Plenge Lab
Date posted: September 9, 2020 | Author: | No Comments »

Categories: Uncategorized

And now for something completely different on my blog. This blog was written in partnership with a number of scientists and clinicians in my local community and serves as rationale for comprehensive viral testing program in K-12 schools. The document (pdf link here) was circulated to members of our community and discussed as part of a town webinar last week (link here). 

Executive summary:

There is much debate about the value of viral testing program for K-12 schools. As described here, we support a comprehensive viral testing plan that returns results in less than 24 hours as part of an overall risk reduction strategy. Testing should be prioritized as follows: (1) baseline “time zero” at the start of school of all students, teachers and staff; (2) symptomatic testing of all students, teachers and staff; (3) at least weekly surveillance testing of all teachers and staff; (4) at least weekly surveillance testing of older students; and (5) at least weekly surveillance testing of younger students. While symptomatic testing is available through local hospitals, clinics and testing centers, baseline time zero testing and surveillance testing of asymptomatic individuals is not. Thus, additional investment is required to support a comprehensive viral testing program in K-12 schools.…

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Date posted: August 12, 2016 | Author: | No Comments »

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I recently listened to a TED Radio Hour podcast on failure (link here). Casey Gerald reminded listeners that while his biographical narrative is impressive (here), there have been many failures along the way.

This got me thinking…why don’t more people write their personal biographies in such a way that highlights their successes and failures? I have not seen one, and LinkedIn certainly does not encourage us to log our failures publicly. (Maybe an entrepreneur should start a site called LinkedOut, where you endorse people for failures and bios must be written with failures included!)

So I thought I would give it a try.

I will start with my conventional “success” bio (which can also be found here) to provide context. Then, I will provide my new “failure” bio (also here). At the end, I provide a brief “lessons learned” on how failures have shaped my professional life.  I conclude with a shout out to Charles Darwin, one of history’s most famous observer of failure in nature.

[Disclaimer: I am a Merck/MSD employee. The opinions I am expressing are my own and do not necessarily represent the position of my employer.]

Here is my conventional “successful” professional biography.

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Date posted: December 8, 2015 | Author: | No Comments »

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My daughter, on a team of fifth grade all-girls from Wellesley MA, recently competed in a First Lego League (FLL) robotics competition. My wife and I served as coaches, which was a demanding but thoroughly rewarding experience. This year’s team got me thinking about design principles for complex systems, as the goal of the annual Challenge is to build from simple (individual Lego pieces) to complex (navigating a robot built from those Lego pieces around a field with missions created from the same Lego pieces) with efficiency and precision.

For those not familiar with FLL, a video link to our team’s performance can be found here. A graphic from Google trends (link here) and the number of views on YouTube (link here) gives you a sense of the magnitude of participation across the world. Overall, FLL is a wonderful example of STEM (Science, Technology, Engineering, Math) in action. The FLL event also fits very well with evolving views on our educational system, as described in a new documentary “Most Likely To Succeed”.

[Disclaimer: I am a Merck/MSD employee. The opinions I am expressing are my own and do not necessarily represent the position of my employer.

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Date posted: August 29, 2014 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Uncategorized

In my previous blog series I talked about why genetics is important in drug discovery: human genetics takes you to a target, informs on mechanism of action (MOA) for therapeutic perturbation, provides guidance for pre-clinical assays of target engagement, and facilitates indication selection for clinical trials.

Here, I provide an overview of a new blog series on how genetics influences decision-making during drug discovery.  The key principle: human genetics establishes a disciplined mindset and a firm foundation – anchoring points – for advancing targets through the complicated process of drug discovery.  [For those less familiar with drug discovery, the end of this blog provides a brief primer on the stages of drug discovery.]

I highlight three areas: establishing a balanced portfolio, identifying targets with novel MOA, and creating a framework for objective decision-making.  In subsequent posts, I will focus primarily on how human genetics informs on the latter (decision-making), with blogs pertaining to designing assays for screens and target engagement, utilizing pre-clinical animal models, predicting on-target adverse drug events, and selecting indications for clinical trials.

1. Establish a balanced portfolio

Whether in academic research, a small biotech company (see here) or a large pharmaceutical company (such as Merck, where I work), a balanced portfolio of projects is very important.…

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Date posted: August 20, 2014 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Uncategorized

In this post I will build on previous blogs (here, here, here) about genetics for target ID and validation (TIDVAL).  Here, I argue that new targets with unambiguous promotable advantage will emerge from studies that focus on genetic pathways rather than single genes.

