient Oncotype as part of the routine diagnostic process.

The fact of using nanotechnology in order to target and treat abnormal cancer cells and tissues adds a powerful weapon towards eradicating the disease in the foreseeable future. However, focusing on weapons when we still have not found a reliable way to build that personalized “shooting target” (Cancer Fingerprinting) still constitutes, in my opinion, the single most relevant barrier to the adoption of Personalized treatments.

In:

Nanotechnology, personalized medicine and DNA sequencing

January 9, 2013

https://pharmaceuticalintelligence.com/2013/01/09/nanotechnology-personalized-medicine-and-dna-sequencing/

 

 

Larry Bernstein, MD – On  Modern Techniques of Molecular Pathology

A look at clinical laboratory science and its expected progress over the next decade

 

In Response to Dr. Scalia’s Comment on Molecular Pathology

In:

Nanotechnology, personalized medicine and DNA sequencing

Commissioned Post by Dr. Aviva Lev-Ari

January 9, 2013

https://pharmaceuticalintelligence.com/2013/01/09/nanotechnology-personalized-medicine-and-dna-sequencing/

Promising forecasts have been made projecting great expectations for medical sciences in the year 2013 and beyond. These predictions follow a decade after completion of the Human Genome Project, and are accompanied by immense breakthroughs in computational and applied mathematics.  In my view, they are:

• Genomic and allied “OMICs-technology”
• Innovation in mathematical classification (complexity)
• Nanotechnology
• Synthetic chemistry from physics, organic and inorganic chemistry

It is not my intention to go deeply into the exponential group of these advanced and integrative sciences; rather, I want raise awareness of an emerging new world that will open to the clinical laboratory scientist, and signal the need in the next generation of laboratory personnel to embrace knowledge domains that will be critical for their careers.

All of these breakthroughs are tied together by a search for personalized and integrative medicine.  These breakthroughs will reinvent nutritional and pharmaceutical medicine as well as medical devices and restructure clinical laboratory and imaging applications to cardiology, oncology, radiology and anatomical pathology.

Metabolomics

What does metabolomics and metabolic profiling have to do with this? Metabolomics is the measurement of small molecules that interact with membrane receptors¹ that are involved with regulation of genomic transcription and cellular regulation and upregulation or downregulation of metabolic processes essential to health. As well, these small molecules may provide targets for disease treatments, and as they are investigated, also provide further “analytes for diagnosis and, moreover, prediction of short-term or long-term outcomes.”²

As a result, the laboratory will become a more significant factor in measuring health and disease and in guiding health or disease maintenance.  As our population has reached increased age limits, the laboratory has been a contributor in the public health sphere, and will have a greater role as a result of

• Improved tie in with provision of information to not only the healthcare workers, but also the patient.
• Achieve turnaround times for critical results through better workflow
• Greater control and access to a next generation of point-of-care technology integrated with the laboratory database, and a restructured electronic health record.
• Despite the hype about the BIG DATA revolution, this is achievable in the system here proposed because there is a published model to achieve this(2)

Familiar Methods

Either individually or grouped as a profile, metabolites are detected by either nuclear magnetic resonance spectroscopy or mass spectrometry, providing a basis for uses of metabolome findings extended to the early detection and diagnosis of cancer and as both a predictive and pharmacodynamics marker of drug effect. We can expect it to become the link between the laboratory and the clinic. The methods used in genomics are microarrays, and for proteomics they are the already familiar chromatographic principles that species migrate at different rates through a column matrix based on their volatility, or carries out a separation as the molecules differ by their adsorption to and elution from a solid matrix, dependent on the binding to the matrix and solubility in the solvent eluate, modified by ph, ionic concentration, and specific conditions needed for recovery.  Powerful mathematical tools are used to analyze the data.³

Cardiovascular Disease

Although coronary thrombosis is the final event in acute coronary syndromes, there is increasing evidence that inflammation also plays a key role in development of atherosclerosis and its clinical manifestations, such as myocardial infarction, stroke and peripheral vascular disease. The inflammatory component was indicated by epidemiological studies of elevated serum levels of high sensitivity C-reactive protein. That eventually led to the demonstration of a benefit from reduction of CRP in individuals without characteristic lipidemia in a major clinical trial, which drew a relationship between diabetes, obesity and disordered inflammatory response in the causation of coronary artery disease, aortic valve and artery disease, carotid artery and peripheral vascular disease.

