Author: Jackson, Robert C.

Source: Pharmaceutical Development and Regulation, Volume 1, Number 3, 2003 , pp. 159-168(10)

Publisher: Adis International

Abstract:

The drug discovery and development process has become more quantitative and much more computationally intensive in recent years. For pharmaceutical and biotechnology companies, this has had two major implications. Firstly, there is now a much greater range of commercial software to support drug design and development. Secondly, a number of specialized companies have appeared that have written proprietary software, and which provide computational service support to the industry.

In the area of drug design, available software falls into four main categories: (i) tools for structure-based ligand design when a 3-dimensional receptor structure is available (from X-ray crystallography or high-field nuclear magnetic resonance spectrometry); (ii) software products for in silico screening of chemical compound collections against a 3-dimensional receptor structure, where this is available; (iii) computational tools for the design of inhibitors in the absence of a 3-dimensional structure, by drawing inferences about receptor structure from the properties of known inhibitors; and (iv) computational techniques for prediction of drug-like properties, i.e. the physical and metabolic attributes characteristic of successful drugs such as solubility, ability to cross biological barriers, and stability to metabolism.

A number of other trends are leading to greater computational intensity in drug development. Software is available that attempts to predict a range of toxicities, and also drug absorption, distribution, metabolism and elimination (ADME) properties from chemical structure. In another growth area, the established discipline of pharmacokinetics (prediction of drug concentrations in body compartments) is extending its range into pharmacodynamics (prediction of drug effects). Since drug effects are the result of interactions of xenobiotic agents with complex biological systems, this has led to attempts to create quantitative disease models, bringing the field of complex system theory into drug development. Ultimately the rate-limiting process in drug development, and the most expensive part, is the clinical trial. The promise that computational biology brings to drug development is the ability to bring these modeling tools to bear on the design and interpretation of clinical trials, to increase their success rate and cost effectiveness.

Keywords: Electronic information services; Research and development

Document Type: Leading Article

Affiliations: Cyclacel Ltd, Dundee, UK

Publication date: 2003-01-01

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