June | 2019 | Leaders in Pharmaceutical Business Intelligence Group, LLC, Doing Business As LPBI Group, Newton, MA

Archive for June, 2019

In-House Development of an intellectual property value calculator (IP-V-Cal) for Valuation of INTANGIBLE products: Intellectual property (IP) assets of Digital Printed Products (DPP) – Online Journal(s), e-Books and a Corpus of Real Time generated eProceedings of the Top Biotech Global Conferences

Posted in Feedback from Investors: LPBI Portfolio of Five Businesses, IP Valuation Models - Pricing Intangible Assets, LPBI Group, e-Scientific Media, DFP, R&D-M3DP, R&D-Drug Discovery, US Patents: SOPs and Team Management on June 30, 2019| Leave a Comment »

In-House Development of an intellectual property value calculator (IP-V-Cal) for Valuation of INTANGIBLE products: Intellectual property (IP) assets of Digital Printed Products (DPP) – Online Journal(s), e-Books and a Corpus of Real Time generated eProceedings of the Top Biotech Global Conferences

Author: Aviva Lev-Ari, PhD, RN

1. All the points I made, below in my e-mail 4AM on 6/28/2019, see below – to match Intangible Assets in Document #2, 4/19/2019 in Inbox of each FIT member.

(after reading Rick’s article we received a link to and after reading the link that I provided in this e-mail)

2. We Need Amnon to enter into an Excel spread sheet as Column #1 all the Contributing Factors to valuation in that 4AM e-mail

3. Columns #2,#3,#4 will be Gail, Amnon, Rick (Business Team)

4. Columns #5,#6 will be Dr. Williams, Prof. Feldman (our Board)

5. Columns #7,#8 #9,#10 will be Dr. Pearlman, Dr. Dror Nir, Dr. Saha, Dr. Irina (Scientists Team)

7. Each Column dedicated to each of out 10 alive and well Active FIT

Will be split into two columns

6. Column #11 will be Aviva’s

8. First column of each of the 10 FIT members will be filled by each by a number between 50 to 100, representing the subjectively perceived contributing weight of the Factor mentioned in Column 1: list of factors contributing to Venture’s valuation

9. Second column of each of the 10 FIT members will list the member’s subjective perspective on Ranking the Factors in Column #1

10. To Column #1: each Business Team member (mentioned in 3, above), needs to contribute FIVE new factors taken from your discussion on Valuation add them with your initials to Column #1

11. Aviva will bring DATA from Article Scoring System already populating a database designed to quantify the

11.1 Valuation of the Journal

11.2 Valuation of the BioMed e-Series: each book, each series, all 16 volumes

11.3 Author’s factor in pricing 11.1 and 11.2

12. Valuation of 70 eProceedings

(60 by Aviva; 10 by Dr. Williams)

needs to be tied to a growth factor in LPBI Group’s INFLUENCE on Twitter

12.1 @pharma_BI

12.2 @AVIVA1950

12.3 Gail’s Twitter account

12.4 Dr. Williams’ Twitter account

12.5 Dr. Asha’s Twitter account

12.6 Dr. Irina’s Twitter account

Factors of INFLUENCE:

– Growth in #Followers on Twitter

– Ratio #Tweets/#Likes

– Cumulative # of Followers’ Followers

13. LinkedIn

I discovered new features and I wish to conduct a Skype training session with narrow messaging to FIT members

Please contribute your thoughts, while

– Amnon is building this Excel

– Irina will be designing DropBox for this Excel that TEN FIT members need to add a number 50 to 100, Ranking the relative importance of each factor for Venture Valuation

GREAT initiative by Business Team to focus on valuation, thank you.

Thank you all FIT members, get ready yo add your subjective numbers into the Valuation Excel.

Amnon, please share with me in a Skype session the draft of this Excel, before we deplore this instrument, place it in Dropbox and announce the window of one week when we collect 2×10 data points on each of the Factors in Column #1,

Board members and Scientists: you are welcome to contribute Factors in Valuation of the Venture in Column #1, the longer this column, the greater the granularity.

We can then focus only on factors that scored above the Mean or any cut off point we will agree upon.

Thank you all – it is exciting to get the entire Team, developing a custom tailor methodology for DIGITAL printed products, NO OFF THE SHELF MODEL WILL FIT US.

Current valuation models that do NOT APPLY to our venture include the following:

“Book to market value”

– we got Intangibles, Column #1

– LPBI Group’s Tangibles are royalties for books sold.

(all data was reviewed by Dr. Williams, for Section #13 in Document #2, for the period, 4/2012 to 4/19/2019)

“VC investment dilution models”

– we kept 100% of ownership

– our shareholders are 12 FIT members:

— >>>>>> 10 are active members

– (Scientist Team: Formula in place) (Gail included)

– (Business Team: 10% of UPSIDE) (Gail included)

— >>>>>> Past commitments outstanding:

– to Dr. Larry and

– to Adam Sonnenberg

– (Formula in place).

– No UPSIDE, due to idle status since 2/6/2019, Exit period launch.

Thank you again.

Aviva Lev-Ari, PhD, RN

Editor-in-Chief, BioMed e-Series

http://PharmaceuticalIntelligence.com

Director & Founder

Leaders in Pharmaceutical Business Intelligence (LPBI) Group

On Jun 28, 2019, at 3:57 AM, Amnon Danzig <amnon.danzig@gmail.com> wrote:

This is a nice article that put in place Corporate Finance practices.

However, The Business Team currently is struggling in much more earlier stages of the valuation of the Group.

We have a long way to go before we are entering the valuation scene in numeric terms.

Aviva,

I must confess that in the last two weeks we (Rick, Gail and me) invested huge amount of work to disclose the real valuation of the Group.

It is a work-in-process.

Thank you for your patience.

