title: In silico prediction of clinical efficacy.
abstract: Drug development is a high risk and costly process, and the ability to predict clinical efficacy in silico (in a computer) can save the pharmaceutical industry time and resources. Additionally, such an approach will result in more targeted, personalized therapies. To date, a number of in silico strategies have been developed to provide better information about the human response to novel therapies earlier in the drug development process. Some of the most prominent include physiological modeling of disease and disease processes, analytical tools for population pharmacodynamics, tools for the analysis of genomic expression data, Monte Carlo simulation technologies, and predictive biosimulation. These strategies are likely to contribute significantly to reducing the failure rate of drugs entering clinical trials.
authors.affiliation: Entelos, Inc., 110 Marsh Drive, Foster City, CA 94404, USA.
authors.forename: Seth
authors.initials: S
authors.lastname: Michelson
authors.forename: Anil
authors.initials: A
authors.lastname: Sehgal
authors.forename: Christina
authors.initials: C
authors.lastname: Friedrich
mesh_terms: D002986:Clinical Trials as Topic / Q000379:methods*; D003198:Computer Simulation; D015195:Drug Design; D004341:Drug Evaluation / Q000379:methods*; D008954:Models, Biological; D010597:Pharmacogenetics / Q000379:methods*