Cancer

Because cancer cells are known to possess a highly unique metabolic phenotype, development of specific biomarkers in oncology is possible and might be used in identifying fingerprints, profiles or signatures to detect the presence of cancer, determine prognosis and/or assess the pharmacodynamic effects of therapy.⁴

HDM2, a negative regulator of the tumor suppressor p53, is over-expressed in many cancers that retain wild-type p53. Consequently, the effectiveness of chemotherapies that induce p53 might be limited, and inhibitors of the HDM2–p53 interaction are being sought as tumor-selective drugs.⁵

Coagulation

Blood coagulation plays a key role among numerous mediating systems activated in inflammation. Receptors of the PAR family serve as sensors of serine proteinases of the blood clotting system in the target cells involved in inflammation. Activation of PAR_1 by thrombin and of PAR_2 by factor Xa leads to a rapid expression and exposure on the membrane of endothelial cells of both adhesive proteins that mediate an acute inflammatory reaction and of the tissue factor that initiates the blood coagulation cascade.

The details of evolving methods are avoided in order to build the argument that a very rapid expansion of discovery has been evolving depicting disease, disease mechanisms, disease associations, metabolic biomarkers, study of effects of diet and diet modification, and opportunities for targeted drug development.

Dr. Bernstein is CEO of Triplex Medical Science, and CSO of Leaders in Pharmaceutical Intelligence http://pharmaceuticalintelligence.com. He has been involved in writing,  reviewing, and a collaborative project on reducing  the noise that exists in complex data, and developing a primary evidence-based classification since retiring from a career in pathology spanning 4 decades.

References

1. Bernstein LH. Metabolomics, metabonomics and functional nutrition: The next step in nutritional metabolism and biotherapeutics. Journal of Pharmacy and Nutrition Sciences, 2012, 2, (xxx).

2. David G, Bernstein LH, and Coifman RR. Generating evidence-based interpretation of hematology screens via anomaly characterization. The Open Clinical Chemistry Journal 2011;4: 10-16.

3. Grainger DJ. Megavariate statistics meets high data-density analytical methods: The future of medical diagnostics? IRTL Reviews 2003;1:1-6.

4. Spratlin JL, Serkova NJ, and Eckhardt SG. Clinical applications of metabolomics in oncology: A review. Clin Cancer Res 2009;15; 15(2): 431–440.

5. Fischer PM, Lane DP. Small molecule inhibitors of thep53 suppressor HDM2: Have protein-protein interactions come of age as drug targets? Trends in Pharm Sci 2004;25(7):343-346.

Other Articles on this Open Access Online Scientific Journal:

Bernstein LH. Assessing Cardiovascular Disease with Biomarkers. http://pharmaceuticalintelligence.com

Bernstein LH. Predicting Tumor Response, Progression, and Time to Recurrence. http://pharmaceticalintelligence.com

Bernstein LH. Special Considerations in Blood Lipoproteins, Viscosity, Assessment and Treatment. http://pharmaceuticalintelligence.com

Comment in Response to Dr. Scalia’s Comment In:

Nanotechnology, personalized medicine and DNA sequencing

January 9, 2013

https://pharmaceuticalintelligence.com/2013/01/09/nanotechnology-personalized-medicine-and-dna-sequencing/

 

 

Dr. Tilda Barlyia – On Quality control (QC) of DNA sequencing

In response to Larry Bernstein, MD comment on 

Nanotechnology, personalized medicine and DNA sequencing

Quality control (QC) of DNA sequencing is of major challenge especially when sequencing long DNA strands. This is also probably one of the reasons why these nanopore DNA sequencers devices haven’t made it to the market yet. Some of the challenges that these sequencing technique have encountered are: (a) high velocity in which the DNA segment passes through the pores and which needs to be slowed down, (b) the need for high spatial resolutions and orientation of the nucleotide in the gap, (c) complex algorithms as well as error-prone DNA conversion steps (from dsDNA to ssDNA). I believe that there’s a long way before we see these devices on the shelf but it’s definitely inspiring to see how scientists vision these techniques and creatively finds ways to solve the problem.

In:

Nanotechnology, personalized medicine and DNA sequencing

January 9, 2013

https://pharmaceuticalintelligence.com/2013/01/09/nanotechnology-personalized-medicine-and-dna-sequencing/