Amnon

Amnon Danzig

Business Strategy

https://lnkd.in/e-zTVz4

Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Israel

http://pharmaceuticalintelligence.com

e-Mail: amnon.danzig@gmail.com

(M) +972-54-6998405

www.amnondanzig.com

SkypeID: Amnon.Danzig LinkedIn Profile Twitter Profile

On Fri, Jun 28, 2019 at 10:30 AM Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu> wrote:

What is Aviva’s take on LPBI Group Valuation?

Not every business needs VC money to get off the ground, and you can potentially preserve a lot of value for yourself and the TEAM

https://bothsidesofthetable.com/do-you-really-even-need-vc-72013e985fab

Advantages of LPBI Group:

We had low barrier to entry and
We had/have Zero labor cost
We are virtual, therefore, no overhead expenses
Run rate at WordPress.com Business Premium Annual Fee $200 and LinkedIn Annual Business Premium $1000
Our 1st CARDINAL factor of production [The Team] is the DEAPTH and very diverse EXPERTISE residing in the Scientist Team and in the Business TEAM
Leadership expressed by new timely challenge selection – Directions into new domains
Team ability to swarm around new domains (new timely challenge selection), Examples:

2015-2016 – 3D BioPrinting – Book: Series E, Volume 4

Volume 4: Medical 3D BioPrinting – The Revolution in Medicine, Technologies for Patient-centered Medicine: From R&D in Biologics to New Medical Devices. On Amazon.com since since 12/30/2017

https://www.amazon.com/dp/B078QVDV2W

2016-2017 – Drug Discovery – JV with SBH Sciences, Dr. Raphael Nir

https://pharmaceuticalintelligence.com/drugdiscovery-lpbi-group/

2019-2020 – AI + ML in Medicine – Book: Series B, Volume 2

https://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/volume-two-genomics-methodologies-ngs-bioinformatics-simulations-and-the-genome-ontology/

Our 2nd CARDINAL factor of Leadership is the FIDELITY of a CORE team of Scientists
Aviva’s ability to multitask on several levels – FIVE persons in just One woman (nee: 1950):

LPBI Group’s DAILY activity on Twitter, LinkedIn, Facebook
IN PERSON at +60 Conferences – yielded a Corpus of eProceedings N=70 [10 by Dr. Williams
Curator of new content – Journal is LIVE at

1,639,029 eReaders

Content

5,642

Posts

686

Narrative Building for the Future of LPBI Group: List of Talking Points

Posted in BioMed e-Books e-Series by LPBI Group, Genome Biology, LPBI Group, e-Scientific Media, DFP, R&D-M3DP, R&D-Drug Discovery, US Patents: SOPs and Team Management, Next Generation Sequencing (NGS) on June 30, 2019| Leave a Comment »

Narrative Building for the Future of LPBI Group: List of Talking Points

Exchange between Gail and Aviva

On Tuesday, June 25, 2019, 11:43:27 AM EDT, Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu> wrote:

https://www.terarecon.com/blog/beyond-the-screen-episode-6-next-generation-ai-companies-providing-physicians-a-starting-point-in-ai?utm_campaign=AuntMinnie%20June%202019

HOW can we get Kevin Landwher of terarecon.com to create a Podcast for LPBI Group IP Assets, including a section on our forthcoming Genomics, Volume 2

https://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/volume-two-genomics-methodologies-ngs-bioinformatics-simulations-and-the-genome-ontology/

In response to this question we are in discussion on POINTS #1,2,3,4

From: Gail Thornton <gailsthornton@yahoo.com>

Reply-To: Gail Thornton <gailsthornton@yahoo.com>

Date: Sunday, June 30, 2019 at 8:38 AM

To: Aviva Lev-Ari <aviva.lev-ari@comcast.net>

Cc: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>, Rick Mandahl <rmandahl@gmail.com>, Amnon Danzig <amnon.danzig@gmail.com>

Subject: Please AUDIT PODCAST —>>>>>>>> Beyond the Screen Episode 6: Next Generation AI Companies Providing Physicians a Starting Point in AI

Aviva:

These videos from terarecon.com typically focus on one topic (not many as you’ve described below).

If there are too many topics proposed to this company, they will not be interested.

My recommendation is for you to finalize Genomics, volume 2, and let’s see the story we have about that specific topic.

Gali

On Tuesday, June 25, 2019, 11:43:27 AM EDT, Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu> wrote:

https://www.terarecon.com/blog/beyond-the-screen-episode-6-next-generation-ai-companies-providing-physicians-a-starting-point-in-ai?utm_campaign=AuntMinnie%20June%202019

HOW can we get Kevin Landwher of terarecon.com to create a Podcast for LPBI Group IP Assets, including a section on our forthcoming Genomics, Volume 2

https://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/volume-two-genomics-methodologies-ngs-bioinformatics-simulations-and-the-genome-ontology/

On Saturday, June 29, 2019, 03:56:08 PM EDT, Aviva Lev-Ari <aviva.lev-ari@comcast.net> wrote:

POINT #1 for VIDEO coverage – Focus on Genomics, Volume 2

After 7/15, Prof. Feldman will be back in the US, stating to work on Part 5 in Genomics, Volume 2. We will Skype to discuss what to include in 5.1, 5.2, 5.3, 5.4

On 7/15, I am submitting my work on creation of Parts 1,2,3,4,6

Dr. Williams and Dr. Saha are working already on Part 7&8.

Below you have abbreviated eTOCs.

Go to URL of the Book to see what I placed already inside this book.

