Introduction to in vitro estimation of metabolic stability and drug interactions of new chemical entities in drug discovery and development.
Determination of metabolic properties of a new chemical entity (NCE) is one of the most important steps during the drug discovery and development process. Nowadays, in vitro methods are used for early estimation and prediction of in vivo metabolism of NCEs. Using in vitro methods, it is possible to determine the metabolic stability of NCEs as well as the risk for drug-drug interactions (DDIs) related to inhibition and induction of drug metabolic enzymes. Metabolic stability is defined as the susceptibility of a chemical compound to biotransformation, and is expressed as in vitro half-life (t(1/2)) and intrinsic clearance (CL(int)). Based on these values, in vivo pharmacokinetic parameters such as bioavailability and in vivo half-life can be calculated. The drug metabolic enzymes possess broad substrate specificity and can metabolize multiple compounds. Therefore, the risk for metabolism-based DDIs is always a potential problem during the drug development process. For this reason, inhibition and induction in vitro screens are used early, before selection of a candidate drug (CD), to estimate the risk for clinically significant DDIs. At present, most pharmaceutical companies perform in vitro drug metabolism studies together with in silico prediction software and automated high-throughput screens (HTS). Available data suggest that in vitro methods are useful tools for identification and elimination of NCEs with unappreciated metabolic properties. However, the quantitative output of the methods has to be improved. The aim of this review is to highlight the practical and theoretical basis of the in vitro metabolic methods and the recent progress in the development of these assays.
Baranczewski
Paweł
P
Preclinical Development, Biovitrum AB, SE-112 76 Stockholm, Sweden. pawel.baranczewski@astrazeneca.com
Stańczak
Andrzej
A
Sundberg
Kathrin
K
Svensson
Richard
R
Wallin
Asa
A
Jansson
Jenny
J
Garberg
Per
P
Postlind
Hans
H
D000818:Animals; D001711:Biotransformation; D003198:Computer Simulation; D065607:Cytochrome P-450 Enzyme Inhibitors; D003577:Cytochrome P-450 Enzyme System / Q000737:chemistry / Q000378:metabolism; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000379:methods; D004347:Drug Interactions; D004355:Drug Stability; D004790:Enzyme Induction / Q000187:drug effects; D004791:Enzyme Inhibitors / Q000493:pharmacokinetics / Q000494:pharmacology; D014453:Glucuronosyltransferase / Q000378:metabolism; D006801:Humans; D066298:In Vitro Techniques; D008954:Models, Biological; D008958:Models, Molecular; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000378:metabolism*; D010599:Pharmacokinetics; D011487:Protein Conformation
D065607:Cytochrome P-450 Enzyme Inhibitors; D004791:Enzyme Inhibitors; D004364:Pharmaceutical Preparations; D003577:Cytochrome P-450 Enzyme System; D014453:Glucuronosyltransferase