Plenge Lab
Date posted: April 13, 2018 | Author: | No Comments »

Categories: Drug Discovery Embedded Genomics Human Genetics

[Disclaimer: I am an employee of Celgene. The views reported here are my own.]

Drug research and development (R&D) is a slow, arduous process. As readers of this blog know, it takes >10 years and upwards of $2.5 billion dollars to bring new therapies to patients in need. An aspiration of the biopharmaceutical ecosystem is to shorten cycle times and increase probability of success, thereby dramatically improving the efficiency of R&D.

One potential solution is to use human genetics to pick targets, understand molecular mechanism, select pharmacodynamics biomarkers, and identify patients most likely to respond to treatment (see Science Translational Medicine article here). While intuitively appealing and supported by retrospective analyses (here), it is not yet routinely implemented in most R&D organizations (although see Amgen blog here; Regeneron study below). Indeed, human genetics often represents an inconvenient path to a new therapeutic, as it takes substantial effort to understand the molecular mechanism responsible for genetic risk and many such targets are difficult to drug.

But what if…

…it were possible to go from gene variant to therapeutic hypothesis instantly via in silico analysis;

…it were possible to select an “off-the shelf” therapeutic molecule that recapitulates a human genetic mutation, and take this molecule into humans almost immediately, with limited pre-clinical testing;

…it were possible to select pharmacodynamics (PD) biomarkers that capture underlying human physiology, and to measure those PD biomarkers in a small, human proof-of-mechanism clinical trial;

…it were possible to model the magnitude of effect of a therapeutic intervention relative to existing standard-of-care, and thereby to estimate the commercial market of an as-yet-to-be-approved drug?…

Read full article...

Date posted: December 19, 2017 | Author: | No Comments »

Categories: Drug Discovery Embedded Genomics Human Genetics Precision Medicine

A new genetics initiative was announced today: the creation of FinnGen (press release here). FinnGen’s goal is to generate sequence and GWAS data on up to 500,000 individuals with linked clinical data and consented for recall. There are many applications for such a resource, including drug discovery and development. In this blog, I want to first describe the application of PheWAS for drug discovery and development, and then introduce FinnGen as a new PheWAS resource (see FinnGen slide deck here).

[Disclaimer: I am an employee of Celgene. The views expressed here are my own.]


PheWAS turns GWAS on its head. While GWAS tests millions of genetic variants for association to a single trait, PheWAS does the opposite: tests hundreds (if not thousands) of traits for association with a single genetic variant. This approach is primarily relevant for those genetic variants with an unambiguous functional consequence – for example, a variant associated with disease risk or a variant that completely abrogates gene function. There are useful online resources (see here), as well as several nice recent reviews by Josh Denny and colleagues, which provide additional background on PheWAS (see here, here).

Work that originated from my academic lab represents the first example of PheWAS for drug discovery – in particular, how to use PheWAS to predict on-target adverse drug events (ADEs) and to select indications for clinical trials (see 2015 PLoS One publication here).…

Read full article...

Date posted: April 30, 2017 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Immunogenomics

A recent study in the New England Journal of Medicine provides genetic support for a pharmacologically validated target, BAFF, in the treatment of systemic lupus erythematosus.  But can human genetics also be used to estimate the target dose and a therapeutic window?

As readers of know, I am constantly on the lookout for published studies that provide insight into the utility of human genetics for drug discovery and development.  This past week there was a great post from Francis Collins on the role of the NIH in the discovery (in part via human genetics) and development of tofacitinib (see here), anakinra and potentially novel targets (e.g., STING) for inflammatory diseases (here).  Nature Reviews Drug Discovery published a News & Analysis on PCSK9 as a “fertile testing ground for new drug modalities including long-acting RNA interference drugs, vaccines against self-antigens, CRISPR therapeutics and small molecules that control ribosomal activity” (here).  New York City released information about a new public health initiative, The NYC Macroscope, which will use electronic health records (EHRs) to track conditions managed by primary care practices that are important to public health..and one day may be linked to genetic data for discovery research (that is me just speculating).…

Read full article...