Dr. Williams and Prof. Feldman will compose

Preface

Introduction to Volume 2

Volume Summary

Epilogue

Based on these four parts and the eTOCs you will have ample content for the video, which may start with the epitome of our book creation: Genomics Volume 2 (you interview the three Editors why it is Epitome)

POINT #2 or #3 or #4 for VIDEOs to Focus on coverage for Marketing LPBI Group

by DESCRIPTION of what was accomplished

Venture history/background
Venture milestones: all posts in the Journal with the Title
“We celebrate …..
5-6 Titles like that, I may add two more
Site Statistics
Book articles cumulative views (Article Scoring System: Data Extract)
section on BioMed e-Series
section on List of Conference covered in Real Time
FIT Team input to Venture Valuation: top 5 or top 10 Factors in consensus
the 3D graphs on Opportunity Maps: Gail, Rick, Amnon, Aviva – each explains their own outcome
section on Pipeline

Video on What is the Ideal Solution for the FUTURE of LPBI Group

Interviews with All FIT Members

For POINT #1:

To build the narrative for a VIDEO dedication to Genomics, Volume Two and Marketing campaign as a NEW BOOK on NGS, the Narrative will use content extracts to built a CASE for

Why GENOMICS Volume 2 – is the Epitome of all BioMed e-Series???????

forthcoming Genomics, Volume 2

https://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/volume-two-genomics-methodologies-ngs-bioinformatics-simulations-and-the-genome-ontology/

Aviva completed Parts 1,2,3,4,6,

[5 is by Prof. Feldman]

[7,8 are by Scientists on FIT]:

Latest in Genomics Methodologies for Therapeutics:

Gene Editing, NGS & BioInformatics,

Simulations and the Genome Ontology

2019

Volume Two

Prof. Marcus W. Feldman, PhD, Editor

Prof. Stephen J. Williams, PhD, Editor

And

Aviva Lev-Ari, PhD, RN, Editor

https://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/volume-two-genomics-methodologies-ngs-bioinformatics-simulations-and-the-genome-ontology/

Abbreviated eTOCs

Part 1: NGS

1.1 The Science

1.2 Technologies and Methodologies

1.3 Clinical Aspects

1.4 Business and Legal

Part 2: CRISPR for Gene Editing and DNA Repair

2.1 The Science

2.2 Technologies and Methodologies

2.3 Clinical Aspects

2.4 Business and Legal

Part 3: AI in Medicine

3.1 The Science

3.2 Technologies and Methodologies

3.3 Clinical Aspects

3.4 Business and Legal

3.5 Latest in Machine Learning (ML) Algorithms harnessed for Medical Diagnosis: Pattern Recognition & Prediction of Disease Onset

Part 4: Single Cell Genomics

4.1 The Science

4.2 Technologies and Methodologies

4.3 Clinical Aspects

4.4 Business and Legal

Part 5: Evolution Biology Genomics Modeling @Feldman Lab, Stanford University – Written and Curated by Prof. Marc Feldman

5.1

5.2

5.3

5.4

Part 6: Simulation Modeling in Genomics

6.1 Mutation Analysis – Gene Encoding

6.2 Mitochondrial Variations

6.3 Variant Analysis

6.4 Variant Detection in Hereditary Cancer Genes

6.5 Immuno-Informatics

6.6 RNA Sequencing

6.7 Complex Insertions and Deletions

6.8 Evolutionary Biology

6.9 Simulation Programs

6.10 A comparison of tools for the simulation of genomic next-generation sequencing data

Part 7: Applications of Genomics: Genotypes, Phenotypes and Complex Diseases

7.1 Genome-wide associations with complex diseases (GWAS)

7.2 Non-coding DNA and phenotypes—including diseases like cancer

7.3 Epigenomic associations with phenotypes including cancer

7.4 Rare variants and diseases

7.5 Population-level genomics and the meaning of group differences

7.6 Targeting drugs for complex diseases

Part 8: Epigenomics and Genomic Regulation

8.1 Genomic controls on epigenomics

8.2 The ENCODE project and gene regulation

8.3 Small interfering RNAs and gene expression

8.4 Epigenomics in cancer

8.5 Environmental epigenomics

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AI System Used to Detect Lung Cancer

Posted in Artificial Intelligence - Breakthroughs in Theories and Technologies, Artificial Intelligence - General, tagged Artificial intelligence, CT scans, Lung cancer, Radiology, Technology on June 28, 2019| Leave a Comment »

AI System Used to Detect Lung Cancer

Reporter: Irina Robu, PhD

3.3.13

3.3.13 AI System Used to Detect Lung Cancer, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

Lung cancer is characterized by uncontrolled cell growth in tissues of the lung. The growth spreads beyond the lung by metastasis into nearby tissues. The most common symptoms are coughing (including coughing up blood), weight loss, shortness of breath, and chest pains. The two main types of lung cancer are small-cell lung carcinoma(SCLC) and non-small-cell lung carcinoma (NSCLC). Lung cancer may be seen on chest radiographs and computed tomography(CT) scans. However, computers seem to be as good or better than regular doctors at detecting tiny lung cancers on CT scans according to scientists from Google.

The AI designed by Google was able to interpret images using the same skills as humans to read microscope slides, X-rays, M.R.I.s and other medical scans by feeding huge amounts of data from medical imaging into the systems. It seems that the researchers were able to train computers to recognize patterns linked to a specific condition.

In a new Google study, the scientists applied artificial intelligence to CT scans used to screen people for lung cancer. Current studies have shown that screening can reduce the risk of dying from lung cancer and can also identify spots that might later become malignant.

The researchers created a neural network with multiple layers of processing and trained the AI by giving it many CT scans from patients whose diagnoses were known. This allows radiologists to sort patients into risk groups and decide whether biopsies are needed or follow up to keep track of the suspected regions. Even though the technology seems promising, but it can have pitfalls such as missing tumors, mistaken benign spots for malignancies and push patients into risky procedures.

