Plenge Lab
Date posted: March 24, 2017 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Precision Medicine

Like many, I waited with bated breath for results of the anti-PCSK9 (evolocumab) FOURIER cardiovascular outcome study last week. There have been many interesting commentaries written on the findings.  A few of my favorites are listed here (Matthew Herper), here (David Grainger), here (Derek Lowe), and here (Larry Husten), amongst others, with summaries provided at the end of this blog.  Most of these articles focused on clinical risk reduction vs. what was predicted for cardiovascular outcome, as well as whether payers will cover the cost of the drugs.  These are incredibly important topics, and I won’t comment on them further here, other than to say that the debate is now about who should get the drug and how much it should cost.

In this blog, I want to emphasize key points that pertain to human genetics and drug discovery.  And make no mistake: the anti-PCSK9 story and FOURIER clinical trial outcome is a triumph for genetics and drug discovery. This message seems to be getting muddled, however, given the current cost of evolocumab and the observation that cardiovascular risk reduction was less than expected, based on predictions from a 2005 study published by Cholesterol Treatment Trialists (CTT) (see Lancet study here).

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If you could pick three innovations that would revolutionize drug discovery in the next 10-20 years, what would they be?

I found myself thinking about this question during a recent family vacation to Italy. I was visiting the Galileo Museum, marveling at the state of knowledge during the 1400-1600’s. The debate over planetary orbits seem so obvious now, but the disagreement between church and science led to Galileo’s imprisonment in 1633.

So what is it today that will seem so obvious to our children and grandchildren…and generations beyond? Let me offer a few ideas related to drug discovery, and hope that others will add their own. I am not sure if my ideas are grounded in reality, but that is part of the fun of the game. In addition, “The best way to predict the future is to invent it.”

To start, let me remind readers of this blog that I believe that the three major challenges to efficient drug discovery are picking the right targets, developing the right biomarkers to enable proof-of-concept (POC) studies, and testing therapeutic hypotheses in humans as quickly and safely as possible. Thus, the future needs to address these three challenges.


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Date posted: June 26, 2015 | Author: | No Comments »

Categories: Drug Discovery Human Genetics

I attended the Mendelian randomization meeting in Bristol, UK this past week (link to the program’s oral abstracts here). The meeting was timed with the release of a number of articles in the International Journal of Epidemiology (current issue here, Volume 44, No. 2 April 2015 TOC here). This blog is a brief synopsis of the meeting – with a focus on human genetics and drug discovery. The blog includes links to several slide decks, as well as references to several published reviews and studies.

[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.]

Several speakers, including Lon Cardon from GSK, gave overview talks on how Mendelian randomization can be applied to pharmaceutical development. In my overview, I described important guiding principles for successful drug discovery (link to my slides here), and how Mendelian randomization (MR) is applied within this framework. In particular, I emphasized the role of establishing causality in the human system: MR is a powerful tool to pick targets by estimating safety and efficacy (i.e., genotype-phenotype dose-response curves) at the time of target identification and validation; MR is effective at picking biomarkers for target modulation; and MR provides quantitative modeling of clinical proof-of-concept (POC) studies.…

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Date posted: March 9, 2015 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Precision Medicine

My overly simplistic vision of the way to transform drug discovery is to (1) pick targets based on causal human biology (e.g., experiments of nature, especially human genetics), (2) develop drugs that recapitulate the biology of the human experiments of nature (e.g., therapeutic inhibitors of proteins), (3) develop biomarkers that measure target modulation in humans, and (4) test therapeutic hypotheses in humans as safely and efficiently as possible.

Thus, one of my favorite themes is “causal human biology”. The word “causal” is key: it means that there is clear evidence between the cause-effect relationship of target perturbation in humans and a desired effect on human physiology. Human genetics represent one way to get at causal human biology, and in my last blog I highlighted recent examples outside of human genetics.

I am constantly scanning the literature to find examples that support or refute this model, as I predict that a discipline portfolio of projects based on causal human biology will be more successful than past efforts by the pharmaceutical industry.

This week I have selected two articles on genetics/genomics in drug discovery that provide further support of this model. [Disclaimer: the first study was funded by Merck, my employer.]

Clinical improvement in psoriasis with specific targeting of interleukin-23, Kopp et al Nature (March 2015).