Date posted: March 31, 2017 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Immunogenomics Precision Medicine

As readers of my blog know, I am a strong supporter of a disciplined R&D model that focuses on: picking targets based on causal human biology (e.g., genetics); developing molecules that therapeutically recapitulate causal human biology; deploying pharmacodynamic biomarkers that also recapitulate causal human biology; and conducting small clinical proof-of-concept studies to quickly test therapeutic hypotheses (see Figure below).  As such, I am constantly on the look-out for literature or news reports to support / refute this model.  Each week, I cryptically tweet these reports, and occasionally – like this week – I have the time and energy to write-up the reports in a coherent framework.

Of course, this model is not so easy to follow in the real-world as has been pointed out nicely by Derek Lowe and others (see here).  A nice blog this week by Keith Robison (Warp Drive Bio) highlights why drug R&D is so hard.

Here are the studies or news reports from this week that support this model. 

(1) Picking targets based on causal human biology:  I am a proponent of an “allelic series” model for target identification.  Here are a couple of published reports that fit with this model.

Read full article...

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).

Read full article...

Date posted: March 15, 2017 | Author: | No Comments »

Categories: Drug Discovery Human Genetics

There were so many good articles and news reports this week on genetics/genomics and drug discovery & development.  A few examples include: article in Nature Communications on gene therapy via CRISPR/Cas9 for retinitis pigments (here); a partnership between Editas and Allergan (Matthew Herper story here); Nature Reviews Genetics article by Khera and Kathiresan on genetics of coronary heart disease (here); Genome Magazine article on the importance of pharmacogenetics across ethnic groups to prevent severe adverse events (here); and a victory for pre-prints in challenging the statistical robustness of a publication in Nature Genetics (here).

I decided to focus on a study that provides a mechanistic link between a genetic mutation and a therapeutic hypothesis in Parkinson’s disease. The reason I chose this article is that it highlights the challenges of going from a robust genetic association to a biology hypothesis, and ultimately how to gain confidence in a therapeutic hypothesis with pre-clinical models.  As you will see at the end, a clinical trial is now underway to test the therapeutic hypothesis in humans.

The manuscript was published March 7 in PNAS, “Glucosylceramide synthase inhibition alleviates aberrations in synucleinopathy models” (see here).

Read full article...

Date posted: October 5, 2016 | Author: | No Comments »

Categories: Drug Discovery Human Genetics

I have many fears, both professional and personal. When I decided to leave academics for a job in industry in 2013, my biggest fear about making the transition was scientific. In my mind, I had a model of how human genetics might transform drug discovery and development. There were anecdotes (e.g., PCSK9 inhibitors) and a few systematic studies in specific diseases (e.g., genetics of rheumatoid arthritis), but there were many holes to the model. Over the last couple of years, additional anecdotes and systematic analyses have emerged (e.g., Matt Nelson, et al. Nature Genetics), which helps to soothe my fears…but I still have concerns.

[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.]

As I have blogged about previously, I see two primary routes to go from human genetics to new drug discovery programs (see here, here). The first requires that there are genes with a series of disease-associated alleles with a range of biological effects, ideally from gain- to loss-of-function (allelic series model). The second requires disease-associated genes to aggregate within specific biological pathways, which can then be turned into assays for disease-relevant pathway-based screens such as phenotypic screens.…

Read full article...

Date posted: June 3, 2016 | Author: | No Comments »

Categories: Drug Discovery Human Genetics


One of the biggest challenges of drug discovery is to determine which targets, when perturbed, will have an acceptable efficacy-safety therapeutic window in patients. In fact, the success rate at choosing the right target and developing a safe and effective drug is quite low: less than 10% of drugs that enter Phase I are approved by regulatory authorities (see recent Nature Reviews Drug Discovery article here, Derek Lowe blog here). Most of the failures in Phase II and III are due to lack of efficacy or unexpected toxicity.

Human genetics offers one potential solution to identify new drug targets with an acceptable therapeutic window. A study published this week in Science Translational Medicine (STM) provides genetics support for an established therapeutic target in type 2 diabetes (T2D), glucagon-like peptide-1 receptor, GLP1R (link to STM article here).  What is surprising, however, is that human genetics suggests that GLP1R agonists may also protect from coronary heart disease (CHD).

[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.]

There are three points that I want to make in this blog. First, the STM study provides general support for the model that human genetics is useful to predict efficacy & safety in drug discovery.…

Read full article...

