Micronutrients, Macronutrients and Dietary Patterns: Nutrition and Fertility

Reporter: Aviva Lev-Ari, PhD, RN

Folic acid. Folic acid is important for germ cell production and pregnancy. The recommended daily dose to prevent neural tube defects is 400-800 µg. Women who take folic acid-containing multivitamins are less likely to be anovulatory, and the time to achieve a pregnancy is reduced. Those who consume more than 800 µg of folic acid daily are more likely to conceive with assisted reproductive technology (ART) than those whose daily intake is less than 400 µg.

Vitamin D. Vitamin D may affect fertility through receptors found in the ovaries and endometrium. An extremely low vitamin D level (< 20 ng/mL) is associated with higher risk for spontaneous miscarriage risk. Some reports suggest that women with adequate vitamin D levels (> 30 ng/mL) are more likely to conceive after ART when compared with those whose vitamin D levels are insufficient (20-30 ng/mL), or deficient (< 20 ng/mL). These findings, however, are inconclusive.

Carbohydrates. Dietary carbohydrates affect glucose homeostasis and insulin sensitivity, and by these mechanisms can affect reproduction. The impact is most pronounced among women with polycystic ovary syndrome (PCOS). In women with PCOS, a reduction in glycemic load improves insulin sensitivity as well as ovulatory function. Whole grains have antioxidant effects and also improve insulin sensitivity, thereby positively influencing reproduction.

Omega-3 supplements. Omega-3 polyunsaturated fatty acids lower the risk for endometriosis. Increased levels of omega-3 polyunsaturated fatty acids are associated with higher clinical pregnancy and live birth rates.

Protein and dairy. Some reports suggest that dairy protein intake lowers ovarian reserve. Other reports suggest improved ART outcomes with increased dairy intake. Meat, fish, and dairy products, however, can also serve as vehicles for environmental contamination that may adversely affect the embryo. Fish, on the other hand, has been shown to exert positive effects on fertility.

Dietary approach. In general, a Mediterranean diet is favored (high intake of fruits, vegetables, fish, chicken, and olive oil) among women diagnosed with infertility.


A well-balanced diet, rich in vegetables and fruits, is preferred for infertile women and should provide the required micro- and macronutrients. It remains common for patients consume a wide variety of vitamin, mineral, and micronutrient supplements daily.[4] Supplements should not replace food sources of vitamins and trace elements because of differences in bioavailability (natural versus synthetic), and inaccuracy of label declarations may result in suboptimal intake of important nutrients.[5,6] Furthermore, naturally occurring vitamins and micronutrients are more efficiently absorbed.

With respect to overall diet, women are advised to follow a caloric intake that won’t contribute to being overweight or obese. Obesity is on the rise among younger people, including children. Obese women have a lower chance of conceiving and are less likely to have an uncomplicated pregnancy.[7] Proper weight can be maintained with an appropriate diet and regular exercise.

Finally, women must abstain from substances that are potentially harmful to pregnancy (eg, smoking, alcohol, recreational drugs, high caffeine intake).

Causes of Infertility

  • ovulatory defect,
  • tubal occlusion,
  • low sperm counts), and many

Factors lower the chance of pregnancy

  • older age,
  • lower ovarian reserve,
  • endometriosis

Factors can’t be altered

  • age and
  • ovarian reserve

Modifiable Factors:

  • body weight and
  • lifestyle habits




http://Peter Kovacs. Food and Fertility: What Should Women Consume When Trying to Conceive? – Medscape – Dec 06, 2018.


Can Blockchain Technology and Artificial Intelligence Cure What Ails Biomedical Research and Healthcare

Curator: Stephen J. Williams, Ph.D.


In the efforts to reduce healthcare costs, provide increased accessibility of service for patients, and drive biomedical innovations, many healthcare and biotechnology professionals have looked to advances in digital technology to determine the utility of IT to drive and extract greater value from healthcare industry.  Two areas of recent interest have focused how best to use blockchain and artificial intelligence technologies to drive greater efficiencies in our healthcare and biotechnology industries.

More importantly, with the substantial increase in ‘omic data generated both in research as well as in the clinical setting, it has become imperative to develop ways to securely store and disseminate the massive amounts of ‘omic data to various relevant parties (researchers or clinicians), in an efficient manner yet to protect personal privacy and adhere to international regulations.  This is where blockchain technologies may play an important role.

A recent Oncotarget paper by Mamoshina et al. (1) discussed the possibility that next-generation artificial intelligence and blockchain technologies could synergize to accelerate biomedical research and enable patients new tools to control and profit from their personal healthcare data, and assist patients with their healthcare monitoring needs. According to the abstract:

The authors introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship value of the data.  They also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare.  In this system, blockchain and deep learning technologies would provide the secure and transparent distribution of personal data in a healthcare marketplace, and would also be useful to resolve challenges faced by the regulators and return control over personal data including medical records to the individual.

