The development of pharmacogenomic models to predict drug response

The potential of pharmacogenomic research to improve general healthcare, reduce morbidity and mortality resulting from treatment side effects, and to accelerate therapeutic compound discovery, design and development in the pharmaceutical industry, remains largely unfulfilled. Major contributory factors affecting progress in the field include: (i) the need for large clinical populations and control/placebo-treated cohorts to be studied; (ii) the difficulty in evaluating drug response in many instances with empirical or qualitative treatment response values often not available; (iii) interactions of underlying biochemical pathways are often not fully understood, both in terms of mode-of-action of a therapeutic compound itself and in the occurrence of side effects; (iv) population-specific frequency data for reported genetic variants and physically mapped genomic markers for evaluation in drug response studies are often not readily and/or publicly available; (v) accurate, high-throughput, cost-effective polymorphism detection and screening methods are required; and (vi) sophisticated biostatistical data analysis programs to perform the multi-parametric tests and permutation analyses necessary are still under development. With the recent human genome sequence draft release by both the public and commercial initiatives, in addition to the publication of locus and chromosome-specific polymorphism maps and TSC (The SNP Consortium) SNP map information expected in late-2001, it is hoped that at least some of the inherent difficulties in pharmacogenomics research will soon be alleviated.