Yet, the ability to process vast amounts of data may make it imaginable for artificial intelligence to recognize subtle patterns that humans simply cannot see. It is well understood that the systems should be studied extensively before using them for general public use. The lung-screening neural network is not ready for the clinic yet.

SOURCE

https://www.unilad.co.uk/technology/a-i-took-test-to-detect-lung-cancer-and-smashed-it

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Analysis of Utilizing LPBI Group’s Scientific Curation Platform as an Educational Tool: New Paradigm for Student Engagement

Posted in Curation, Curation methodology, Experimental validation, Scientific Publishing, tagged Content Curation, Curation, Educational Resources, educational software, medical education, scientific curation, student engagement, university teaching on June 27, 2019| Leave a Comment »

Analysis of Utilizing LPBI Group’s Scientific Curation Platform as an Educational Tool: New Paradigm for Student Engagement

Author: Stephen J. Williams, Ph.D.

Use of LBPI Platform for Educational Purposes

Goal: to offer supplemental information for student lessons in an upper level Biology course on Cell Signaling and Cell Motility with emphasis on disease etiology including cancer, neurological disease, and cardiovascular disease.

Course: Temple University Department of Biology course Cell Signaling and Motility Spring semester 2019. Forty five students enrolled.

Methodology: Each weekly lesson was presented to students as a PowerPoint presentation. After each lesson the powerpoint presentation was originally meant to be disseminated to each class-registered student on the students Canvas account. Canvas is a cloud based Learning Management Software developed by educational technology company Salt Lake City, Utah company Infrastructure, Inc. According to rough figures, Canvas® charges a setup fee and at least $30 per user (for a university the size of Temple University: 55,000 students at $30 each = 1.6 million a semester for user fees only).

As a result of a technical issue with uploading the first week lesson on this system, I had informed the class that, as an alternative means, class presentation notes and lectures will be posted on the site www.pharmaceuticalintelligence.com as a separate post and searchable on all search engines including Google, Twitter, Yahoo, Bing, Facebook etc. In addition, I had informed the students that supplemental information, from curated posts and articles from our site, would be added to the class lecture post as supplemental information they could use for further reading on the material as well as helpful information and reference for class projects.

The posted material was tagged with #TUBiol3373 (university abbreviation, department, course number) and disseminated to various social media platforms using our system. This allowed the students to enter #TUBiol3373 in any search engine to easily find their lecture notes and supplemental information.

This gave students access to lectures on a mobile platform which was easily discoverable due to our ability to do search engine optimization. (#TUBiol3373 was among the first search results on most popular search engines).

From a technical standpoint, the ease at which posts of this nature can be made as well as the ease of including links to full articles as references as well as media has been noted. Although students seem to navigate the Canvas software with ease, they had noticed many professors have issues or problems with using this software, especially with navigating the software for their needs. LBPI’s platform is an easily updated, accessible, and extensive knowledge system which can alleviate many of these technical issues and provide the added value of incorporating media based instructional material as well as downloadable file and allow the instructor ability to expound on the presented material with commentary. In addition due to the social nature of the platform, feedback can be attained by use of curated site statistics and commentary sections as well as online surveys.

Results

After the first week, all 45 students used LBPI platform to access these lecture notes with 17 out of 45 continuing to refer to the site during every week (week 1-4) to the class notes. This was evident from our site statistics as well as number of downloads of the material. The students had used the #TUBIol3373 and were directed to the site mainly from search engines Google and Yahoo. In addition, students had also clicked on the links corresponding to supplemental information which I had included, from articles on our site. In addition, because of the ability to incorporate media on our site, additional information including instructional videos and interviews were included in lecture posts, and this material was easily updated on the instructor’s side.

Adoption of the additional material from our site was outstanding, as many students had verbally said that the additional material was very useful in their studies. This was also evidenced by site statistics owing to the secondary clicks made from the class lecture post going to additional articles, some not even included as links on the original post.

In addition, and more important, students had incorporated many of the information from the additional site articles posted and referenced in their class group projects. At end of semester a survey was emailed to each student to assess the usefulness of such a teaching strategy. Results of the polling are shown below.

Results from polling of students of #TUBiol3373 “Cell Signaling & Motility” Class

Do you find using a web based platform such as a site like this an easier communication platform for posting lecture notes/added information than a platform like Canvas®? (5 votes)

Answer	Votes	Percent
Yes	2	40%
Somewhat but could use some improvement	2	40%
No	1	20%
Did not use web site	0	0%

Do you find using an open access, curated information platform like this site more useful than using multiple sources to find useful extra study/presentation materials? (6 votes)

Answer	Votes	Percent
Yes	5	83%
No	1	17%

Did you use the search engine on the site (located on the top right of the home page) to find extra information on topics for your presentations/study material? (5 votes)

Answer	Votes	Percent
Yes	4	67%
No	1	17%
Did not use web site	1	17%

Were you able to easily find the supplemental information for each lecture on search engines like Google/Yahoo/Bing/Twitter using the hashtag #TUBiol3373? (6 votes)

Answer	Votes	Percent
Yes I was able to find the site easily	4	67%
No	1	17%
Did not use a search engine to find site, went directly to site	1	17%
Encountered some difficulty	0	0%
Did not use the site for supplemental or class information	0	0%

How did you find the supplemental material included on this site above the Powerpoint presented material for each of the lectures? (7 votes)

Answer	Votes	Percent
Very Useful	4	57%
Did not use supplemental information	2	29%
Somewhat Useful	1	14%
Not Useful	0	0%

How many times did you use the information on this site (https://www.pharmaceuticalintelligence.com) for class/test/project preparation? (7 votes)

Answer	Votes	Percent
Frequently	3	43%
Sparingly	2	29%
Occasionally	1	14%
Never	1	14%