It has been a good week for human genetics, with high-profile studies published in Science (here) and NEJM (here, here, here), and a summit at the White House on Precision Medicine. Here, I summarize the published studies and put them in context for drug discovery. But first, I want to briefly detour into a story about the Wright Brothers.

[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.]

In 1900, Wilbur and Orville Wright first began experiments with their flying machine. They defined three problems for manned flight: power, wing structure and control. As described beautifully in David McCullough’s book (review here), the brothers focused on the latter, control, which when sufficiently solved led to the first manned flight in 1903. Within ten years of solving the “flying problem”, aviation technology progressed to the point that manned flights were routine.

By analogy, I would argue that there are three key challenges for drug discovery: targets, biomarkers and clinical proof-of-concept studies. The key problem to solve is target selection. Today, we do not know enough about causal human biology to select targets, and as a consequence we have a crisis in cost (drugs are too expensive to develop because of failures at the most costly stage, late development) and innovation (for those drugs that work, there is insufficient differentiation from standard-of-care treatments to change health care outcomes).…

Read full article...

The primary purpose of this blog is to recruit clinical scientists into our new Translational Medicine department at Merck (job postings at the end). However, I hope that the content goes beyond a marketing trick and provides substance as to why translational medicine is crucial in drug discovery and development. Moreover, I have embedded recent examples of translational medicine in action, so read on!

[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.]

There is a strong need to recruit clinical scientists into an ecosystem to develop innovative therapies that make a genuine difference in patients. This ecosystem requires those willing to toil away at fundamental biological problems; those committed to converting biological observations into testable therapeutic hypotheses in humans; and those who develop therapies and gain approval from regulatory agencies throughout the world.   The first step is largely done in academic settings, and the other two steps largely done in the biopharmaceutical industry…although I am sure there are many who would disagree with this gross generalization!

The term “Translational Medicine” has been broadly used to describe the second step, thereby bridging the Valley of Death between the first and third steps.…

Read full article...

I admit upfront that this is a self-serving blog, as it promotes a manuscript for which I was directly involved. But I do think it represents a very nice example of the role of human genetics for drug discovery. The concept, which I have discussed before (including my last blog), is that there is a four-step process for progressing from a human genetic discovery to a new target for a drug screen. A slide deck describing these steps and applying them to the findings from the PLoS One manuscript can be found here, which I hope is valuable for those interested in the topic of genetics and drug discovery.

[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. However, the PLoS One study was performed while I was still in academics at BWH/Harvard/Broad.]

Before I provide a summary of the study, I would like to highlight a few recent news stories that highlight that the world thinks this type of information is valuable. First, the state of California is investing US $3-million in a precision medicine project that links genetics and medical records to develop new therapies and diagnostics (here, here).…

Read full article...

There was an eruption in Iceland last week. No, this was not another volcanic eruption. Rather, there was a seismic release of human genetic data that provides a glimpse into the future of drug discovery. The studies were published in Nature Genetics (the issue’s Table of Contents can be found here), with insightful commentary from Carl Zimmer / New York Times (here), Matthew Herper / Forbes (here), and others (here, here).

[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.]

As I have commented before, human genetics represent a very powerful approach to identify new drug targets (see here, here). I have articulated a 4-step process (see slide #5 from this deck): (1) select a phenotype that is relevant for drug discovery; (2) identify a series of genetic variants (or “alleles”) that is associated with the phenotype; (3) assess the biological function of phenotype-associated alleles; and (4) determine if those same alleles are associated with other phenotypes that may be considered adverse drug events.

There is an important assumption about this model: genes with an “allelic series” will be identified from large-scale genetic studies, and these phenotype-associated alleles will serve as an estimate of function-phenotype dose-response curves.…

Read full article...

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.…

Read full article...

Date posted: December 11, 2014 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Immunogenomics

Welcome to this second blog post on genetics/genomics for drug discovery! So far, we are 2 for 2. That is, this is the second week in a row where we have reviewed the literature for interesting journal articles and written a blog on why the study is relevant for drug discovery. I say “we”, because this week I asked for input from our Merck Genetic & Pharmacogenomics (GpGx) team. We received a number of interesting submissions from GpGx team members, as summarized at the end of the blog.

This week’s article uses antisense as therapeutic proof-of-concept in humans for a genetic target…again! This story is reminiscent of last week’s post on APOC3 (see here).

