The US Food and Drug Administration (FDA) is currently developing a guidance for industry to replace a previous guidance, "Pharmacokinetics in Patients With Impaired Renal Function--Study Design, Data Analysis, and Impact on Dosing and Labeling" (renal guidance) issued in May 1998. The impact of the 1998 renal guidance was assessed following a survey of 94 new drug applications (NDAs) for small-molecule new molecular entities (NMEs) approved over the past 5 years (2003-2007). The survey results indicate that 57% of these NDAs included renal impairment study data, that 44% of those with renal data included evaluation in patients on hemodialysis, and that 41% of those with renal data resulted in recommendation of dose adjustment in renal impairment. In addition, the survey results provided evidence that renal impairment can affect the pharmacokinetics of drugs that are predominantly eliminated by nonrenal processes such as metabolism and/or active transport. The latter finding supports our updated recommendation to evaluate pharmacokinetic/pharmacodynamic alterations in renal impairment for those drugs that are mainly eliminated by nonrenal processes, in addition to those that are mainly excreted unchanged by the kidney.

An important goal in drug development is to understand the effects of intrinsic and/or extrinsic factors (IEFs) on drug pharmacokinetics. Although clinical studies investigating a given IEF can accomplish this goal, they may not be feasible for all IEFs or for situations when multiple IEFs exist concurrently. Physiologically based pharmacokinetic (PBPK) models may serve as a complementary tool for forecasting the effects of IEFs. We developed PBPK models for four drugs that are eliminated by both cytochrome P450 (CYP)3A4 and CYP2D6, and evaluated model prediction of the effects of comedications and/or genetic polymorphism on drug exposure. PBPK models predicted 100 and ≥70% of the observed results when the conventional "twofold rule" and the more conservative 25% deviation cut point were applied, respectively. These findings suggest that PBPK models can be used to infer effects of individual or combined IEFs and should be considered to optimize studies that evaluate these factors, specifically drug interactions and genetic polymorphism of drug-metabolizing enzymes.