The review discusses:

  1. Recent achievements in next-generation artificial intelligence
  2. Basic concepts of highly distributed storage systems (HDSS) as a preferred method for medical data storage
  3. Open source blockchain Exonium and its application for healthcare marketplace
  4. A blockchain-based platform allowing patients to have control of their data and manage access
  5. How advances in deep learning can improve data quality, especially in an era of big data

Advances in Artificial Intelligence

  • Integrative analysis of the vast amount of health-associated data from a multitude of large scale global projects has proven to be highly problematic (REF 27), as high quality biomedical data is highly complex and of a heterogeneous nature, which necessitates special preprocessing and analysis.
  • Increased computing processing power and algorithm advances have led to significant advances in machine learning, especially machine learning involving Deep Neural Networks (DNNs), which are able to capture high-level dependencies in healthcare data. Some examples of the uses of DNNs are:
  1. Prediction of drug properties(2, 3) and toxicities(4)
  2. Biomarker development (5)
  3. Cancer diagnosis (6)
  4. First FDA approved system based on deep learning Arterys Cardio DL
  • Other promising systems of deep learning include:
    • Generative Adversarial Networks ( requires good datasets for extensive training but has been used to determine tumor growth inhibition capabilities of various molecules (7)
    • Recurrent neural Networks (RNN): Originally made for sequence analysis, RNN has proved useful in analyzing text and time-series data, and thus would be very useful for electronic record analysis. Has also been useful in predicting blood glucose levels of Type I diabetic patients using data obtained from continuous glucose monitoring devices (8)
    • Transfer Learning: focused on translating information learned on one domain or larger dataset to another, smaller domain. Meant to reduce the dependence on large training datasets that RNN, GAN, and DNN require.  Biomedical imaging datasets are an example of use of transfer learning.
    • One and Zero-Shot Learning: retains ability to work with restricted datasets like transfer learning. One shot learning aimed to recognize new data points based on a few examples from the training set while zero-shot learning aims to recognize new object without seeing the examples of those instances within the training set.

Highly Distributed Storage Systems (HDSS)

The explosion in data generation has necessitated the development of better systems for data storage and handling. HDSS systems need to be reliable, accessible, scalable, and affordable.  This involves storing data in different nodes and the data stored in these nodes are replicated which makes access rapid. However data consistency and affordability are big challenges.

Blockchain is a distributed database used to maintain a growing list of records, in which records are divided into blocks, locked together by a crytosecurity algorithm(s) to maintain consistency of data.  Each record in the block contains a timestamp and a link to the previous block in the chain.  Blockchain is a distributed ledger of blocks meaning it is owned and shared and accessible to everyone.  This allows a verifiable, secure, and consistent history of a record of events.

Data Privacy and Regulatory Issues

The establishment of the Health Insurance Portability and Accountability Act (HIPAA) in 1996 has provided much needed regulatory guidance and framework for clinicians and all concerned parties within the healthcare and health data chain.  The HIPAA act has already provided much needed guidance for the latest technologies impacting healthcare, most notably the use of social media and mobile communications (discussed in this article  Can Mobile Health Apps Improve Oral-Chemotherapy Adherence? The Benefit of Gamification.).  The advent of blockchain technology in healthcare offers its own unique challenges however HIPAA offers a basis for developing a regulatory framework in this regard.  The special standards regarding electronic data transfer are explained in HIPAA’s Privacy Rule, which regulates how certain entities (covered entities) use and disclose individual identifiable health information (Protected Health Information PHI), and protects the transfer of such information over any medium or electronic data format. However, some of the benefits of blockchain which may revolutionize the healthcare system may be in direct contradiction with HIPAA rules as outlined below:

Issues of Privacy Specific In Use of Blockchain to Distribute Health Data

  • Blockchain was designed as a distributed database, maintained by multiple independent parties, and decentralized
  • Linkage timestamping; although useful in time dependent data, proof that third parties have not been in the process would have to be established including accountability measures
  • Blockchain uses a consensus algorithm even though end users may have their own privacy key
  • Applied cryptography measures and routines are used to decentralize authentication (publicly available)
  • Blockchain users are divided into three main categories: 1) maintainers of blockchain infrastructure, 2) external auditors who store a replica of the blockchain 3) end users or clients and may have access to a relatively small portion of a blockchain but their software may use cryptographic proofs to verify authenticity of data.


YouTube video on How #Blockchain Will Transform Healthcare in 25 Years (please click below)



In Big Data for Better Outcomes, BigData@Heart, DO->IT, EHDN, the EU data Consortia, and yes, even concepts like pay for performance, Richard Bergström has had a hand in their creation. The former Director General of EFPIA, and now the head of health both at SICPA and their joint venture blockchain company Guardtime, Richard is always ahead of the curve. In fact, he’s usually the one who makes the curve in the first place.




Please click on the following link for a podcast on Big Data, Blockchain and Pharma/Healthcare by Richard Bergström:


  1. Mamoshina, P., Ojomoko, L., Yanovich, Y., Ostrovski, A., Botezatu, A., Prikhodko, P., Izumchenko, E., Aliper, A., Romantsov, K., Zhebrak, A., Ogu, I. O., and Zhavoronkov, A. (2018) Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare, Oncotarget 9, 5665-5690.
  2. Aliper, A., Plis, S., Artemov, A., Ulloa, A., Mamoshina, P., and Zhavoronkov, A. (2016) Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data, Molecular pharmaceutics 13, 2524-2530.
  3. Wen, M., Zhang, Z., Niu, S., Sha, H., Yang, R., Yun, Y., and Lu, H. (2017) Deep-Learning-Based Drug-Target Interaction Prediction, Journal of proteome research 16, 1401-1409.
  4. Gao, M., Igata, H., Takeuchi, A., Sato, K., and Ikegaya, Y. (2017) Machine learning-based prediction of adverse drug effects: An example of seizure-inducing compounds, Journal of pharmacological sciences 133, 70-78.
  5. Putin, E., Mamoshina, P., Aliper, A., Korzinkin, M., Moskalev, A., Kolosov, A., Ostrovskiy, A., Cantor, C., Vijg, J., and Zhavoronkov, A. (2016) Deep biomarkers of human aging: Application of deep neural networks to biomarker development, Aging 8, 1021-1033.
  6. Vandenberghe, M. E., Scott, M. L., Scorer, P. W., Soderberg, M., Balcerzak, D., and Barker, C. (2017) Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer, Scientific reports 7, 45938.
  7. Kadurin, A., Nikolenko, S., Khrabrov, K., Aliper, A., and Zhavoronkov, A. (2017) druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico, Molecular pharmaceutics 14, 3098-3104.
  8. Ordonez, F. J., and Roggen, D. (2016) Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition, Sensors (Basel) 16.


