The ability to synthesize large numbers of diverse combinatorial chemistry libraries and the advances in automated high throughput screening (HTS) techniques have reduced significantly, the time required for identifying lead candidate with desired potency against a biological target. As a result, the bottleneck of faster drug discovery seems shifting towards optimizing lead candidates so as to result in adequate ADME (absorption, distribution, metabolism, and excretion) properties, according to Dr R Narayanan, Bioinformatics Division, Advanced Technology Centre, Tata Consultancy Services.

Between 1964 and 1985, 66 per cent of chemical entities were withdrawn from further development in seven large British pharmaceutical companies. A similar trend was found in the US. Between 1964-1989, only one in six new chemical entities nominated to investigational new drug status eventually became a marketed drug.

It was shown that in addition to unproved efficacy, toxicity, and adverse reactions, inadequate pharmacokinetic properties resulted in nearly 40 per cent of withdrawals of leads from further development. Apparently fast evaluation of ADME properties in the early stages of drug discovery will save both time and expense. However, due to complex nature of these properties and the time-consuming experimental procedures involved, these properties are not apt to experimental high throughput screening, he added.

It has been suggested that computational models for reliable prediction of ADME properties are promising as early screening tools for drug candidates and for designing more successful combinatorial libraries.