CERSI Collaborators: Russ Altman, MD, PhD, Snehit Prabhu, PhD, Dmitri Petrov, PhD (Stanford), Natalia Khuri, PhD (Stanford & UCSF)
FDA Collaborators: Elaine Johanson
Project Start Date: September 2015
Regulatory Science Challenge
In 2015, President Obama announced the Precision Medicine Initiative (PMI), which calls for advancing the field of precision medicine, also referred to as personalized medicine, to tailor disease prevention and treatment to an individual’s characteristics, including their genetic makeup, environment and lifestyle. As part of the PMI, FDA must prepare for the task of evaluating many new diagnostics and therapies that will be based on individual characteristics. In particular, there is great excitement about the use of individual genome sequences to determine disease risk and select medications. The FDA has created an open portal called precisionFDA (https://precision.fda.gov/) that will allow scientists to collaborate in comparing different approaches for analyzing this large volume of genomic data. With success, precisionFDA will provide information to help FDA make informed decisions about medical products and devices that may rely on the use of this data and ensure that the PMI benefits patients.
Project Description & Goals
The UCSF-Stanford CERSI has three projects focused on building the capabilities of the FDA in genomic analysis by:
1. Creating a course that explains the challenges of analyzing genome sequences, introduces the precisionFDA portal, and provides exercises for researchers to understand how they can use the portal to understand current best practices and help improve them. Events are being hosted to encourage the community to contribute their software and data to the precisionFDA portal so that it becomes a rich environment for testing different strategies for analyzing genomes.
2. Studying the importance of ancestry in interpreting genomic tests. People of different ancestral backgrounds may have differences in their DNA that are critical to understand in order to appropriately interpret diagnostic tests and administer therapies. Researchers are working to characterize the ways that different ancestral groups are similar and different and will generate methods to validate diagnostic tests to be sure that they work for all patients, regardless of their ancestry.
3. Studying the inherent errors in different sequencing technologies, and their consistency and reproducibility. Researchers are analyzing standardized genomes using several different technologies and then analyzing the results to see where they agree and disagree. They are working on how to resolve disagreements so that the most accurate possible genetic information is used to make decisions about diagnosis and treatment.
A research roadmap for next-generation sequencing informatics. Altman RB, Prabhu S, Sidow A, Zook JM, Goldfeder R, Litwack D, Ashley E, Asimenos G, Bustamante CD, Donigan K, Giacomini KM, Johansen E, Khuri N, Lee E, Liang XS, Salit M, Serang O, Tezak Z, Wall DP, Mansfield E, Kass-Hout T. Sci Transl Med. 2016 Apr 20; 8 (335).