Other Articles in this Open Access Journal on Digital Health include:

Can Mobile Health Apps Improve Oral-Chemotherapy Adherence? The Benefit of Gamification.

Medical Applications and FDA regulation of Sensor-enabled Mobile Devices: Apple and the Digital Health Devices Market


How Social Media, Mobile Are Playing a Bigger Part in Healthcare


E-Medical Records Get A Mobile, Open-Sourced Overhaul By White House Health Design Challenge Winners


Medcity Converge 2018 Philadelphia: Live Coverage @pharma_BI


Digital Health Breakthrough Business Models, June 5, 2018 @BIOConvention, Boston, BCEC







Non pure motives for pushing recertification: The American Board of Internal Medicine attempted to expand its recertification process and keep its medical monopoly that abuses its immense power.

Reporter: Aviva Lev-Ari, PhD, RN


“It is incumbent upon The American Board of Internal Medicine (ABIM) and/or the American Board of Medical Specialties (ABMS) to engage a respected independent party to assess the impact of The Maintenance of Certification, (MOC) program and make the findings publicly available” required by The American College of Rheumatology

ABIM’s survival as a medical monopoly that abuses its immense power seems less probable with each passing day. And, because of its arrogance and the appearance of corruption it allowed to metastasize inside the organization, the officials there have no one to blame but themselves.

It’s a horror story that has played out for years throughout the U.S. as the ABIM abuses its monopoly power to force doctors to do whatever it decrees, while ignoring the many doctors who have demanded for years that independent researchers conduct comprehensive studies to determine if ABIM’s requirements do anything to improve patient care. This medical protection racket has made millionaires of ABIM top officers, financed a ritzy condominium, limousines and first-class travel, all while sucking huge sums of cash out of the health care system.

But now, after decades of unchecked rule by ABIM, cracks are appearing in the organization’s facade of power. Thousands of doctors began a widespread revolt months ago and, in the last few weeks, evidence that their efforts are succeeding has started rolling in. ABIM officials have proclaimed that they are rushing to make changes—and indeed have announced some changes—but it seems they waited too long and are changing too little.

Rheumatologists, who must fulfill ABIM’s requirements for maintenance of certification, or MOC, recently slapped down the process—and hard.

“There is evidence that many of the MOC requirements have no beneficial impact on clinical care,” the statement says. “Moreover, the direct and indirect costs of the MOC program to physicians and the health care system is excessive.”

The study concluded that internists incur an average of $23,607 in MOC costs over 10 years—with doctors who specialize in cancers and blood diseases out $40,495. All told, the study concluded, MOC will suck $5.7 billion out of the health care system over 10 years, including $5.1 billion in time costs (resulting from 32.7 million physician-hours spent on MOC) and $561 million in testing costs. And remember—all that time and expense is for a program that has not been proven to accomplish anything.

And the NBPAS process is completely different than the one required by ABIM. A two-year recertification through NBPAS costs $169 (a single review course for the ABIM test costs more than $1,000.) It requires that physicians obtain initial certification through ABIM or one of its affiliated organizations. Then, for recertification, it requires physicians to attend 50 hours of what are known as qualified continuing medical education programs every two years. That way, doctors choose what education programs most benefit their practice by attending about 25 hours of those courses and conferences each year. No time is wasted learning about items that have no relevance to the work of a particular doctor.

And the National Board of Physicians and Surgeons (NBPAS) process is completely different than the one required by ABIM. A two-year recertification through NBPAS costs $169 (a single review course for the ABIM test costs more than $1,000.) It requires that physicians obtain initial certification through ABIM or one of its affiliated organizations. Then, for recertification, it requires physicians to attend 50 hours of what are known as qualified continuing medical education programs every two years. That way, doctors choose what education programs most benefit their practice by attending about 25 hours of those courses and conferences each year. No time is wasted learning about items that have no relevance to the work of a particular doctor.


What’s ruining medicine for physicians: MOC costs and requirements

University of California accounts for nearly 10% of all published research in the United States. It’s also a significant partner of Elsevier, which publishes about 18% of all UC output and collects more than 25% of the university’s $40-million overall subscription budget.


Reporter: Aviva Lev-Ari, PhD, RN

UC policy has been explicitly committed to open access since 2013, when the university’s Academic Senate adopted the policy. UC authors are required to deposit versions of their papers or links in the university’s eScholarship online repository, which currently holds more than 200,000 items available to the public for free. (Compliance by researchers is thought to be spotty as yet, however, in part because there’s no enforcement system.)

No one knows yet how the showdown between UC and Elsevier will play out. Some observers expect that the deadline will be extended so the two sides can continue negotiating, though Elsevier would have the right to shut off access to new journal issues as of Jan. 1. (Access to prior publications already paid for wouldn’t be affected.)

As for the longer time frame, the research community expects the big publishers to stay in business, but perhaps with narrower profit margins and an evolved model more reliant on preparation fees than subscriptions.

