Drug Discovery, Open Data and Decision-making Seminar

The discovery and development of a new medicine is a long and complex endeavour, involving many different scientific disciplines. Hundreds of decisions need to be made, each of which can have an impact on the overall success of the project. Nevertheless, at the heart of the problem are three fundamental scientific challenges: (a) deciding on the biological target, (b) identifying a molecule with an appropriate balance of properties and (c) designing an effective clinical trial strategy.

In this talk I will focus on the first two of these ("right target" and "right molecule") and will discuss in particular how data, informatics and computational methods have an ever-growing role to play in making informed decisions. The biological sciences have a long tradition of “open data” yet until relatively recently this was not the case in the chemical and chemical biology sciences. The advent of freely-available public resources such as ChEMBL has changed that situation. ChEMBL currently contains more than 15m activity values for more than 1.8m compounds, curated from the literature, from data depositions and from other relevant sources. Our companion patent resource SureChEMBL contains more than 19 million unique compounds. These two databases have been widely used, in conjunction with other experimental and computational methods, to tackle a wide range of questions relevant to drug discovery. Further, the integration of bioactivity and drug data from ChEMBL with other bioinformatics resources in large-scale projects such as the Open Targets public-private partnership and the NIH's Illuminating the Druggable Genome enhances even further our ability to make more informed decisions in our quest for new therapies.