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BIO Investor Forum Session Recap: Precision Medicine: Leveraging National Genomic Databases for Therapy Development (U.S., UK, Iceland)

October 20, 2015
As the price point for full genome analysis falls through the $1,000 per person milestone, national efforts are ramping up for large studies that should enable much more personalized therapies.  This data should accelerate drug development by clarifying genetic targets and the most appropriate patient sub-groups for clinical trials.

At the 14th Annual  BIO Investors Forum in San Francisco, a panel of precision medicine experts came together to share their perspectives on the current state and future trends of the precision medicine industry that investors should be aware of.

The panel was moderated by Esteban G. Burchard, Professor of Medicine and Bioengineering and Therapeutic Sciences, University of California, San Francisco; and member of NIH Precision Medicine Initiative Working Group. The panelists were:

Burchard started out by talking about how 95% of medical research has been done using patients with European ancestry, which means that only 5% of the available genes and biomarkers available out there are being explored. This not only means missed opportunities for therapeutic discoveries, but also can create poorer health outcomes for non-European patients. He gave the example of Pravix, a heart drug that was launched in Hawaii, which over half of Asians do not metabolize well, putting their lives at risk. He then opened the discussion by asking the panelists to introduce themselves and their connection to precision medicine.

May mentioned that a lot of data is now being collected, and the challenge is to probe functionally to understand underlying mechanisms. Sklar mentioned that she would like to see more research applied to brain disorders to bring the benefits of personalized medicines to psychiatric patients. Wish mentioned wanting to collect data from 100,000 people in Newfoundland to support drug discoveries, and pointed to several characteristics of why Newfoundland is amenable to this approach, such as the amount of healthcare data the government tracks, and the number of population isolates throughout its history. Scholz mentioned the similarity between the work his company does and the work on CAR-T cells, except his company makes the cells build instead of kill things. His perspective was that patient-to-patient variability trumps most other variables. Thorsmarason discussed how his company worked in many countries around the world (China, United Kingdom, Qatar, United States), and can help identify the responders and nonresponders to drugs through analysis of large amounts of biologic data.

A key question that Burchard put to the panelist was where the investment and scientific communities should be focusing their attention in order to get the biggest bang for their buck. May suggested a systematic attempt to follow up on data that’s already been collected, which can allow us to look at variations within clinical data itself. Sklar felt that precision medicine should be used to increase our understanding of how genetics influence the brain, as there are many psychiatric conditions that could benefit greatly from increased treatment options.

The panel also discussed how genes play out differently for different ethnic groups. If you have enough data from different ethnic groups, you can better understand how genetic factors work. Sklar felt it was important to situate biobanks in diverse population areas for this reason.  Burchard pointed out that the strength of looking at founder populations is identifying a gene, but next step is “taking it to the max” by understanding the functional mechanisms at play, and creating treatments from this. Wish advocated the idea of leveraging complex datasets and modern analytics to increase our understanding of this, and bring benefits to lots of areas, such as colorectal cancers. He also pointed out the importance of engagement with patient groups, policy makers, and other stakeholders to effectively collect, analyze, and utilize data from diverse groups. Smarason pointed out that getting access to patients is sensitive, and you have to be thoughtful and ethical in your approach.

One of the audience members thought it seemed counterintuitive to go bigger and bigger in your approach, and asked “Wouldn’t it be better to start small and go bigger?” Sklar responded by saying that starting small and going bigger only works well if you have models already to test. When dealing with complex disorders, it is hard to predict who to hone in on. In the past, we have use pharmacological responses to generate hypothesis to test, and this limited our effectiveness.

Burchard wrapped up the panel with an analogy for the investors in the audience: the current approach of using a non-diverse patient group with 95% Euro-based ancestry is like looking for oil, and only looking at 5% of the earth for places to drill. According to Burchard, we are missing tremendous opportunities to identify new drugs.  Social justice benefits aside, he argues, doing so just makes good financial sense.