Plenge Lab
Date posted: September 28, 2019 | Author: | No Comments »

Categories: Drug Discovery Embedded Genomics Human Genetics

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

In the Wizard of Oz, Dorothy clicks her heels and hopes for re-entry from her dream world by repeating, “There’s no place like homethere’s no place like home…” I often feel that many in the genetics community look at their human genetics data with the same youthful optimism as Dorothy – clicking their genetic heels and wishing “my genetic discovery will become a drugmy genetic discovery will become a drug…” But without rigor and discipline, such heel-clicking won’t overcome many of the challenges that face drug hunters along the tortuous journey from a genetic idea to a new medicine.

In this blog, I discuss a recent study on the genetics of multiple sclerosis (MS) published in Science (see here). This is a beautiful study that substantially advances the genetic landscape of patients with a devastating disease. However, the study falls short in terms of the application of human genetics to drug discovery. To chart a course for the future, I introduce the concept of mechanism, magnitude and markers (oh my!), which I refer to as the three M’s. …

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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).…

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Date posted: February 13, 2016 | Author: | No Comments »

Categories: Drug Discovery Embedded Genomics Human Genetics Precision Medicine

A study published last week in Science described a large-scale genetic association study of Neandertal-derived alleles with clinical phenotypes from electronic health records (EHRs). Here, I focus less on the Neandertal aspect of the study – which to me is really just a gimmick and not medically relevant – and more on the ability to use EHR data for unbiased association studies against a large number of clinical traits captured in real-world datasets. I also provide some thoughts on how this same approach could be used for 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.]

The study used clinical data from the Electronic Medical Records and Genomics (eMERGE) Network, a consortium that unites EHR systems linked to patient genetic data from nine sites across the United States. The clinical data was primarily from ICD9 billing codes, an imperfect but decent way to capture clinical data from EHRs. In total, a set of 28,416 adults of European ancestry from across the eMERGE sites had both genotype data and sufficient EHR data to define clinical phenotypes (n=13,686 in the Discovery set; n=14,730 in the replication set).…

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

Categories: Drug Discovery Human Genetics Immunogenomics Precision Medicine

Many of you are probably fully aware of how immuno-oncology is changing cancer treatment. Ken Burns highlighted immunotherapy in his recent PBS series, “Cancer: The Emperor of All Maladies” (video link here). Forbes’ Matthew Herper, BBC and others have written extensively about it, too (here, here). More recently, Genome Magazine had a feature article on the history of immunotherapy (here). As the article states: “The promise of immunotherapy is startling in its simplicity: With a little help from cancer doctors, the patients will cure themselves.

The key word here is “cure”. Cure!

The purpose of this blog is two-fold: (1) introduce geneticists and genomicists to cancer immunotherapy, if they have not thought about it before, and (2) highlight a recent Science publication by Elaine Mardis, Gerald Linette, and colleagues at WashU (here), with an accompanying News & Views article in Nature (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.]

Cancer immunotherapy is really cool! As a former practicing rheumatologist at Brigham and Women’s Hospital, I had thought about the role of neoantigens in autoimmunity for many years.…

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