Views of #TUBiol3373 lessons/posts on www.pharmaceuticalintelligence.com

Lesson/Title	Total # views	# views 1^st day	# views 2^nd day	% views day 1 and 2	% views after 1^st 2 days
Lesson 1 AND 2 Cell Signaling & Motility: Lessons, Curations and Articles of reference as supplemental information: #TUBiol3373	60	27	15	93%	45%
Lesson 3 Cell Signaling And Motility: G Proteins, Signal Transduction: Curations and Articles of reference as supplemental information: #TUBiol3373	56	12	11	51%	93%
Lesson 4 Cell Signaling And Motility: G Proteins, Signal Transduction: Curations and Articles of reference as supplemental information: #TUBiol3373	37	17	6	48%	31%
Lesson 5 Cell Signaling And Motility: Cytoskeleton & Actin: Curations and Articles of reference as supplemental information: #TUBiol3373	13	6	2	17%	15%
Lesson 8 Cell Signaling and Motility: Lesson and Supplemental Information on Cell Junctions and ECM: #TUBiol3373	16	8	2	22%	13%
Lesson 9 Cell Signaling: Curations and Articles of reference as supplemental information for lecture section on WNTs: #TUBioll3373	20	10	3	28%	15%
Curation of selected topics and articles on Role of G-Protein Coupled Receptors in Chronic Disease as supplemental information for #TUBiol3373	19	11	2	28%	13%
Lesson 10 on Cancer, Oncogenes, and Aberrant Cell Signal Termination in Disease for #TUBiol3373	21	10	2	26%	20%
Totals	247	69	46	31%	62%

Note: for calculation of %views on days 1 and 2 of posting lesson and supplemental material on the journal; %views day1 and 2 = (#views day 1 + #views day 2)*100/45 {45 students in class}

For calculation of %views past day 1 and 2 = (total # views – day1 views – day2 views) * 100/45

For calculation in total column last two columns were divided by # of students (45) and # of posts (8)

Overall class engagement was positive with 31% of students interacting with the site during the course on the first two days after posting lessons while 61% of students interacted with the site during the rest of the duration of the course. The higher number of students interacting with the site after the first two days after lecture and posting may be due to a higher number of students using the posted material for study for the test and using material for presentation purposes.

Engagement with the site for the first two days post lecture ranged from 93% engagement to 22% engagement. As the class neared the first exam engagement with the site was high however engagement was lower near the end of the class period potentially due to the last exam was a group project and not a written exam. Students appeared to engage highly with the site to get material for study for the written exam however there still was significant engagement by students for purposes of preparation for oral group projects. Possibly engagement with the site post 2 days for the later lectures could be higher if a written exam was also given towards the end of the class as well. This type of analysis allows the professor to understand the level of class engagement week by week.

The results of post-class polling confirm some of the conclusions on engagement. After the final grades were given out all 45 students received an email with a link to the poll. Of the 45 students emailed, there were 20 views of the poll with 5-7 answers per question. Interestingly, most answers were positive on the site and the use of curated material for learning and a source of research project material. It was very easy finding the posts using the #classname and most students used Google to find the material, which was at the top of Google search results. Not many students used Twitter or other search engines. Some went directly to the site. A majority (71%) found the material useful or somewhat useful for their class presentations and researching topics.

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New Targeted Cancer Therapy may be ‘Possible Hope’ for Some Pancreatic Cancer Patients

Posted in Biological Engineering, Cancer - General, Cancer and Current Therapeutics, Diagnostics and Lab Tests, Pancreatic cancer, tagged BRCA1 mutation, BRCA2 mutation, genetic engineering, Pancreatic cancer, poly (ADP-ribose) polymerase, Targeted therapy on June 27, 2019| Leave a Comment »

New Targeted Cancer Therapy may be ‘Possible Hope’ for Some Pancreatic Cancer Patients

Reporter: Irina Robu, PhD

UPDATED on 7/18/2019

BREAKTHROUGH PANCREATIC CANCER TREATMENT PHASE III TRIAL OPENS IN ISRAEL

Hope is that successful trials will allow Rafael Pharmaceuticals will receive expedited FDA approval by late 2020.

BY MAAYAN JAFFE-HOFFMAN JULY 18, 2019 18:30

“What it does is feeds misinformation to these regulatory elements, making them feel that there is too much carbon flow through both of these complexes, causing them to be inhibited,” Pardee said. “It simultaneously inhibits both complexes so tumor cells that are primarily driven by glucose cannot utilize glucose in the TCA cycle. Tumor cells that are primarily driven by glutamine usage cannot use glutamine-derived carbons in the TCA cycle. And, importantly, tumors cannot switch from one source to the other in the presence of CPI-613,” he explained.

He said that hitting two complexes simultaneously has many advantages. One is that the carbon source the tumor is primarily dependent on does not matter; another is that evolved resistance for both complexes simultaneously is very unlikely to happen.

Pardee said CPI-613’s key differentiators are that it is highly selective on the uptake and target level in cancer cells, which leads to less toxicity to healthy cells. This allows for patients to receive extended treatment courses and for the drug to be used in combination with other drugs.

CPI-613 is being administered in this clinical trial with a chemotherapy combination of fluorouracil, leucovorin, irinotecan, and oxaliplatin, called FOLFIRINOX.

SOURCE

https://www.jpost.com/HEALTH-SCIENCE/Breakthrough-pancreatic-cancer-treatment-phase-III-trial-opens-in-Israel-596059

New Targeted Cancer Therapy may be ‘Possible Hope’ for Some Pancreatic Cancer Patients

Pancreatic cancer is the 12th maximum common cancer and the fourth leading cause of cancer death. The cancer is often difficult to diagnose as there is no cost-effective ways to screen for the illness. For over 52% of people who are diagnosed after the cancer has spread and with a 5-year survival rate.