Researchers have begun to sense that they may have more leverage against the publishers than they assumed. “As authors, we do have a choice of where we send our articles and invest our time as peer reviewers,” Bales says. “If enough of the publishers’ customers end their subscriptions… they’ll have to change.”


In UC’s battle with the world’s largest scientific publisher, the future of information is at stake

by Michael Hiltzik

Other related articles published in this Open Access Online Scientific Journal include the following:

Three Genres in e-Scientific Publishing AND Three Scientists’ Dilemmas

Curator: Aviva Lev-Ari, PhD, RN

e-Scientific Publishing: The Competitive Advantage of a Powerhouse for Curation of Scientific Findings and Methodology Development for e-Scientific Publishing – LPBI Group, A Case in Point

Author and Editor-in-Chief: Aviva Lev-Ari, PhD RN

Innovations in electronic Scientific Publishing (eSP): Case Studies in Marketing eContent, Curation Methodology, Categories of Research Functions, Interdisciplinary conceptual innovations by Cross Section of Categories, Exposure to Frontiers of Science by Real Time Press coverage of Scientific Conferences

Editor-in-Chiefhttp://pharmaceuticalintelligence.comAviva Lev-Ari, PhD, RN

FIVE years of e-Scientific Publishing, Top Articles by Author and by e-Views >1,000, 4/27/2012 to 1/29/2018

Editor-in-Chief: Aviva Lev-Ari, PhD, RN



Gene-editing Second International Summit in Hong Kong: George Church, “Let’s be quantitative before we start being accusatory”


Reporter: Aviva Lev-Ari, PhD, RN

UPDATED on 11/30/2018

Gene editing takes a foreboding leap forward

He Jiankui. Photo: Zhang Wei/Chinese News Service/VCG via Getty Images


China is temporarily suspending the work of scientists who claimed twins were born after being genetically edited as embryos.

Why it matters: The scientific consensus is that gene editing embryos at this stage of science is “irresponsible.” But, while this particular experiment has not been verified, the fact is the technology is available to researchers, so there’s a growing call for international limitations on its use.

ICYMI: Chinese scientist He Jiankui announced earlier this week that twins were born after he used the gene-editing tool CRISPR-Cas9 to cut the CCR5 gene that’s known to play a role in HIV infection.

  • He stirred even more dismay when he mentioned the possibility of a second pregnancy.
  • China currently bans human implantation of gene-edited embryos. Its Ministry of Science and Technology is investigating the claims, per Xinhua.

There are concerns about the safety, efficacy and possible mosaicism, where a person can contain genes in both its edited and unedited forms, from cutting genes.

  • Editing embryos raises an even bigger concern: The genetic changes and all the unknowns around them can be passed down to future generations.

Between the lines: Not everyone viewed it as a complete disaster. For instance, Harvard Medical School’s George Daley suggested that it may be time to reconsider the massive amounts of research done over the past several years and look for plausible methods of moving forward.

What to watch: Scientists are cautious about predicting what the impact will be, in part because the details of this claim are thin. However, the debate is heating up and one concern is it will dampen important research.

  • Medical ethicist Jonathan Moreno from the University of Pennsylvania says the situation reminds him of other times in history where there were tremors in the science world, like the death of 18-year-old Jesse Gelsinger in 1999 from a gene therapy trial that led to years of diminished research.

The bottom line: The alarm over what could be next is real. But scientists hope the current debate will promote consensus on firm limits and promote transparency.

Go deeper:


From: Andrew Freedman <>

Date: Thursday, November 29, 2018 at 5:33 PM

To: Aviva Lev-Ari <>

Subject: Axios Science: About that climate report — Gene editing takes a foreboding step — Building in harms’ way



He Jiankui spoke at the second international summit on human genome editing in Hong Kong. (Alex Hofford/EPA-EFE/Shutterstock)

CRISPR-baby scientist faces the music

The scientist who claims to have helped produce the first people born with edited genomes faced a tough crowd yesterday at a gene-editing summit in Hong Kong. He Jiankui gave a 20-minute talk about his unpublished work in animals and humans before opening a 40-minute Q&A session (watch it here). He faced difficult questions about the ethics of his work and his choice to keep it mostly under wraps until after the babies were born, and left many unanswered.

Meanwhile, prominent geneticist George Church is one of the few scientists who seem to be looking on the bright side of He’s controversial claim. “Let’s be quantitative before we start being accusatory,” Church told Science. “As long as these are normal, healthy kids it’s going to be fine for the field and the family.”

Nature | 9 min read & Science | 6 min read

Read more: Genome-edited baby claim provokes international outcry



From: Nature Briefing <>

Reply-To: Nature Briefing <>

Date: Thursday, November 29, 2018 at 12:18 PM

To: Aviva Lev-Ari <>

Subject: CRISPR-baby scientist faces the music at gene-editing summit




The ethical red flags of genetically edited babies

Driving the news: Chinese scientist He Jiankui announced Sunday night that a pair of twin girls had been born from embryos he modified using the gene-editing tool known as CRISPR.

  • He hasn’t provided solid proof, but if it‘s true, it would be the first time the technology has been used to engineer a human.

What they’re saying: The inventors of CRISPR technology did not seem pleased with the development — one called for a moratorium on implantation edited embryos into potential mothers.

  • “I hope we will be more cautious in the next thing we try to do, and think more carefully about when you should use technology versus when you could use technology,” said Jessica Berg, a bioethicist at Case Western Reserve University.

Between the lines: Several specific factors in He’s work sent up ethical red flags.

