In my previous blog series I talked about why genetics is important in drug discovery: human genetics takes you to a target, informs on mechanism of action (MOA) for therapeutic perturbation, provides guidance for pre-clinical assays of target engagement, and facilitates indication selection for clinical trials.
Here, I provide an overview of a new blog series on how genetics influences decision-making during drug discovery. The key principle: human genetics establishes a disciplined mindset and a firm foundation – anchoring points – for advancing targets through the complicated process of drug discovery. [For those less familiar with drug discovery, the end of this blog provides a brief primer on the stages of drug discovery.]
I highlight three areas: establishing a balanced portfolio, identifying targets with novel MOA, and creating a framework for objective decision-making. In subsequent posts, I will focus primarily on how human genetics informs on the latter (decision-making), with blogs pertaining to designing assays for screens and target engagement, utilizing pre-clinical animal models, predicting on-target adverse drug events, and selecting indications for clinical trials.
1. Establish a balanced portfolio
Whether in academic research, a small biotech company (see here) or a large pharmaceutical company (such as Merck, where I work), a balanced portfolio of projects is very important.…
In this post I will build on previous blogs (here, here, here) about genetics for target ID and validation (TIDVAL). Here, I argue that new targets with unambiguous promotable advantage will emerge from studies that focus on genetic pathways rather than single genes.
This is not meant to contradict my previous post about the importance of genetic studies of single genes to identify new targets. However, there are important assumptions about the single gene “allelic series” approach that remain unknown, which ultimately may limit its application. In particular, how many genes exist in the human genome have a series of disease-associated alleles? There are enough examples today to keep biopharma busy. Moreover, I am quite confident that with deep sequencing in extremely large sample sizes (>100,000 patients) such genes will be discovered (see PNAS article by Eric Lander here). Given the explosion of efforts such as Genomics England, Sequencing Initiative Suomi (SISu) in Finland, Geisinger Health Systems, and Accelerating Medicines Partnership, I am sure that more detailed genotype-phenotype maps will be generated in the near future.
[Note: Sisu is a Finnish word meaning determination, bravery, and resilience; it is about taking action against the odds and displaying courage and resoluteness in the face of adversity. …
A key learning from my time in academia was the value of collaborations. Much of my most enjoyable and productive research was conducted in collaboration with fellow scientists across the globe.
I am pleased to report that industry is no different. After one year working for Merck, I have found that in addition to collaborations across the company ties with external scientific experts focused on advancing programs of interest are actively encouraged.
It is heartening to see how some recent progress in several notable drug development programs is leading to increased excitement around the application of human genetics in identifying human drug targets. As I have previously noted, human genetics can also provide insights to identifying pathways enriched for approved drugs (see Nature article here), which indicates that novel pathways may provide an important foundation for novel drug discovery programs. Indeed, the use of pathway-based approaches, including phenotypic screens, can provide a powerful way to make complex genetic pathways actionable for drug discovery.
Today, I am excited to note that Merck has launched a Merck Innovation Network (MINt) Request for Proposals to identify collaborations with academic scientists to evaluate genetic targets or genetic pathways for their potential to become drug discovery programs. …
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). …
1.The observable physical or biochemical characteristics of an organism, as determined by both genetic makeup and environmental influences.
2. An individual or group of organisms exhibiting a particular phenotype.
There are many different phenotypes: strength in the face of adversity (see here); self-reflection in a time of uncertainty (see here); and creativity amidst a sea of sameness (see here).
Phenotypes also refer to disease states such as risk of disease, response to therapy, a quantitative biomarker of medical relevance, or a physical trait such as height (as in the figure above).
For drug discovery, I have put forth the premise that human genetics is a useful tool to uncover novel drug targets that are likely to have unambiguous promotable advantage (see here). The starting point in a genetic study is to pick the right phenotype, one that is an appropriate surrogate for drug efficacy.
And phenotype matters!
Two illustrative examples are the autoimmune diseases type 1 diabetes and rheumatoid arthritis. In type 1 diabetes the immune system destroys the pancreas, thereby preventing insulin secretion and the control of blood glucose levels.
Human genetics has identified many alleles associated with the risk of type 1 diabetes, nearly all of which act on the immune system (see here). …
The key is to find targets with novel mechanism of action (MOA) and an increased probability of success to differentiate in the clinic.
The pharmaceutical industry is in desperate need of new therapies with “unambiguous promotable advantage” that address unmet clinical need (see here, here and here). Of course, this is a laudable goal in drug development. In fact, given the current health care climate, we have no other choice (see here). If we are to have a sustainable industry, we must change the way we do discovery science. According to the Bernstein Report on BioBusiness: “Differentiation or Bust: Drug companies must start creating the case for value differentiation in discovery and then steadily build a body of evidence throughout the product development process.”
This means that dedicated drug hunters have a steep challenge ahead: to identify targets with novel mechanisms of action that have an increased probability to differentiate in the clinic. This will take creativity, hard work and innovation.
There is a lot written about “innovation”. [See here for a collection of articles from the HBR Insight Center; you can test your “innovation quotient” here.] Most comments about innovation involve creating a climate of risk taking balanced with accountability. …
