Biopharmaceutic Classification System: A Scientific Framework for Pharmacokinetic Optimization in Drug Research

Abstract

The tenets of biopharmaceutics, solubility and permeability, are of pivotal importance in new drug discovery and lead optimization due to the dependence of drug absorption and pharmacokinetics on these two properties. A classification system for drugs based on these two fundamental parameters, Biopharmaceutic Classification System (BCS), provides drug designer an opportunity to manipulate structure or physicochemical properties of lead candidates so as to achieve better "deliverability". Considering the facts for failure of NCEs, drug research, once concentrating on optimizing the efficacy and safety of the leads, dramatically transformed in the past two decades. With the enormous number of molecules being synthesized using combinatorial and parallel synthesis, high throughput methodologies for screening solubility and permeability has gained significant interest in pharmaceutical industry. Ultimate aim of the drug discovery scientist in pharmacokinetic optimization is to tailor the molecules so that they show the features of BCS class I without compromising on pharmacodynamics. Considerations to optimize drug delivery and pharmacokinetics right from the initial stages of drug design propelled need for "High Throughput Pharmaceutics" (HTP). In silico predictions and development of theoretical profiles for solubility and lipophilicity provides structure based biopharmaceutical optimization, while in vitro experimental models (microtitre plate assays and cell cultures) validate the predictions. Thus, biopharmaceutical characterization during drug design and early development helps in early withdrawal of molecules with insurmountable developmental problems associated with pharmacokinetic optimization.