Factor XI Antisense Oligonucleotide for Prevention of Venous Thrombosis, New England Journal of Medicine (December 2014).

Summary of the manuscript: While patients with congenital Factor XI deficiency have a reduced risk of venous thromboembolism (VTE), it is unknown whether therapeutic modulation of Factor XI will prevent venous thromboembolism without increasing the risk of bleeding. In this open-label, parallel-group study, 300 patients who were undergoing elective primary unilateral total knee arthroplasty were randomly assigned to receive one of two doses of FXI-ASO (200 mg or 300 mg) or 40 mg of enoxaparin once daily.…

Read full article...

Date posted: November 12, 2014 | Author: | No Comments »

Categories: Drug Discovery Embedded Genomics Human Genetics Precision Medicine

I have come across three reports in the last few days that help me think about the question: How many genomes is enough?  My conclusion – we need a lot!  Here are some thoughts and objective data that support this conclusion.

(1) Clinical sequencing for rare disease – JAMA reported compelling evidence that exome sequencing identified a molecular diagnosis for patients (Editorial here).  One study investigated 2000 consecutive patients who had exome sequencing at one academic medical center over 2 years (here).  Another study investigated 814 consecutive pediatric patients over 2.5 years (here).  Both groups report that ~25% of patients were “solved” by exome sequencing.  All patients had a rare clinical presentation that strongly suggested a genetic etiology.

(2) Inactivating NPC1L1 mutations protect from coronary heart diease – NEJM reported an exome sequencing study in ~22,000 case-control samples to search for coronary heart disease (CHD) genes, with follow-up of a specific inactivating mutation (p.Arg406X in the gene NPC1L1) in ~91,000 case-control samples (here).  The data suggest that naturally occurring mutations that disrupt NPC1L1 function are associated with reduced LDL cholesterol levels and reduced risk of CHD.  The statistics were not overwhelming despite the large sample size (P=0.008, OR=0.47). …

Read full article...

Date posted: August 16, 2014 | Author: | No Comments »

Categories: Drug Discovery Human Genetics

Question: What can we learn from Sputnik (see here), DARPA (see here) and disruptive innovation (see here) to invent new drugs?

Answer: The best way to prevent surprise is to create it. And if you don’t create the surprise, someone else will. (This is a cryptic answer, I know, but I hope the answer will become clearer by the end of the blog.)

My previous blogs highlighted (1) the pressing need to match an innovative R&D culture with an innovative R&D strategy rooted in basic science (see here), and (2) the importance of phenotype in target ID and validation (TIDVAL) efforts anchored in human genetics (see here).  Now, I want to flesh out more of the scientific strategy around human genetics – with a focus on single genes and single drug targets.

To start, I want to frame the problem using an unexpected source of innovation: the US government.

There is an interesting article in Harvard Business Review on DARPA and “Pasteur’s Quadrant” – use-inspired, basic-science research (see here and here).  This theme is critically important for drug discovery, as the biopharma industry has a profound responsibility to identify new targets with increased probability-of-success and unambiguous promotable advantage (see here).   …

Read full article...

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).…

Read full article...

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.…

Read full article...

Date posted: February 8, 2013 | Author: | No Comments »

Categories: Drug Discovery Precision Medicine

Genetics can guide the first phase of drug development (identifying drug targets, see here ) as well as late phase clinical trials (e.g., patient segmentation for response/non-responder status, see here ). But is there a convergence between the two areas, or pharmaco-convergence (a term I just made up!)? And are there advantages to a program anchored at both ends in human genetics?


Consider the following two hypothetical examples.

(1) Human genetics identifies loss-of-function (LOF) mutations that protect from disease. The same LOF mutation is associated with an intermediate biomarker, but is not associated with other phenotypes that might be considered adverse drug events. A drug is developed that mimics the effect of the mutation; that is, a drug is developed that inhibits the protein product of the gene. In early mechanistic studies, the drug is shown to influence the intermediate biomarker in a way that is consistent to that predicted by the LOF-protective mutations. Further, because functional studies of the LOF-protective mutations provide insight into relevant biological pathways in humans (e.g., a gene expression signature that correlates with mutation carrier status), additional information is known about genomic signatures of those who carry the LOF-protective mutations (which mimics drug exposure) compared to those who do not carry the LOF-protective mutations (which mimics those who are not exposed to drug).…

Read full article...