  • Many scientists had assumed that, when this technology was first used in humans, it would edit out mutations tied to a single gene that were certain to cause a child pain and suffering once it was born — essentially, as a last resort.
  • But He used CRISPR to, as he put it, “close a door” that HIV could have one day traveled through. That has prompted some speculation that this project was more about testing the technology than serving an acute medical need.
  • “That should make us very uneasy about the whole situation,” Berg said. “Of all the things to have started with, it does make you a little suspicious about this particular choice.”

The intrigue: There’s a lot we still don’t know about He’s work, and that’s also contributing to an attitude of skepticism.

  • How many embryos did he edit and implant before these live births?
  • How will he know it worked? As the children age, they’ll likely have their blood drawn and those samples will be exposed to HIV in a lab, but researchers aren’t going to tell them to go out and have unprotected sex or use intravenous drugs — another reason HIV seems like an odd starting place for human gene editing.
  • How did this even happen? The university where He worked said he was on leave, and Chinese officials have said he’s under investigation. But gene editing is a pretty hard thing to freelance.

The other side: He defended his work in a video message, saying, “I understand my work will be controversial but I believe families need this technology and I’m willing to take the criticism for them.”

  • “Their parents don’t want a designer baby, just a child who won’t suffer from a disease which medicine can now prevent,” He said.

Yes, but: Now that this threshold may have been crossed, attempts to create “designer babies” — within the limitations of what CRISPR can do — probably aren’t far off, some experts fear.

  • There are “likely to be places that are less regulated than others, where people are going to attempt to see what they can do,” Berg said. “I wouldn’t say everything in the world has changed now, but it’s certainly the next step.”

The Future of Precision Cancer Medicine, Inaugural Symposium, MIT Center for Precision Cancer Medicine, December 13, 2018, 8AM-6PM, 50 Memorial Drive, Cambridge, MA

Reporter: Aviva Lev-Ari, PhD, RN

#CPCM2018 @AVIVA1950 @pharma_BI



Aviva Lev-Ari, PhD, RN, Editor-in-Chief, will attend and cover this event in REAL TIME for 

Over the past decade, there have been major advancements in the field of precision medicine, leading to exciting new treatments for some cancer patients. Much attention has been focused on genomic profiling of tumors to identify genomic alterations that might guide selection of specific therapies for individual patients. Beyond genomics, however, there is a variety of other precision approaches that can identify and exploit cancer-specific biological mechanisms including proteomics, metabolomics, and computational modeling, resulting in the more effective use of existing cancer medicines. On Thursday, December 13, 2018, the MIT Center for Precision Cancer Medicine will hold its inaugural annual symposium in the Samberg Conference Center at MIT. This full-day event will feature leading researchers and clinicians, who will highlight recent advances in precision cancer medicine and share perspectives on the future. An industry panel will also discuss the barriers to instituting precision medicine into current and future clinical trials.


Keynote Address

Charles Sawyers

Charles Sawyers, MD

Chair, Human Oncology and Pathogenesis Program
Memorial Sloan Kettering Cancer Center


Andrea Califano

Andrea Califano, PhD

Clyde and Helen Wu Professor of Chemical Systems Biology, Columbia University
Chair, Department of Systems Biology, Columbia University
Director, JP Sulzberger Columbia Genome Center
Associate Director, Herbert Irving Comprehensive Cancer Center

Chris Love

J. Christopher Love, PhD

Professor of Chemical Engineering, MIT
Associate Member, Ragon Institute of MGH, MIT and Harvard
Member, Koch Institute, MIT

Richard Marais

Richard Marais, PhD

Professor of Molecular Oncology
Director, CRUK Manchester Institute
The University of Manchester

Kenna Mills Shaw

Kenna Mills Shaw, PhD

Executive Director
Sheikh Khalifa Bin Zayed al Nahyan Institute for Personalized Cancer Therapy
MD Anderson Cancer Center

Alice Shaw

Alice Shaw, MD, PhD

Professor, Harvard Medical School
Director, Thoracic Cancer Program, Massachusetts General Hospital

Matt Vander Heiden

Matthew Vander Heiden, MD, PhD

Associate Professor of Biology, MIT
Associate Director, Koch Institute
Member, MIT Center for Precision Cancer Medicine

Mike Yaffe

Michael B. Yaffe, MD, PhD

David H. Koch Professor of Science, MIT
Professor of Biology and Biological Engineering, MIT
Director, MIT Center for Precision Cancer Medicine
Director, Koch Institute Clinical Investigator Program

Jean Zhao

Jean Zhao, PhD

Professor of Biological Chemistry and Molecular Pharmacology
Harvard Medical School and Dana-Farber Cancer Institute

Panelists: Barriers to Instituting Precision Medicine in Clinical Trials


Peter Hammerman, MD, PhD

Global Head, Translational Research
Oncology Disease Area
Novartis Institutes for BioMedical Research


Steffan N. Ho, MD, PhD

Vice President, Head of Translational Oncology
Pfizer Global Product Development

Shiva Malek

Shiva Malek, PhD

Director and Principal Scientist
Department of Discovery Oncology
Genentech Inc


Kevin Marks, PhD

VP of Biology
Agios Pharmaceuticals

Michael Rothenberg

S. Michael Rothenberg, MD, PhD

Vice-President, Research and Development
Loxo Oncology, Inc.

