Data-driven medicinal chemistry in the era of big data

• Published in: Drug discovery today Vol. 19; no. 7; pp. 859 - 868
• Main Authors: Lusher, Scott J., McGuire, Ross, van Schaik, René C., Nicholson, C. David, de Vlieg, Jacob
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.07.2014
• Subjects: Animals; Chemistry, Pharmaceutical - methods; Chemistry, Pharmaceutical - trends; Drug Discovery - methods; Drug Discovery - trends; Humans; Statistics as Topic - methods; Statistics as Topic - trends
• ISSN: 1359-6446; 1878-5832
• DOI: 10.1016/j.drudis.2013.12.004

Science, and the way we undertake research, is changing. The increasing rate of data generation across all scientific disciplines is providing incredible opportunities for data-driven research, with the potential to transform our current practices. The exploitation of so-called ‘big data’ will enable us to undertake research projects never previously possible but should also stimulate a re-evaluation of all our data practices. Data-driven medicinal chemistry approaches have the potential to improve decision making in drug discovery projects, providing that all researchers embrace the role of ‘data scientist’ and uncover the meaningful relationships and patterns in available data. All scientific disciplines, including medicinal chemistry, are the subject of a revolution as data are generated at unprecedented rates and their analysis and exploitation become increasingly fundamental to innovation.