Scientists at Sheba Medical Center in Israel developed a targeted cancer therapy drug together with AstraZeneca and Merck which can offer a possible new solution for patients with a specific kind of pancreatic cancer by delaying the progression of the disease. To evaluate the safety and test the efficacy of a new drug treatment regimen based on Lynparza tablets. The tablets are a pharmacological inhibitor of the enzyme poly (ADP-ribose) polymerase which inhibit the enzyme. They were developed for a number of indications, but most prominently for the treatment of cancer, as numerous forms of cancer are more dependent for their development on the enzyme than regular cells are. This makes poly (ADP-ribose) polymerase an attractive target for cancer therapy.

Their study included 154 patients who were randomly assigned to get the tablets at a dose of 300 mg twice a day with metastatic pancreatic cancer who carried the genetic mutation called BRCA 1 and BRCA 2. BRCA1 and BRCA2 are human genes that produce proteins accountable for repairing damaged DNA and play a substantial role in preserving the genetic stability of cells. Once either of these genes is mutated, DNA damage can’t be repaired properly and cells become unstable. As a result, cells are more likely to develop additional genetic alterations that can lead to cancer.

Patients with these mutations make up six to seven percent of the metastatic pancreatic cancer patients. The trial using the using the medicine Lynparza offers possible hope for those who suffer from metastatic pancreatic cancer and have a BRCA mutation and slows down the disease progression. According to the researchers this is the first Phase 3 biomarker that is positive in pancreatic cancer and the drug gives incredible hope for patients with the advanced stage of the cancer.

SOURCE
https://www.timesofisrael.com/israeli-researchers-find-potential-hope-for-some-pancreatic-cancer-patients/

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First Cost-Effectiveness Study of Multi-Gene Panel Sequencing in Advanced Non-Small Cell Lung Cancer Shows Moderate Cost-Effectiveness, Exposes Crucial Practice Gap

Posted in Cancer and Current Therapeutics, Cancer Informatics, Genetics & Innovations in Treatment, Genetics & Pharmaceutical, Genome Biology, Genomic Expression, Genomic Testing: Methodology for Diagnosis, Genomics Pharmacy, Mutagenesis, Personalized and Precision Medicine & Genomic Research on June 27, 2019| Leave a Comment »

First Cost-Effectiveness Study of Multi-Gene Panel Sequencing in Advanced Non-Small Cell Lung Cancer Shows Moderate Cost-Effectiveness, Exposes Crucial Practice Gap

WASHINGTON (June 27, 2019) — The results of the first economic modeling study to estimate the cost-effectiveness of “multi-gene panel sequencing” (MGPS) as compared to standard-of-care, single-gene tests for patients with advanced non-small cell lung cancer (aNSCLC) show that the MGPS tests are moderately cost-effective but could deliver more value if patients with test results identifying actionable genetic mutations consistently received genetically guided treatments. The results of the study, which was commissioned by the Personalized Medicine Coalition (PMC), underline the need to align clinical practices with an era of personalized medicine in which physicians can use diagnostic tests to identify specific biological markers that inform targeted prevention and treatment plans.

The study, which was published yesterday in JCO Clinical Cancer Informatics, analyzed the clinical and economic value of using MGPS testing to identify patients with tumors that over-express genetic mutations that could be targeted by available therapies designed to inhibit the function of those genes — a mainstay of modern care for aNSCLC patients. Using data provided by Flatiron Health, researchers examined clinical and cost information associated with the care of 5,688 patients with aNSCLC treated between 2011 – 2016, separating them into cohorts who received MGPS tests that assess at least 30 genetic mutations at once and those who received only “single-marker genetic testing” (SMGT) of less than 30 genes.

Compared to SMGT, the MGPS testing strategy, including downstream treatment and monitoring of disease, incurred costs equal to $148,478 for each year of life that it facilitated, a level suggesting that MGPS is moderately cost-effective compared to commonly cited thresholds in the U.S., which range from $50,000 to $200,000 per life year (LY) gained.

The authors of the study point out, however, that physicians only prescribed a targeted therapy to some of the patients whose MGPS test results revealed actionable mutations. MGPS tests can only improve downstream patient outcomes if actionable results are used to put the patient on a targeted treatment regimen that is more effective than the therapy they would otherwise have been prescribed. It is therefore impossible for the cost of an MGPS test to translate into additional LYs if actionable results do not result in the selection of a targeted treatment regimen.

Although MGPS testing revealed actionable mutations in 30.1 percent of the patients in the study cohort, only 21.4 percent of patients who underwent MGPS testing received a targeted treatment.

The study’s authors calculated that if all MGPS-tested patients with actionable mutations had received a targeted therapy, MGPS testing would deliver measurably better value ($110,000 per LY gained).

“This research underlines the importance of ensuring that clinical practices keep pace with scientific progress in personalized medicine so that we can maximize the benefits of diagnostic tests that can improve patient care and make the health system more efficient by ensuring that safe and effective targeted therapies are prescribed to those patients who will benefit,” said PMC President Edward Abrahams.

The study’s authors include Dr. Lotte Steuten, Vice President and Head of Consulting, The Office of Health Economics, London, U.K., and Affiliate Associate Faculty Member, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center; Dr. Bernardo Goulart, Associate Faculty Member, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center; Dr. Neal Meropol, Vice President, Research Oncology, Flatiron Health; Dr. Daryl Pritchard, Senior Vice President, Science Policy, Personalized Medicine Coalition; and Dr. Scott Ramsey, Director, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center.

###

About the Personalized Medicine Coalition:

The Personalized Medicine Coalition, representing innovators, scientists, patients, providers and payers, promotes the understanding and adoption of personalized medicine concepts, services and products to benefit patients and the health system. For more information, please visit www.personalizedmedicinecoalition.org.