Angela Koehler


Angela Koehler, PhD

Goldblith Career Development Professor in Applied Biology, MIT
Member, Koch Institute for Integrative Cancer Research
Member, MIT Center for Precision Cancer Medicine




  • Peter Hammerman, Novartis Institutes for BioMedical Research
  • Steffan Ho, Pfizer
  • Shiva Malek, Genentech, Inc
  • Kevin Marks, Agios Pharmaceuticals
  • S. Michael Rothenberg, Loxo Oncology, Inc

Moderated by Angela Koehler, MIT’s Koch Institute


8:00 am Registration and continental breakfast

8:45 am Opening remarks by Michael Yaffe (MIT’s Koch Institute)

  • Season of great expectation, tumor genetics is just the beginning, beyond: science, engineering, medicine: beyond genomics: immunology, cell biology, early detection, new drug development for the undrugable, system biology, RNAi
  • Jack Tyler was the initiator to find a donor for CPCM

9:00 am Keynote Address by Charles L. Sawyers (Memorial Sloan Kettering Cancer Center)

  • developed a drug for prostate cancer
  • Clinical trained oncologist/genomics
  • Lineage Plasticity:
  1. luminal cells in histology of origin and basal cells and require androgen receptor AR) function
  2. deprive lunimal cells fro growth factor
  3. Hormonal therapy Leuprolite, degarelix [castration methastatic]
  4. after relapse 2nd generation anti-androgens abirateron
  7. Lineage shift Sox2 level goes up – prevent drug resistance, in vivo and in vitro
  8. SOX2 promotes lineage placticity and antiadrogen resistance in TP53 and RBI-deficient prostate cancer
  9. Evolution of Lineage plasticity over time
  10. AR Pathway inhibition accelerates lineage plasticity: synaptophysin-positive disease in-vivo
  11. scRNA-seq time course – modeled by diffusion map displayed in luminal and basal cells
  12. Emergence of EMT phenotype, with retention of epithelial features
  13. Use CRISPR to perturb luminal plasticity by phyeno type
  14. Genomic landscape of Primary Prostate Cancer: ERG gain drives luminal layer
  15. Different classes of FOXA1 mutations in Prostate organoid Cancer – Missense, inframe, truncated
  16. FOXA1 key in hormone receptor signaling
  17. Hypermorphic peaks – ATAC-seq neomorphic FOXA1 pioneering activity
  18. Common Prostate Cancer Genes:differentiation phenotypes: TP53 Loss, RB1 – Loss,
  19. work of Matan Hofree – four subtypes of luminal cells
  20. involution and regeneration of single cell RNAseq
  21. Transcriptional shifts in response to castration/androgen addback
  22. androgen addback: 50% of luminal cells are proliferation in 48 hours
  23. cell responsible for organ regeneration


9:45 am Alice T. Shaw (Massachusetts General Hospital)

  • evolution of drug resistance in Lung Cancer
  • oncogenic drivers in lung adenocarcenoma –
  1. EGFR – sensitizing 19.4% of all patients
  2. KRAS
  3. ALK
  4. ROS1
  5. CMET
  6. BRAF
  7. NTRK1
  8. RET

Delay and prevention of drug resistance: liquid biopsy of pleural fluids and serial blood collections

  • Crizotinib patient with ROS1 + nsclc
  • acquired mutation in ROS1 G2032R – resistance to Crizotinib – Michael Lawrence, MGH – analysis of mutation and resistance
  • Repotrectinib – for ROS1 – Resistance mediated by this mutation
  • If patient fails three antiinhibitor drugs: secondary ALK mutations mediate Crizotinib Resistance
  • 2nd generation of  ALK inhibitors are structurally Distinct molecules
  • Lorlatinib – 3rd generation –>> back to 1st generation Crizotinib
  • Clonal evolution of resistance in ALK in NSCLC
  • compound mutations in ALK mutations – Lorlatinib Resistance
  • Sequential TKI therapy foster the development of compound mutation refractory to all generations og ALK TKIs – compound mutation can’t be overcome
  • Intratumoral Heterogeneity revealed by multiregion sequencing of renal cell carcinoma and resected NSCLC
  • somatic mutations: Pre-treatment to Lorlatinib resistance
  • Clonal Analysis: Multiple Drivers of resistance underlie clinical relapse
  • genomic instability – eradicate residual disease to eliminate drug resistance and tolerance persistance


10:25 am Networking Break

10:45 am Richard Marais (Cancer Research UK, Manchester Institute)

  • Melanoma – Precision Medicin
  • Request – NOT TO PUBLISH on the INTERNET, some of the work presented is not PUBLISHED.
  • Request is honored

11:25 am Matthew Vander Heiden (MIT’s Koch Institute)

  • Targeting Metabolism is altered in cancer
  • Metabolism is glucose carbohydrates, lipids – conversion of nutrients into biomass: ATP, Protein, Nucleic acid,
  • Not -proliferating cells vs proliferating cells
  • genetic mutations, tissue of origin, lineage of cells — metabolism takes place: combination of these three facto
  • environment consists the metabolic network definers.d by cell intrinsic network
  • Assessment of nutrient levels in tumor microenvironment
  • Metabolite analysis: ion suppression vs nutrients
  • nutrients are available to cells in tumors
  • depletion of glucose vs enrichment
  • metabolite most different: Gluthamine, needed for cancer to grow
  • Lineage can contribute – tryptophane and argenine
  • gluthamine – Cyctine affect gluthamine sensitivity to gluthamine inhibitors
  • what you eat, where is the tumor locate, tissue environment — more important
  • therapeutic window: metabolism processes – cell proliferation
  • ability to make aspartate – given to mice pancreatic  — tumor grow faster
  • cellular oxidation state correlate with pyruvate oxidation — PDH Activator suppress oxidation
  • Aspartate vs NAD+/NADH – lactate TCA – form more carbon
  • PDH activation reduces Redux
  • Serine availability can limit proliferation even in cells with increase
  • Serine vs NAD regeneration
  • which cancer falls into which group : Serine pathway – increase serine synthesis: Melanoma vs Breast cancer
  • growth of breast cancer: Serine availability dependent – accelerate of inhibit growth by level of serine
  • Model for how nutrient limitation affect tumor growth, tumor size depends of serine levels


12:05 pm Box lunch

12:30 pm Industry panel: Barriers to instituting precision medicine into clinical trials

  • Long term benefits of Precision Medicine
  • What phynotype are now looked for?

