ABSTRACT
INTRODUCTION Drug discovery precedes preformulation studies but often a preformulation feedback helps faster drug discovery. Much has changed in the discovery of drugs over the past 25 years. Microprocessor-driven instrumentation has revolutionized data handling systems. Robotic systems have eased large sample processing, and integration of various physical and chemical sciences has resulted in the emergence of newer techniques. For example, high-throughput screening (HTS) is now an integral component of the drug discovery process practiced by most pharmaceutical and large biotechnology companies. It has evolved over the past decade from crude automation to use of sophisticated computer-driven array systems using robotic devices. Improved physicochemical data on prospective new active entities (NAEs) provide a great stimulus to new drug development as well as offering insights for the preformulation scientists to project the characteristics of the NAEs that would prove useful in their downstream processing. The downstream processes include hit-to-lead (HTL), lead optimization (LO), and in vitro absorption, distribution, metabolism, elimination, and toxicology (ADMET) studies, which are all driven by the peculiar characteristics of the NAE. What used to be the application of preformulation studies in the formulation steps has now shifted somewhat backwards into evaluation of lead compounds. In many instances, HTL and preformulation studies (theoretical or experimental) are combined to maximize the probability of clinical success.
