Genomics is enabling more individualized treatment by providing insights into which genes contribute to various medical conditions. For example, scientists are currently using genomics to understand how COVID-19 spreads and affects the immune system. This information could help with vaccine development.
A single human genome sequence generates between 300GB to 1TB of data. Technological improvements have driven down the costs of sequencing—a historically expensive process—and caused an explosion in genomic data over the past decade. This has created multiple opportunities for artificial intelligence in the space. Companies are working to commercialize AI-based genomics solutions to develop better pharmaceuticals, power more accurate disease diagnosis and help physicians to identify the most effective treatments.
In many big data applications, data loses its value over time, but the opposite is true for genomics. As genomics datasets grow, they can be re-analyzed to discover new mutations or biomarkers. Further, AI can improve treatment recommendations for patients using population-level data.
By analyzing massive amounts of genomic and clinical data, AI-based solutions can help physicians to determine the right treatment for each patient. Precision medicine is projected to be a $217 billion market by 2028. Use cases here can include identifying the various mutations that can further subtype a disease and spotting the best candidates for the different available therapies. It also includes dosing optimization based on genotypic or phenotypic characteristics, as well as biomarker analysis and linkage to disease and therapy selection.