Michael Rothenberg

  1. short term, identify mutations
  2. more testing is needed
  3. sequencing the therapies
  4. challenge getting tissue, doing experiments in house
  5. Industry needs Academia collaboration for accelerated innovations
  6. AI may lower the cost of drug discovery


  2. phynotyping, tissue acquisition immune phenotype, what drive therapeutic response?
  3. genetic drivers
  4. HR seeks Scientistist that worked in TEAMS, collaborative science


  1. long term benefits are very important
  2. Stage III disease – technology advances
  3. advanced in the regulatory space
  4. smaller cohort size to approve a drug
  5. biologic complexity, driver oncogenes, precision to imprecision
  6. cost of risk in investment in innovations
  7. check point inhibitor – known biology and immuno-modulation, data hypothesis and moving forward
  8. Organizational culture, interaction in teams, functional behavior
  9. commit to deliverable, perfect timing contingent on work of others.

Peter Hammerman

  1. single cell tumor immunity in combination drug therapy
  2. Tumor monitoring over time
  3. Novartis is interested to collaborate with innovators in Academia and in other institutions
  4. critical thinking on DATA and on negative data
  5. Combination drug therapy: orthogonal mechanism of actions and drug classed – toxicity is an issue

Shiva Malek

  1. How to drug mutations on DATA
  2. Acquired and intrinsic mutations
  3. exposure and patient safety
  4. UCSF’s Ashkenazi’s Team and Genetech – basic biology area selection
  5. Failure are not talked about
  6. Round table for problem solvers, how you approach a problem
  7. translational work require skills beyond technical expertise
  8. learning the navigation inside an organization
  9. leadership in R&D, expected to demonstrate leadership, the Scientist needs to have command of the field and of desirable directions of research


2:00 pm J. Christopher Love (MIT’s Koch Institute)

Acceleration of the PROCESS to develop Precision Medicine products

  • design, build, test – PROCESS
  • New drugs and vaccines – the process is iterative
  • measurements, with use of smallest number of samples
  • deliver precision medical: small f patients or large population or
  • clinical samples provide rich source of information: Blood or tissue sample
  • Tissue – extract RNA, component cells, single-cell RNA sequencing,
  • Challenges of enabling scRNA-seq in clinical labs
  • Probability, scale, capture efficiencies, temporal uniformity
  • single-cell sequencing
  • Seq-Well: method for scRNA-Seq
  • New Chemistries for T-cell
  • Blood: cell, cfDNA, Exosomes
  • map cancer genome from blood
  • Tissue:
  • Single circulating Tumor cells:
  • yield genomic landscape of cancer
  • cell free DNA, vells, proteins, metabolite, Tumor is existence, draw blood
  • cfDNA Tumor Fraction is prognostic of survival in mTNBC
  • automate to 13 cancer types
  • Rs is now possible
  • reduce sample requirement
  • cost is low digital information from clinical samples
  • Keytruda – is a molecular Signature
  • low volume product, advanced preparation (mo-years) __>>> agile solutions (days to years)
  • bentchtop, on-demand manufacturing system: Production, Purification, Formulation
  • hand-free production of formulated G-CSF: comparable to licensed products.
  • Plug and play manufacturing using  InSeq
  • Novel MAbs from patients
  • Many molecules to many products


2:40 pm Andrea Califano (Columbia University, System Biology)

Mechanistic Framework for the systematic pharmacological targeting of Non-Oncogene Dependencies – Precise Precision Oncology

  • systematic elucidation od critical cancer cell dependencies
  • drug MOA
  • Tumor dependencies to Drug MOA
  • Tumor heterogeneity
  • ARACNe – regulatory targets of regulatory proteins
  • Combinational Therapy: HER@ inhibitor and JAK1/JAK2 inhibitor
  • Driver Mutations
  • Aberrantly activated protein for Prioritizing treatment in patients
  • Checkpoint activity reversal – prioritize drugs based on
  • Tumor model selection: GIST
  • 260 patients, 14 untreatable cancers — N of 1 Study
  • Single cell Studies – active proteins in stem-like progenitor cells
  • Ivermectin Treatment vs Control (7d vs 14d)


3:20 pm Networking Break

3:40 pm Jean Zhao (Dana Farber Cancer Institute)

Immunotherapy and Targeted Therapy in Cancer Therapy

  • Targeting cancer with CDK4/6 inhibitors
  • CDK4/6 inhibitors causes tumor regression in breast cancer and regression of CT-26 colorectal cancer
  • CDK4/6DNMT1 inducing viral mimicry
  • PARP inhibitors  changing treatment in ovarian cancer
  • FDA approved three drugs for ovarian cancer
  • p53-null; BRCA-null; myc high – model testing


4:20 pm Kenna Mills Shaw (MD Anderson Cancer Center)