This is not meant to contradict my previous post about the importance of genetic studies of single genes to identify new targets.  However, there are important assumptions about the single gene “allelic series” approach that remain unknown, which ultimately may limit its application. In particular, how many genes exist in the human genome have a series of disease-associated alleles?  There are enough examples today to keep biopharma busy.  Moreover, I am quite confident that with deep sequencing in extremely large sample sizes (>100,000 patients) such genes will be discovered (see PNAS article by Eric Lander here).  Given the explosion of efforts such as Genomics England, Sequencing Initiative Suomi (SISu) in Finland, Geisinger Health Systems, and Accelerating Medicines Partnership, I am sure that more detailed genotype-phenotype maps will be generated in the near future.

[Note: Sisu is a Finnish word meaning determination, bravery, and resilience; it is about taking action against the odds and displaying courage and resoluteness in the face of adversity. …

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Date posted: August 8, 2014 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Uncategorized

phe·no·type  n.

1.The observable physical or biochemical characteristics of an organism, as determined by both genetic makeup and environmental influences.

2. An individual or group of organisms exhibiting a particular phenotype.


There are many different phenotypes: strength in the face of adversity (see here); self-reflection in a time of uncertainty (see here); and creativity amidst a sea of sameness (see here).

Phenotypes also refer to disease states such as risk of disease, response to therapy, a quantitative biomarker of medical relevance, or a physical trait such as height (as in the figure above).

For drug discovery, I have put forth the premise that human genetics is a useful tool to uncover novel drug targets that are likely to have unambiguous promotable advantage (see here).  The starting point in a genetic study is to pick the right phenotype, one that is an appropriate surrogate for drug efficacy.

And phenotype matters!

Two illustrative examples are the autoimmune diseases type 1 diabetes and rheumatoid arthritis. In type 1 diabetes the immune system destroys the pancreas, thereby preventing insulin secretion and the control of blood glucose levels.

Human genetics has identified many alleles associated with the risk of type 1 diabetes, nearly all of which act on the immune system (see here). …

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Date posted: August 2, 2014 | Author: | No Comments »

Categories: Uncategorized

The key is to find targets with novel mechanism of action (MOA) and an increased probability of success to differentiate in the clinic.

The pharmaceutical industry is in desperate need of new therapies with “unambiguous promotable advantage” that address unmet clinical need (see here, here and here).  Of course, this is a laudable goal in drug development.  In fact, given the current health care climate, we have no other choice (see here). If we are to have a sustainable industry, we must change the way we do discovery science. According to the Bernstein Report on BioBusiness: “Differentiation or Bust: Drug companies must start creating the case for value differentiation in discovery and then steadily build a body of evidence throughout the product development process.”

This means that dedicated drug hunters have a steep challenge ahead: to identify targets with novel mechanisms of action that have an increased probability to differentiate in the clinic.  This will take creativity, hard work and innovation.

There is a lot written about “innovation”. [See here for a collection of articles from the HBR Insight Center; you can test your “innovation quotient” here.]   Most comments about innovation involve creating a climate of risk taking balanced with accountability.  …

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Date posted: April 25, 2013 | Author: | No Comments »

Categories: Uncategorized

While most consider pharmacogenomics (PGx) the study of response to drugs in the clinic (e.g., efficacy and toxicity), PGx is also an amazing tool to understand fundamental biology of human disease.  Drugs perturb human physiology in a way that cannot be accomplished in the resting state.  

Most would agree that complex traits such as rheumatoid arthritis (RA) are more than just one disease.  In fact, some advocate using the term “syndrome” rather than “disease” for RA, as syndrome emphasizes the complex and heterogeneous etiology.  However, what are the underlying subsets?

Genomic technology promises to deconstruct complex traits such as RA.  The problem that I have seen, however, is how to classify the subsets of disease.  On one hand, we could take an unsupervised approach, and allow the data to form phenotypic subclassifications.  In the study of RA synovial tissue (the primary site of pathology), data suggest that there are histological categories of disease depending upon the predominant cell type.  One the other hand, what is ultimately important is how to translate disease subsets into clinical care.  And for this to occur, there must be a correlation with clinical findings.

Here is where drug exposure can help translate an unsupervised approach into a clinically actionable discovery.…

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