SOURCE

From: Personalized Medicine Coalition <pmc@personalizedmedicinecoalition.org>

Reply-To: “Christopher Wells (PMC)” <cwells@personalizedmedicinecoalition.org>

Date: Thursday, June 27, 2019 at 9:32 AM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: First Cost-Effectiveness Study of MGPS in aNSCLC Shows Moderate Cost-Effectiveness, Exposes Crucial Practice Gap

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Biologists Wondered—How Old are Cells in an Organism?

Posted in Biological Engineering, Cell Biology, tagged age mosaicism, beta cells, cell age, Cell Biology, delta cells, liver cells, neurons on June 26, 2019| Leave a Comment »

Biologists Wondered—How Old are Cells in an Organism?

Reporter: Irina Robu, PhD

Scientists form Salk Institute discovered that the mouse brain, live and pancreas contain populations of cells and proteins with extremely long lifespans with some as old as neurons. The research was published in Cell Metabolism on June 6, 2019. The general idea is that most neurons in the brain do not divide during adulthood and experience a long lifespan and age-related decline. Yet, due to limitations the lifespan of cells outside of the brain was difficult to determine.

However, the researchers knew very well that neurons are not replaced during the lifespan, they used them as control to compare other non-dividing cells. The team used an electron isotope labeling with hybrid imaging method to visualize and quantify cell and protein age and turnover in the brain, pancreas and liver in the young and old rodent models.

To confirm that their method is correct, the scientist determined first the age of the neurons and then realized that the cells that line blood vessels, endothelial cells were as old as neurons. According to this research, it means that some non-neuronal cells do not replicate themselves throughout the lifespan. The pancreas, the organ responsible for maintaining blood sugar levels and secreting digestive enzymes showed cells of all ages. Still, some beta cells, replicate during the lifetime and are relatively young, while others do not divide and were long lived. Yet, delta cells found in stomach do not divide at all.
Unlike other type of cells, the liver cells have the capacity to regenerate during adulthood. The researchers expected to observe young liver cells, however the majority of liver cells were found to be as old as the animal, while the cells that line blood vessels and stellate like cells, another liver type cell were short lived.

But on the molecular level, a selection of long-lived cells contains protein complexes displaying age mosaicism. Due to the modern visualizing technologies, scientists were able to pinpoint the age of the cells and their supra-molecular complexes precisely. The ultimate goal to determining the age of the cells and sub-cellular structures is to provide insights into cell maintenance and repair mechanism and utilize these mechanisms to prevent or delay old age-linked decline of organs with limited cell regeneration.

SOURCE

https://www.salk.edu/news-release/how-old-are-your-organs-to-scientists-surprise-organs-are-a-mix-of-young-and-old-cells/

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Sepsis Detection using an Algorithm More Efficient than Standard Methods

Posted in Artificial Intelligence - Breakthroughs in Theories and Technologies, Artificial Intelligence - General, tagged Artificial intelligence, Clinical Trials, Sepsis, Technology, Vasopressor therapy on June 25, 2019| Leave a Comment »

Sepsis Detection using an Algorithm More Efficient than Standard Methods

Reporter : Irina Robu, PhD

3.3.15

3.3.15 Sepsis Detection using an Algorithm More Efficient than Standard Methods, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

Sepsis is a complication of severe infection categorized by a systemic inflammatory response with mortality rates between 25% to 30% for severe sepsis and 40% to 70% for septic shock. The most common sites of infection are the respiratory, genitourinary, and gastrointestinal systems, as well as the skin and soft tissue. The first manifestation of sepsis is fever with pneumonia being the most common symptom of sepsis with initial treatment which contains respiratory stabilization shadowed by aggressive fluid resuscitation. When fluid resuscitation fails to restore mean arterial pressure and organ perfusion, vasopressor therapy is indicated.

However, a machine-learning algorithm tested by Christopher Barton, MD from UC-San Francisco has exceeded the four typical methods used for catching sepsis early in hospital patients, giving clinicians up to 48 hours to interfere before the condition has a chance to begin turning dangerous. The four standard methods were Systemic Inflammatory Response Syndrome (SIRS) criteria, Sequential (Sepsis-Related) Organ-Failure Assessment (SOFA) and Modified Early Warning System (MEWS). The purpose of dividing the data sets between two far-flung institutions was to train and test the algorithm on demographically miscellaneous patient populations.

The patients involved in the study were admitted to hospital without sepsis and all had at least one recording of each of six vital signs such as oxygen levels in the blood, heart rate, respiratory rate, temperature, systolic blood pressure and diastolic blood pressure. Even though they were admitted to the hospital without it, some have contracted sepsis during their stay while others did not. Researchers used their algorithm detection versus the standard methods applied at sepsis onset at 24 hours and 48 hours prior.
Even though sepsis affects at least 1.7 million adults mostly outside of the hospital settings, nearly 270,000 die. Researchers are hoping that the algorithm would allow clinicians to interfere prior to the condition becoming deadly.

SOURCE
https://www.aiin.healthcare/topics/diagnostics/sepsis-diagnosis-machine-learning

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AI App for People with Digestive Disorders

Posted in Artificial Intelligence - Breakthroughs in Theories and Technologies, Artificial Intelligence - General, tagged Artificial intelligence, biotech startup, chronic digestive disorders, digital therapeutics, Technology on June 24, 2019| Leave a Comment »

AI App for People with Digestive Disorders

Reporter: Irina Robu, PhD

3.3.14

3.3.14 AI App for People with Digestive Disorders, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

Artificial intelligence (AI) constitutes machine learning and deep learning, which allows computers to learn without being clearly programmed every step of the way. The basic principle decrees that AI is machine intelligence leading to the best outcome when given a problem. This sets up AI well for life science applications, which states that AI can be taught to differentiate cells, be used for higher quality imaging techniques, and analysis of genomic data.

