Plenge Lab
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).   The task to invent new drugs is a perfect example of use-inspired, basic-science research!

As the Harvard Business Review article states: “The work in Pasteur’s Quadrant doesn’t exist on road maps. It results in discoveries that upset the current trajectory and can destroy an existing business.

Disruption is fine.  However, there need to be guiding principles that chart a path.

I strongly believe that human genetics has reached an inflection point to help solve, in a new way, the practical problem of inventing new therapies.

As I have stated before (see here), genetics is not the only way – but it is one that is ripe for exploration…today.  This is because there has been an explosion of genotype-phenotype correlations, where genetic variants (whether common or rare) have been linked to clinical phenotypes that are good surrogates for drug efficacy. The concept is based on the idea that humans represent the ideal model organism (#himo) to understand human disease (see Forbes Pharma & Healthcare post tangentially related to this topic here).

So what is the genetic strategy?

This blog highlights one approach: single genes to single targets.  Many of these ideas have also been captured in a review article I published in Nature Reviews Drug Discovery in 2013 (see here).

In brief: Genetic mutations serve as nature’s way to perturb biological targets, akin to pharmacological perturbation.  This puts the winds of human evolution at our backs, which is important given the extraordinary complexity of human physiology. I like to think of human genetic mutations as a way to estimate dose-response curves at the time of target validation.   Human genetics tells you which targets to perturb, how to perturb them therapeutically, and which biomarkers should be used to test target engagement in pre-clinical models.

For drug discovery, the most appealing genes will have the following features: 

• The gene harbors a causal variant that is unequivocally associated with a medical trait that is a good surrogate for drug efficacy

• The biological function of the causal gene and causal variant are known, thereby pointing to a mechanism of action (MOA) that can be mimicked by a therapeutic perturbation

• The gene harbors multiple causal variants of known biological function, thereby enabling the generation of genotype–phenotype dose–response curves

• The gene harbors a loss-of-function allele that protects against disease, or a gain-of-function allele that increases the risk of disease (as it is easier, in general, to develop a drug that acts as an inhibitor)

• The causal variant is associated with an intermediate phenotype that can be used as a biomarker for target engagement, which enables fine-tuning of a drug candidate in pre-clinical models

• The gene target is druggable

• The causal variant is not associated with other phenotypes that may be considered surrogates for adverse drug events

• Corroborating biological data support genetic findings, including MOA of the gene and variant in animal models of disease

In other words, human genetics takes you to the target, provides insight into the MOA for perturbing the target, and provides biomarkers for target engagement to guide the target through pre-clinical studies on the way to first-in-human studies.

For baseball enthusiasts, I point you to a blog that puts this problem in context of Bill James’ “Keltner list” (see here), with a focus on the poster-child for genetics and drug discovery, PCSK9 (see slide deck here).

Idea: If anyone out there wants to try and socialize this Keltner list concept, I would be keen to see a website where genetic targets are vetted via a crowdsource mechanism. For example, anyone could nominate a genetic target, then ask the crowd to vote based on these criteria…and see what happens! I bet something unexpected would result. ]

There is precedence that human genetics can identify drug targets (see here).  In addition to PCSK9, other examples include HMGCR/statins and RANKL/denosumab.  Some examples are very unexpected, including the history behind how human genetics led to the development of finasteride (see History in the Wikipedia link here).

Here is a collection of papers you might want to read to ask: Is this a good drug target? What would we need to do to build a complete biological package for TIDVAL?  The manuscripts, which are all based on human genetic data, can be found here (GPR120/O3FAR1 for obesity and T2D), here (PLS3 and osteoporosis), here (Nav1.9/SCN11A and pain), here (GTF2I and Sjogren’s syndrome), here (PTEN and insulin resistance), here (TREM2 and Alzheimer’s disease), here (SLC30A8 and T2D), here (ATG16L1 and Crohn’s disease), and here/here (CETP and heart disease).  [Hint: I don’t think all of these are good drug targets!]

In conclusion, the US government used Sputnik as a motivating factor to establish DARPA, which eventually led to the invention of the Internet and GPS.  In biopharma today, we are using high attrition rates and decreased productivity in the pharmaceutical industry (see here) as motivating factors to establish a new approach early discovery.  I believe human genetics, which has reached an inflection point due to improved genotype-phenotype maps, is a powerful, disruptive strategy to discover new drug targets.

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