Last week Alnylam reported positive news on Phase 3 outcomes for their RNA interference (RNAi) therapy to treat patients with a rare genetic cause of amyloidosis with polyneuropathy (see here). I tweeted the following:
The 20-year journey from scientific discovery to positive Phase 3 clinical trial data got me thinking about other novel therapeutic modalities. Was twenty years a long time or typical for an innovative therapeutic modality? Where are other promising modalities on their journey to regulatory approval? Is the biopharmaceutical industry on the cusp of a series of innovative modalities that could change the therapeutic landscape for patients? How will these new modalities improve our ability to test therapeutic hypotheses?
[Disclaimer: I am an employee of Celgene. The views expressed here are my own.]
To explore these questions, I decided to review different novel therapeutic modalities, which I am defining as those other than small molecules, protein therapeutics (e.g., insulin) and traditional vaccines. This decision was practical, as the amount of literature in these modalities is expansive.
For each new modality, I asked whether a drug has been approved by either a European or US regulatory agency (EMA and FDA, respectively). If a drug has been approved, I reviewed the time from seminal scientific discovery (which sometimes is clear, sometimes is not) to the approved therapy.…
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.
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.
I recently listened to a TED Radio Hour podcast on failure (link here). Casey Gerald reminded listeners that while his biographical narrative is impressive (here), there have been many failures along the way.
This got me thinking…why don’t more people write their personal biographies in such a way that highlights their successes and failures? I have not seen one, and LinkedIn certainly does not encourage us to log our failures publicly. (Maybe an entrepreneur should start a site called LinkedOut, where you endorse people for failures and bios must be written with failures included!)
So I thought I would give it a try.
I will start with my conventional “success” bio (which can also be found here) to provide context. Then, I will provide my new “failure” bio (also here). At the end, I provide a brief “lessons learned” on how failures have shaped my professional life. I conclude with a shout out to Charles Darwin, one of history’s most famous observer of failure in nature.
[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.]
Here is my conventional “successful” professional biography.…
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.…
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). …
Are the same standards applied to genetic and non-genetic tests in clinical medicine? In a review by Munir Pirmohamed and Dyfrig Hughes (download PDFhere), the authors “strongly argue that the slow progress in the implementation of pharmacogenetic (and indeed other genetic) tests can partly be explained by the fact that different criteria are applied when considering genetic testing compared with non-genetic diagnostic tests.” They provide a few compelling examples:
There is no regulatory requirement to undertake clinical trials to show that the dosing recommendations for patients with, for example, renal impairment are equivalent in terms of clinical outcomes to those for patients with normal renal function. Indeed, such a stipulation would be impractical and costly, and would never be done during the drug development process, potentially disadvantaging vulnerable patient populations.
Atomoxetine, a drug widely used for attention deficit hyperactivity disorder, is metabolized in the liver by CYP2D6. The SmPC for atomoxetine states that the dose should be reduced by 50% in patients with hepatic impairment (Child-Pugh class B), as drug exposure goes up by twofold. It is also known that drug exposure is increased by a similar amount in CYP2D6 PMs; however, although the SmPC for atomoxetine mentions the effect of CYP2D6 polymorphisms, it does not mandate testing for their presence.…