Obviously, this type of technology which serves a function and removes the need for explicit programming. It is clear that digital therapeutics will have an essential role in treatment of individuals with gastrointestinal disorders such as IBS. Deep learning is a favorite among the AI facets in biology. The structure of deep learning has its roots in the structure of the human brain which connect to one another through which the data is passed. At each layer, some data is extracted. For example, in cells, one layer may analyze cell membrane, the next some organelle, and so on until the cell can be identified.

A Berlin-based startup,Cara Care uses AI to help people manage their chronic digestive problems and intends to spend the funding raised getting the app in the hands of gastrointestinal patients in the U.S. The company declares its app has already helped up to 400,000 people in Germany and the U.S. manage widespread GI conditions such as reflux, irritable or inflammatory bowel, food intolerances, Crohn’s disease and ulcerative colitis “with a 78.8% treatment success rate.” Cara Care will also use the funding to conduct research and expand collaborations with companies in the pharmaceutical, diagnostics and food-production industries.

SOURCE
https://www.aiin.healthcare/topics/connected-care/ai-app-digestive-disorders-raises-7m?utm_source=newsletter

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The launch of SCAI – Interview with Gérard Biau, director of the Sorbonne Center for Artificial Intelligence (SCAI).

Posted in Artificial Intelligence - Breakthroughs in Theories and Technologies, Artificial Intelligence - General, Artificial Intelligence Applications in Health Care on June 24, 2019| Leave a Comment »

The launch of SCAI – Interview with Gérard Biau, director of the Sorbonne Center for Artificial Intelligence (SCAI).

Reporter: Aviva Lev-Ari, PhD, RN

Why create a center dedicated to artificial intelligence at Sorbonne University?

Today, artificial intelligence (AI) is everywhere. It is already transforming society and changing our lives. In the context of increasing international competition, the French government launched an ambitious strategy, AI for Humanity, in March 2018 with the goal of propelling France among the leaders of AI. SCAI is fully committed to this program.

Thanks to Sorbonne University’s faculties of Letters, Medicine and Sciences & Engineering, with its partners of the Alliance, has brought together considerable strength in the fundamental aspects of the AI (in mathematics, in computer science, in robotics), its applications (in health, environment or artistic creation) and in digital humanities. In total, more than one hundred experts from many laboratories are directly involved in AI research.

The aim of SCAI is to unite these capabilities in a place where the disciplines can enrich each other, share their experiences and identify common issues to advance innovative projects.

Designed as an “AI house” in the heart of Paris, the center aims to motivate, organize and make visible multidisciplinary research in AI through the establishment of chairs of excellence, support and hospitality, interdisciplinary projects, concerted responses to calls for tenders, the creation of task forces, the setting up of doctoral programs and more.

Internationally recognized experts, such as Jim Kurose, professor emeritus at the University of Massachusetts and advisor to the US government on AI, will bring their expertise to define the strategic directions of the center.

What relationships does the research and training center intend to maintain with the industrial world?

The development of AI, which involves the deployment of technological objects such as the autonomous car, will not happen without the expertise and know-how from companies. It is therefore essential to involve our industrial partners today to focus on an application transformation of AI.

To achieve this goal, we wanted to establish Chairs of Excellence that will allow us to collaborate on innovative themes with the industrial world. A memorandum of understanding has been signed with Thales and Total and a partnership with Atos is being developed on the subject of precision medicine.

In addition, we have signed an agreement with the AP-HP which should enable the exchange of expertise, skills, the setting up of joint projects, the implementation of simplified access to the Health Data Warehouse, the mobility of researchers or students, and communication and awareness actions.

SCAI is also working with international transfer and industrial recovery centers and will be an integral part of Paris Parc, the future innovation park of Sorbonne University.

SCAI:

4 research areas: mathematics-informatics-robotics, health-medicine, climate-environment-Universes and digital humanities

More than 100 scientists, 150 doctoral and post-doctoral researchers, 300 students

More than 20 industrial partners (from start-ups to large international groups)

700 m² in the heart of Paris

1 satellite center on the Abu Dhabi campus of Sorbonne University

SOURCE

http://www.sorbonne-universite.fr/en/newsroom/actualites/launch-scai

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Narrative Building for the Future of LPBI Group: List of Talking Points

In response to this question we are in discussion on POINTS #1,2,3,4

POINT #1 for VIDEO coverage – Focus on Genomics, Volume 2

POINT #2 or #3 or #4 for VIDEOs to Focus on coverage for Marketing LPBI Group

by DESCRIPTION of what was accomplished

Video on What is the Ideal Solution for the FUTURE of LPBI Group

For POINT #1:

To build the narrative for a VIDEO dedication to Genomics, Volume Two and Marketing campaign as a NEW BOOK on NGS, the Narrative will use content extracts to built a CASE for

Why GENOMICS Volume 2 – is the Epitome of all BioMed e-Series???????

forthcoming Genomics, Volume 2

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AI System Used to Detect Lung Cancer

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Analysis of Utilizing LPBI Group’s Scientific Curation Platform as an Educational Tool: New Paradigm for Student Engagement

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New Targeted Cancer Therapy may be ‘Possible Hope’ for Some Pancreatic Cancer Patients

New Targeted Cancer Therapy may be ‘Possible Hope’ for Some Pancreatic Cancer Patients

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First Cost-Effectiveness Study of Multi-Gene Panel Sequencing in Advanced Non-Small Cell Lung Cancer Shows Moderate Cost-Effectiveness, Exposes Crucial Practice Gap

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Biologists Wondered—How Old are Cells in an Organism?

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Sepsis Detection using an Algorithm More Efficient than Standard Methods

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AI App for People with Digestive Disorders

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The launch of SCAI – Interview with Gérard Biau, director of the Sorbonne Center for Artificial Intelligence (SCAI).

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