Heidi J. Einolf

The Conduct of In Vitro and In Vivo Drug‐Drug Interaction Studies: A PhRMA Perspective

Current regulatory guidances do not address specific study designs for in vitro and in vivo drug‐drug interaction studies. There is a common desire by regulatory authorities and by industry sponsors to harmonize approaches to allow for a better assessment of the significance of findings across different studies and drugs. There is also a growing consensus for the standardization of cytochrome P450 (CYP) probe substrates, inhibitors, and inducers and for the development of classification systems to improve the communication of risk to health care providers and patients. While existing guidances cover mainly CYP‐mediated drug interactions, the importance of other mechanisms, such as transporters, has been recognized more recently and should also be addressed. This paper was prepared by the Pharmaceutical Research and Manufacturers of America (PhRMA) Drug Metabolism and Clinical Pharmacology Technical Working Groups and represents the current industry position. The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug‐drug interaction studies targeted to development (not discovery support) and to define a data package that can be expected by regulatory agencies in compound registration dossiers.

In Vitro and in Vivo Induction of Cytochrome P450: A Survey of the Current Practices and Recommendations: A Pharmaceutical Research and Manufacturers of America Perspective

Cytochrome P450 (P450) induction is one of the factors that can affect the pharmacokinetics of a drug molecule upon multiple dosing, and it can result in pharmacokinetic drug-drug interactions with coadministered drugs causing potential therapeutic failures. In recent years, various in vitro assays have been developed and used routinely to assess the potential for drug-drug interactions due to P450 induction. There is a desire from the pharmaceutical industry and regulatory agencies to harmonize assay methodologies, data interpretation, and the design of clinical drug-drug interaction studies. In this article, a team of 10 scientists from nine Pharmaceutical Research and Manufacturers of America (PhRMA) member companies conducted an anonymous survey among PhRMA companies to query current practices with regards to the conduct of in vitro induction assays, data interpretation, and clinical induction study practices. The results of the survey are presented in this article, along with reviews of current methodologies of in vitro assays and in vivo studies, including modeling efforts in this area. A consensus recommendation regarding common practices for the conduct of P450 induction studies is included.

Absorption, Metabolism, and Excretion of [14C]Vildagliptin, a Novel Dipeptidyl Peptidase 4 Inhibitor, in Humans

The absorption, metabolism, and excretion of (1-[[3-hydroxy-1-adamantyl) amino] acetyl]-2-cyano-(S)-pyrrolidine (vildagliptin), an orally active and highly selective dipeptidyl peptidase 4 inhibitor developed for the treatment of type 2 diabetes, were evaluated in four healthy male subjects after a single p.o. 100-mg dose of [14C]vildagliptin. Serial blood and complete urine and feces were collected for 168 h postdose. Vildagliptin was rapidly absorbed, and peak plasma concentrations were attained at 1.1 h postdose. The fraction of drug absorbed was calculated to be at least 85.4%. Unchanged drug and a carboxylic acid metabolite (M20.7) were the major circulating components in plasma, accounting for 25.7% (vildagliptin) and 55% (M20.7) of total plasma radioactivity area under the curve. The terminal half-life of vildagliptin was 2.8 h. Complete recovery of the dose was achieved within 7 days, with 85.4% recovered in urine (22.6% unchanged drug) and the remainder in feces (4.54% unchanged drug). Vildagliptin was extensively metabolized via at least four pathways before excretion, with the major metabolite M20.7 resulting from cyano group hydrolysis, which is not mediated by cytochrome P450 (P450) enzymes. Minor metabolites resulted from amide bond hydrolysis (M15.3), glucuronidation (M20.2), or oxidation on the pyrrolidine moiety of vildagliptin (M20.9 and M21.6). The diverse metabolic pathways combined with a lack of significant P450 metabolism (1.6% of the dose) make vildagliptin less susceptible to potential pharmacokinetic interactions with comedications of P450 inhibitors/inducers. Furthermore, as vildagliptin is not a P450 inhibitor, it is unlikely that vildagliptin would affect the metabolic clearance of comedications metabolized by P450 enzymes.

