Tags

, , , , , ,

Li DiLi Di, Ph.D., is an associate research fellow at Pfizer Inc., Groton, Conn.

In recent years, modeling and simulation have made great advancements in drug discovery and development. The increased need to efficiently evaluate and use information to improve success in the drug development process is a challenge met by progress in computational technology. Computer-aided drug design (CADD) and its related virtual technologies are state-of-the-art and have evolved to meet the increased need to rapidly evaluate large numbers of chemicals at speeds comparable to biomolecular screening. Their methods are becoming increasingly more reliable and have significantly contributed to advances in drug discovery. Advances in computational power, cheminformatics, and application to translational science represent ways CADD has been innovative at the drug design and development interface.

Great strides have also been made in accurately analyzing large compound libraries through cheminformatics. Cheminformatics encompasses the collection, storage, and analysis of data related to the physiochemical properties and pharmacological activities of molecular libraries. Such a wealth of information may be overwhelming but can be handled efficiently by a number of cheminformatic tools. The ultimate goal of CADD is to enhance the efficiency with which a drug is brought “from bench to bedside.” Accordingly, CADD can be applied to translational bioscience as a tool for predicting new uses for old drugs (repurposing) and directing selection of the best therapeutic regimen for each patient (personalized medicine).

Drug Discovery

As new protein targets and pharmacological endpoints are discovered, the need to quickly identify novel hits for development becomes paramount. The challenge remains for application of CADD to personalized medicine in correlating genetic biomarkers with disease prognosis, and identifying patients who will best respond to a particular therapy. As a link between biochemical information and patient health outcomes, modern CADD represents an important and growing tool in translational bioscience.

The article “Advances in Modeling and Simulation in Drug Discovery and Development,” featured in the July issue of the AAPS Newsmagazine and developed by the Drug Discovery and Development Interface section, highlights the success of prediction tools not only in computer-aided drug design but also in absorption, distribution, metabolism, excretion, toxicity (ADMET); pre-formulation; and formulation. Read the article and then participate in the discussion questions below.

Discussion Point: What modeling and simulation tools do you use? Do you find they are meeting your needs? What new in silico tools do you think are useful to develop in the future?