Role of the development scientist in compound lead selection and optimization.

The R&D process for bringing drugs from discovery laboratories to the marketplace is undergoing rapid change, as enabled by new technologies and as demanded by the global pharmaceutical business environment. One consequence of the accelerated R&D paradigm is a blurring of the traditional discovery-development interface, which in turn impacts the traditional roles of discovery and development scientists. R&D organizations must find ways to screen out rapidly compounds that have relatively poor probability of successful registration. Quality of development candidates can be favorably influenced by early consideration of "developability" criteria along with receptor-based potency and specificity. Computational approaches and/or high-throughput experimental determinations will be used increasingly to profile compound characteristics which influence "developability." If such criteria are considered at the time of lead selection and optimization, the compound attrition rate during later development should be decreased from the historical norm. This article discusses the emerging role of development scientists during small-molecule lead selection and optimization. The changing role of development scientists also has implications for graduate curricula in the pharmaceutical sciences.

[1]  R A Hamilton,et al.  Determination of mean valproic acid serum level by assay of a single pooled sample , 1981, Clinical pharmacology and therapeutics.

[2]  S. Walker,et al.  Pharmaceutical innovation by the seven UK-owned pharmaceutical companies (1964-1985). , 1988, British journal of clinical pharmacology.

[3]  K. Luthman,et al.  Caco-2 monolayers in experimental and theoretical predictions of drug transport , 1996 .

[4]  CHANGES IN PHARMACOKINETICS AND DRUG METABOLISM RESPONSIBILITY IN DRUG DISCOVERY AND DEVELOPMENT , 1996 .

[5]  THE EVOLVING DRUG DISCOVERY AND DEVELOPMENT PROCESS , 1996 .

[6]  J. H. Krieger.  COMPUTATIONAL CHEMISTRY IMPACT , 1997 .

[7]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings , 1997 .

[8]  T. Kennedy.  Managing the drug discovery/development interface , 1997 .

[9]  Success is not necessarily automatic , 1998, The Journal of automatic chemistry.

[10]  W. Curatolo,et al.  Physical chemical properties of oral drug candidates in the discovery and exploratory development settings , 1998 .

[11]  Thomas J. Raub,et al.  Factors impacting the delivery of therapeutic levels of pyrone-based HIV protease inhibitors. , 1998, Pharmaceutical biotechnology.

[12]  Andrew T Merritt.  Uptake of new technology in lead optimization for drug discovery , 1998 .

[13]  P. Woollard,et al.  Cassette dosing: rapid in vivo assessment of pharmacokinetics , 1998 .

[14]  J R Chretien,et al.  Estimation of blood-brain barrier crossing of drugs using molecular size and shape, and H-bonding descriptors. , 1998, Journal of drug targeting.

[15]  Sample pooling to enhance throughput of brain penetration study. , 1999, Journal of pharmaceutical and biomedical analysis.

[16]  P J Sinko.  Drug selection in early drug development: screening for acceptable pharmacokinetic properties using combined in vitro and computational approaches. , 1999, Current opinion in drug discovery & development.

[17]  J. Chin,et al.  Preclinical evaluation of anti-inflammatory activities of the novel pyrrolopyrimidine PNU-142731A, a potential treatment for asthma. , 1999, The Journal of pharmacology and experimental therapeutics.

[18]  Michael J. Wise,et al.  Quantitative, Scalable Discrete-Event Simulation of Metabolic Pathways , 1999, ISMB.

[19]  F. Lombardo,et al.  The Anxieties of Drug Discovery and Development , 2002 .