By Clinical Informatics News Staff

May 19, 2016 | Taha A. Kass-Hout, FDA’s Chief Health Informatics Officer (CHIO) and Director of FDA’s Office of Health Informatics, and colleagues outline the precisionFDA Challenges today at FDA’s blog, FDAVoice.

PrecisionFDA was conceived to help the Agency better understand how accurate computational pipelines really are at interpreting genetic data. “The ultimate goal of precisionFDA is to foster innovation and develop regulatory science around NGS tests, which are essential to achieving the promise of President Obama’s Precision Medicine Initiative,” Kass-Hout says in the blog.

It’s an important and daunting task, but Kass-Hout already has a track record for launching tricky and important programs. In 2014, he spearheaded openFDA, a web portal designed to make it easier for the public to access and search through medical data already collected by the agency.

FDA brought the precisionFDA platform online in December, and the platform so impressed our judges, that we recognized the effort this year as a Bio-IT World Best Practices Award winner.

Six months after its launch, precisionFDA is wrapping up its second open challenge. The first, the Consistency Challenge, aimed to test the accuracy and reproducibility of some of the most basic software tools used in genetic research

“Participants were given two datasets of whole genome sequences from a known human sample, sequenced at two different sites and generously donated to precisionFDA by Garvan Institute of Medical Research and Human Longevity, Inc. Challenge participants were instructed to use the informatics pipeline (software) of their choice to identify genetic variants and check for consistency between results in the provided datasets,” the blog explains.

Winners of the Consistency Challenge will be announced next week.

The second precisionFDA challenge is ongoing: the Truth Challenge closes on May 26, 2016. Designed in collaboration with the Genome in a Bottle consortium and the Global Alliance for Genomics and Health, the challenge calls for participants to identify genetic variants in one known and one unknown sample dataset.

“The goal is to see how close they come to the truth when analyzing data from a human sample with variant results unknown to them, which we will reveal at the end of the challenge. An exciting characteristic of this challenge is that the Genome in a Bottle consortium will release for the first time new high confidence variant calls for the unknown sample dataset (we refer to in this challenge as “truth dataset”) for the human sample at the end of the contest.”