BELFAST, March 2015: Almac had identified a bottleneck in their bioinformatics workflow relating to gap statistic. Gap statistic is used in the discovery and validation of molecular subtypes from high-throughput data, an essential component in their development of prognostic and predictive tests for stratified medicine. The typical run time for the gap statistic was 33 hours which limited the number of concurrent projects.
Analytics Engines achieved a 98% reduction in runtime for the typical full gap pipeline, reducing it down to 45 minutes. This performance improvement enables 44 times as many iterations over the same time period as before optimization, allowing for acceleration of timelines and increased throughput of diagnostic discovery projects.