Drug Metab Dispos. 2017 Jan; 45(1); 86-108.
Published online 2016 Nov 7
As a follow up to previous reviews, the aim of the present analysis was to systematically examine all drug metabolism, transport, pharmacokinetics (PK), and drug-drug interaction (DDI) data available in the 33 new drug applications (NDAs) approved by the Food and Drug Administration (FDA) in 2015, using the University of Washington Drug Interaction Database, and to highlight the significant findings. In vitro, a majority of the new molecular entities (NMEs) were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. In vivo, 95 clinical DDI studies displayed positive PK interactions, with an area under the curve (AUC) ratio ≥ 1.25 for inhibition or ≤ 0.8 for induction. When NMEs were considered as victim drugs, 21 NMEs had at least one positive clinical DDI, with three NMEs shown to be sensitive substrates of CYP3A (AUC ratio ≥ 5 when coadministered with strong inhibitors): cobimetinib, isavuconazole (the active metabolite of prodrug isavuconazonium sulfate), and ivabradine. As perpetrators, nine NMEs showed positive inhibition and three NMEs showed positive induction, with some of these interactions involving both enzymes and transporters. The most significant changes for inhibition and induction were observed with rolapitant, a moderate inhibitor of CYP2D6 and lumacaftor, a strong inducer of CYP3A. Physiologically based pharmacokinetics simulations and pharmacogenetics studies were used for six and eight NMEs, respectively, to inform dosing recommendations. The effects of hepatic or renal impairment on the drugs’ PK were also evaluated to support drug administration in these specific populations.
Drug Metab Dispos. 2016 Jan; 44(1); 83-101.
Published online 2015 Sep 30
Regulatory approval documents contain valuable information, often not published, to assess the drug-drug interaction (DDI) profile of newly marketed drugs. This analysis aimed to systematically review all drug metabolism, transport, pharmacokinetics, and DDI data available in the new drug applications and biologic license applications approved by the U.S. Food and Drug Administration in 2014, using the University of Washington Drug Interaction Database, and to highlight the significant findings. Among the 30 new drug applications and 11 biologic license applications reviewed, 35 new molecular entities (NMEs) were well characterized with regard to drug metabolism, transport, and/or organ impairment and were fully analyzed in this review. In vitro, a majority of the NMEs were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. In vivo, when NMEs were considered as victim drugs, 16 NMEs had at least one in vivo DDI study with a clinically significant change in exposure (area under the time-plasma concentration curve or Cmax ratio ≥2 or ≤0.5), with 6 NMEs shown to be sensitive substrates of cytochrome P450 enzymes (area under the time-plasma concentration curve ratio ≥5 when coadministered with potent inhibitors): paritaprevir and naloxegol (CYP3A), eliglustat (CYP2D6), dasabuvir (CYP2C8), and tasimelteon and pirfenidone (CYP1A2). As perpetrators, seven NMEs showed clinically significant inhibition involving both enzymes and transporters, although no clinically significant induction was observed. Physiologically based pharmacokinetic modeling and pharmacogenetics studies were used for six and four NMEs, respectively, to optimize dosing recommendations in special populations and/or multiple impairment situations. In addition, the pharmacokinetic evaluations in patients with hepatic or renal impairment provided useful quantitative information to support drug administration in these fragile populations.
Drug Metab Dispos. 2015 Nov; 43(11); 1823-37.
Published online 2015 Aug 21
Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms “PBPK” and “physiologically based pharmacokinetic model” to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines.
CPT Pharmacometrics Syst Pharmacol. 2015 Aug; 4(8); 489-94.
Published online 2015 Jul 14
The organ impairment and drug-drug interaction (OI-DDI) database is the first rigorously assembled database of pharmacokinetic drug exposure data from publicly available renal and hepatic impairment studies presented together with the maximum change in drug exposure from drug interaction inhibition studies. The database was used to conduct a systematic comparison of the effect of renal/hepatic impairment and pharmacologic inhibition on drug exposure. Additional applications are feasible with the public availability of this database.
Drug Metab Dispos. 2014 Dec; 42(12); 1991-2001.
Published online 2014 Sep 30
The aim of the present work was to perform a systematic review of drug metabolism, transport, pharmacokinetics, and DDI data available in the NDAs approved by the FDA in 2013, using the University of Washington Drug Interaction Database, and to highlight significant findings. Among 27 NMEs approved, 22 (81%) were well characterized with regard to drug metabolism, transport, or organ impairment, in accordance with the FDA drug interaction guidance (2012) and were fully analyzed in this review. In vitro, a majority of the NMEs were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. However, in vivo, only half (n = 11) showed clinically relevant drug interactions, with most related to the NMEs as victim drugs and CYP3A being the most affected enzyme. As perpetrators, the overall effects for NMEs were much less pronounced, compared with when they served as victims. In addition, the pharmacokinetic evaluation in patients with hepatic or renal impairment provided useful information for further understanding of the drugs’ disposition.