title: Use of big data in drug development for precision medicine.
abstract: Drug development has been a costly and lengthy process with an extremely low success rate and lack of consideration of individual diversity in drug response and toxicity. Over the past decade, an alternative "big data" approach has been expanding at an unprecedented pace based on the development of electronic databases of chemical substances, disease gene/protein targets, functional readouts, and clinical information covering inter-individual genetic variations and toxicities. This paradigm shift has enabled systematic, high-throughput, and accelerated identification of novel drugs or repurposed indications of existing drugs for pathogenic molecular aberrations specifically present in each individual patient. The exploding interest from the information technology and direct-to-consumer genetic testing industries has been further facilitating the use of big data to achieve personalized Precision Medicine. Here we overview currently available resources and discuss future prospects.
authors.affiliation: Division of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, USA.
authors.forename: Rosa S
authors.initials: RS
authors.lastname: Kim
authors.affiliation: Division of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, USA; Division of Gastroenterology and Hepatology, Geneva University Hospital, Geneva, Switzerland.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Goossens
authors.affiliation: Division of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, USA.
authors.forename: Yujin
authors.initials: Y
authors.lastname: Hoshida
keywords: Big data; drug development; high-throughput screen; in silico drug discovery; precision medicine