Plenge Lab
Date posted: April 23, 2017 | Author: | No Comments »

Categories: Drug Discovery Embedded Genomics Human Genetics

In response to an original research article published in Nature by Sekar Kathiresan and colleagues (see here), I penned a News & Views piece for Nature (here), a blog for the Timmerman Report (here, here), and a podcast for BBC Inside Science (here). An important theme for drug discovery & development is that human knockouts can rule-in and to rule-out drug targets.  For human knock-out data, the key concept is to understand the effect of maximum genetic perturbation on human physiology.

  1. Rule-in drug targets: As has been described by Matt Nelson and colleagues from GlaxoSmithKline (see 2015 Nature Genetics), and David Cook and colleagues from AstraZeneca (see 2014 Nature Reviews Drug Discovery), therapeutic molecules developed against targets with human genetic data are more likely to lead to regulatory approval than those without.  PCSK9 represents the poster child for human genetic knockouts in drug discovery & development (see my blog here).  But there are many other examples, too.
  1. Rule-out drug targets: But human genetics can also rule-out drug targets or mechanisms that are nominated through animal models, human epidemiology or other approaches.  A prominent example is related to raising HDL cholesterol, the so-called “good cholesterol”.

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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.

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Date posted: April 24, 2016 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Immunogenomics

Inevitably when I post a blog on “human biology” I get a series of comments about the importance of non-human model organisms in drug discovery and development. My position is clear: pick targets based on causal human biology, and then use whatever means necessary to advance a drug discovery program to the clinic.

Very often, non-human model organisms are the “whatever means necessary” to understand mechanism of action. For example, while human genetic studies identified PCSK9 as an important regulator of LDL cholesterol, mouse studies were critical to understand that PCSK9 acts via binding to LDL receptor (LDLR) on the surface of cells (see here). As a consequence, therapeutic antibodies were designed to block circulating PCSK9 from the blood and increase LDLR-mediated removal of circulating LDL (and hopefully to protect from cardiovascular disease).

Moreover, non-human animal models are necessary to understand in vivo pharmacology and safety of therapeutic molecules before advancing into human clinical trials.

Beyond drug discovery, of course, studies from non-human animal models provide fundamental biological insights. Without studies of prokaryotic organisms, for example, we would not have powerful genome-editing tools such as CRISPR-Cas9. Without decades of work on mouse embryonic stem cells, we would not have human induced pluripotent stem cells (iPSCs).…

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

Categories: Drug Discovery

It is not uncommon that I am asked the following question during public talks: “Does innovation happen in large pharmaceutical companies?” Sometimes, the question is just a critical comment, disguised as a question: “Large pharma does not innovate, they just conduct clinical trials and drive up the cost of drugs. Right?” Other times the questions are more thoughtful: “As an academic, I don’t see what happens in industry. Can you describe examples of innovation driven out of large pharma?

[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.]

At the risk of sounding defensive, here are some answers to the “pharma innovation” question. I know there are many more, and I invite readers to share their examples. Admittedly, the examples are biased towards examples at Merck, but that is just because I know these examples better.

First, the past couple of weeks have been particularly good for industry scientists. These recent examples provide objective evidence to answer the pharma innovation question.

(a) 2015 Nobel Prize in Physiology or Medicine. Former Merck scientist Dr. William Campbell was awarded the Nobel Prize for the discovery of an antiparasitic agent used to treat river blindness in places like Latin America, Africa and Yemen.…

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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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