  • PM nor a Silver bullet nor a Dream Illusion
  • 2013: not all mutations are equally actionable
  • Context of Biomarkers
  • co-mutations in lung cancer identity – therapeutic vulnerability
  • NGS cost decrease leads to increases in Data generation
  • there are only 125 genes ACTIONABLE IN THE CLINIC
  • finding biomarkers beyond direct targets
  • clinical actionability:80K mutation – 32%
  • patients: No standard treatment available
  • Enrollment inGenotype Matched TRIALS
  • 69% GOT NEW REGIMEN, 17% did not come back — no one called them
  • 58% enrolled on genotrype-matched trials
  • Beyond NGS:


5:00 pm Michael Yaffe (MIT)

  • inflammation
  • Therpeutics-targeted Synthetic Lethality
  • BRCA mutation seen in 10%-20% of patients
  • p53 mutations DNA demage – leads to apoptosis p38 MK2 as a pathway is taking over repair DNA and no apotosis occurs.
  • doxorubicin
  • Nanoparticle targeting of siRNAs to established tumors
  • The Concept of augmented Synthetic Lethality   —- enhance a prevosly known synthetic interaction by targeting additional pathways
  • combination of repair pathway  and checkpoint activation – lead to better therapeutic results
  • MK2 – targets hnRNP A0 (an RNA binding protein)  – Cleaved Caspase 3 – is synthetic lethal with p53 mutuant tumors, not just p53 null alleles
  • MK2 links Inflammation and Cancer – IBD –>> polyps and Colon Cancer
  • myeloid cell recruitment to inflammatory tumors in
  • MK2 KO mice: IL-4 –M2 magrophage – tumor progression; regulate the tumor microenvironment
  • IFNgamma –>M1 macrophages – tumor suppression





CMS initiative in Modernizing Medicare to lead to Lower Prescription Drug Costs

Reporter: Aviva Lev-Ari, PhD, RN


CMS Takes Action to Lower Prescription Drug Costs by Modernizing Medicare



CMS Takes Action to Lower Prescription Drug Costs by Modernizing Medicare 
Proposed regulation for Medicare Parts C & D would strengthen negotiations with prescription drug manufacturers to lower costs and increase transparency for patients

Today, the Centers for Medicare & Medicaid Services (CMS) proposed polices for 2020 to strengthen and modernize the Medicare Part C and D programs. The proposal would ensure that Medicare Advantage and Part D plans have more tools to negotiate lower drug prices, and the agency is also considering a policy that would require pharmacy rebates to be passed on to seniors to lower their drug costs at the pharmacy counter.

“President Trump is following through on his promise to bring tougher negotiation to Medicare and bring down drug costs for patients, without restricting patient access or choice,” said HHS Secretary Alex Azar. “By bringing the latest tools from the private sector to Medicare Part D, we can save money for taxpayers and seniors, improve access to expensive drugs many seniors need, and expand their choice of plans. The Part D proposals complement efforts to bring down costs in Medicare Advantage and in Medicare Part B through negotiation, all part of the President’s plan to put American patients first by bringing down prescription-drug prices and out-of-pocket costs.”

In the twelve years since the Part D program was launched, many of the tools outlined in today’s proposal have been developed in the commercial health insurance marketplace, and the result has been lower costs for patients. Seniors in Medicare also deserve to benefit from these approaches to reducing costs, so today CMS is proposing to modernize the Medicare Advantage and Part D programs and remove barriers that keep plans from leveraging these tools.

“In designing today’s proposal, foremost in the agency’s mind was the impact on patients, and the proposal is yet another action CMS has taken to deliver on President Trump and Secretary Azar’s commitment on drug prices,” said CMS Administrator Seema Verma. “Today’s changes will provide seniors with more plan options featuring lower costs for prescription drugs, and seniors will remain in the driver’s seat as they can choose the plan that works best for them. The result will be increasing access to the medicines that seniors depend on by lowering their out-of-pocket costs.”

Private plan options for receiving Medicare benefits are increasing in popularity, with almost 37 percent of Medicare beneficiaries expected to enroll in Medicare Advantage in 2019, and Part D enrollment increasing year-over-year as well. The programs are driven by market competition; plans compete for beneficiaries’ business, and each enrollee chooses the plan that best meets his or her needs. Consumer choice puts pressure on plans to improve quality and lower costs.  Premiums in both Medicare Advantage and Part D are projected to decline next year.

Today’s proposed changes include:

  • Providing Part D plans with greater flexibility to negotiate discounts for drugs in “protected” therapeutic classes, so beneficiaries who need these drugs will see lower costs;
  • Requiring Part D plans to increase transparency and provide enrollees and their doctors with a patient’s out-of-pocket cost obligations for prescription drugs when a prescription is written;
  • Codifying a policy similar to the one implemented for 2019 to allow “step therapy” in Medicare Advantage for Part B drugs, encouraging access to high-value products including biosimilars; and
  • Implementing a statutory requirement, recently signed by President Trump, that prohibits pharmacy gag clauses in Part D.

CMS is also considering for a future plan year, which may be as early as 2020, a policy that would ensure that enrollees pay the lowest cost for the prescription drugs they pick up at a pharmacy, after taking into account back-end payments from pharmacies to plans.

Medicare Advantage and Part D will continue to protect patient access, as both programs are embedded with robust beneficiary protections. These include CMS’s review of Part D plan formularies, an expedited appeals process, and a requirement for plans to cover two drugs in every therapeutic class.

CMS looks forward to receiving comments on these proposals and other policies under consideration.

For a blog post on the proposed rule by Secretary Azar and Administrator Verma, please visit:

For a fact sheet on the proposed rule, please visit:

The proposed rule (CMS-4180-P) can be downloaded from the Federal Register at:


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