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Date posted: January 16, 2015 | Author: | No Comments »

Categories: Drug Discovery Human Genetics

Welcome to our first blog of 2015 on genetics/genomics for drug discovery. After a nice vacation in sunny Arizona flying drones (here), I am back soliciting ideas from our Merck Genetic & Pharmacogenomics (GpGx) team. This week’s pick riffs off the events at J.P.Morgan 2015, where there were a number of interesting deals made by pharmaceutical companies and genetic companies (see here, here, here).

With all of this interest in human genetics, it raises the question about how genetics can be used to develop new drugs. The first step is to go from “genes to screens”. That is, the first step is to progress from a human genetic variant associated with a clinical trait of interest to an actual drug screen. This week’s article, published in Nature Chemical Biology, describes one example (see here, here).

Summary of the manuscript: Deleterious mutations in the ABHD12 gene cause a rare neuroinflammatory-neurodegenerative disorder named polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and cataract (PHARC, see here). A similar phenotype is observed in ABHD12-deficient mice. ABHD12 is an enzyme degrading lysophosphatidylserine (lyso-PS), a signaling lipid known to regulate macrophage activation. The Nature Chemical Biology study by Kamat and colleagues describes the chemical proteomic identification of a related enzyme, ABHD16A, which synthesizes the terminal step leading to lyso-PS generation.…

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Date posted: May 17, 2013 | Author: | No Comments »

Categories: Drug Discovery Human Genetics

After all, baseball is a metaphor for life.

Bill James developed the “Keltner list” to serve as a series of gut-check questions to test a baseball player’s suitability for the Hall of Fame (see here).  The list comprises 15 questions designed to aid in the thought process, where each question is designed to be relatively easy to answer.  As a subjective method, the Keltner list is not designed to yield an undeniable answer about a player’s worthiness.  Says James: “You can’t total up the score and say that everybody who is at eight or above should be in, or anything like that.”

The Keltner list concept has been adapted to address to serve as a common sense assessment of non-baseball events, including political scandals (see here) and rock bands like Devo (see here).

Here, I try out this concept for genetics and drug discovery.  That is, I ask a series of question designed to answer the question: “Would a drug against the product of this gene be a useful drug?”  I use PCSK9 as one of the best examples (see brief PCSK9 slide deck here).  I also used in on our recent study of CD40 in rheumatoid arthritis, published in PLoS Genetics (see here).…

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Date posted: April 3, 2013 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Immunogenomics

This blog post pertains to the Systems Immunology graduate course at Harvard Medical School (Immunology 306qc; see here), which is led by Drs. Christophe Benoist, Nick Haining and Nir Hacohen.  My lecture is on the role of human genetics as a tool for understanding the human immune system in health and disease.  What follows is an informal description of my lecture.  The slide deck for the lecture can be downloaded here.  Throughout, I have added key references, with links to the manuscripts and other web-based resources embedded within the blog (and also listed at the end).  I highlight five key manuscripts (#1, #2, #3, #4, and #5), which should be reviewed prior to the lecture; the other references, while interesting, are optional.


It is increasingly clear that humans serve as the best model organism for understanding human health and disease.  One reason for this paradigm shift is the lack of fidelity of most animal models to human disease.  For systems immunology, the mouse is a powerful model organism to understand fundamental mechanisms of the immune system.  However, studies in humans are required to understand how these mechanisms can be translated into new biomarkers and drugs.…

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I read with interest a recent publication by Khandpur et al in Science Translational Medicine on NETosis in the pathogenesis of rheumatoid arthritis (download PDF here).  It made me think about “cause vs consequence” in scientific discovery.  That is, how does one determine whether a biological process observed in patients with active disease is a cause of disease rather than a consequence of disease?

In reading the article, I learned about how neutrophils cause tissue damage and promote autoimmunity through the aberrant formation of neutrophil extracellular traps (NETs).  Released via a novel form of cell death called NETosis, NETs consist of a chromatin meshwork decorated with antimicrobial peptides typically present in neutrophil granules.  (Read more about NETs on Wikipedia here.) 

Mendelian randomization is a method of using measured variation in genes of known function to examine the causal effect of a modifiable exposure on disease in non-experimental studies (read more here).  It is a powerful to determine if an observation in patients is causal.  For example, if autoantibodies are pathogenic in RA, then DNA variants that influence the formation of autoantibodies should also be associated with risk of RA.  This is indeed the case, as exemplified by variants in a gene, PADI4, the codes for an enzyme involved in peptide citrullination (see here). …

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