title: Improving drug safety using computational biology.
abstract: Despite the significant investment made in drug safety testing by the pharmaceutical industry, new drugs continue to experience a substantial failure rate because of unacceptable toxicology in patients. More effective methods of predicting potential safety issues that can be employed during the drug design phase are required to reduce this attrition. Computational biology offers such new approaches, and is a term that includes a wide range of disciplines, the general features of which are the application of computer science and mathematics to biology. The techniques used in computational biology can integrate and analyze large complex sets of data and enable scientists to truly exploit the large amounts of information available to them, both in predicting likely risk and in understanding issues when they arise. These new approaches can only be achieved by embracing in silico experimentation as a valid and equal partner to other forms of experimentation in drug safety, and by integrating these approaches alongside current methods to support better decision-making in R&D that will ultimately result in the production of safer medicines.
authors.affiliation: AstraZeneca plc, Global Safety Assessment, Mereside, Alderley Park, Macclesfield, Cheshire, SK10 4TG, UK. david.cook@astrazeneca.com
authors.forename: David
authors.initials: D
authors.lastname: Cook
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003657:Decision Making; D015195:Drug Design; D004345:Drug Industry; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D008962:Models, Theoretical