Evaluation of Various Static and Dynamic Modeling Methods to Predict Clinical CYP3A Induction Using In Vitro CYP3A4 mRNA Induction Data

Several drug–drug interaction (DDI) prediction models were evaluated for their ability to identify drugs with cytochrome P450 (CYP)3A induction liability based on in vitro mRNA data. The drug interaction magnitudes of CYP3A substrates from 28 clinical trials were predicted using (i) correlation approaches (ratio of the in vivo peak plasma concentration (Cmax) to in vitro half‐maximal effective concentration (EC50); and relative induction score), (ii) a basic static model (calculated R3 value), (iii) a mechanistic static model (net effect), and (iv) mechanistic dynamic (physiologically based pharmacokinetic) modeling. All models performed with high fidelity and predicted few false negatives or false positives. The correlation approaches and basic static model resulted in no false negatives when total Cmax was incorporated; these models may be sufficient to conservatively identify clinical CYP3A induction liability. Mechanistic models that include CYP inactivation in addition to induction resulted in DDI predictions with less accuracy, likely due to an overprediction of the inactivation effect.

Cytochrome P450 1A2 Detoxicates Aristolochic Acid in the Mouse

Aristolochic acids (AAs) are plant-derived nephrotoxins and carcinogens responsible for chronic renal failure and associated urothelial cell cancers in several clinical syndromes known collectively as aristolochic acid nephropathy (AAN). Mice provide a useful model for study of AAN because the renal histopathology of AA-treated mice is strikingly similar to that of humans. AA is also a potent carcinogen in mice with a tissue spectrum somewhat different from that in humans. The toxic dose of AA in mice is higher than that in humans; this difference in susceptibility has been postulated to reflect differing rates of detoxication between the species. Recent studies in mice have shown that the hepatic cytochrome P450 system detoxicates AA, and inducers of the arylhydrocarbon response protect mice from the nephrotoxic effects of AA. The purpose of this study was to determine the role of specific cytochrome P450 (P450) enzymes in AA metabolism in vivo. Of 18 human P450 enzymes we surveyed only two, CYP1A1 and CYP1A2, which were effective in demethylating 8-methoxy-6-nitro-phenanthro-(3,4-d)-1,3-dioxolo-5-carboxylic acid (AAI) to the nontoxic derivative 8-hydroxy-6-nitro-phenanthro-(3,4-d)-1,3-dioxolo-5-carboxylic acid (AAIa). Kinetic analysis revealed similar efficiencies of formation of AAIa by human and rat CYP1A2. We also report here that CYP1A2-deficient mice display increased sensitivity to the nephrotoxic effects of AAI. Furthermore, Cyp1a2 knockout mice accumulate AAI-derived DNA adducts in the kidney at a higher rate than control mice. Differences in bioavailability or hepatic metabolism of AAI, expression of CYP1A2, or efficiency of a competing nitroreduction pathway in vivo may explain the apparent differences between human and rodent sensitivity to AAI.

Evaluation of various static in vitro-in vivo extrapolation models for risk assessment of the CYP3A inhibition potential of an investigational drug

Nine static models (seven basic and two mechanistic) and their respective cutoff values used for predicting cytochrome P450 3A (CYP3A) inhibition, as recommended by the US Food and Drug Administration and the European Medicines Agency, were evaluated using data from 119 clinical studies with orally administered midazolam as a substrate. Positive predictive error (PPE) and negative predictive error (NPE) rates were used to assess model performance, based on a cutoff of 1.25‐fold change in midazolam area under the curve (AUC) by inhibitor. For reversible inhibition, basic models using total or unbound systemic inhibitor concentration [I] had high NPE rates (46–47%), whereas those using intestinal luminal ([I]gut) values had no NPE but a higher PPE. All basic models for time‐dependent inhibition had no NPE and reasonable PPE rates (15–18%). Mechanistic static models that incorporate all interaction mechanisms and organ specific [I] values (enterocyte and hepatic inlet) provided a higher predictive precision, a slightly increased NPE, and a reasonable PPE. Various cutoffs for predicting the likelihood of CYP3A inhibition were evaluated for mechanistic models, and a cutoff of 1.25‐fold change in midazolam AUC appears appropriate.

Evaluation of a New Molecular Entity as a Victim of Metabolic Drug-Drug Interactions - an Industry Perspective

Under the guidance of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ), scientists from 20 pharmaceutical companies formed a Victim Drug-Drug Interactions Working Group. This working group has conducted a review of the literature and the practices of each company on the approaches to clearance pathway identification (fCL), estimation of fractional contribution of metabolizing enzyme toward metabolism (fm), along with modeling and simulation-aided strategy in predicting the victim drug-drug interaction (DDI) liability due to modulation of drug metabolizing enzymes. Presented in this perspective are the recommendations from this working group on: 1) strategic and experimental approaches to identify fCL and fm, 2) whether those assessments may be quantitative for certain enzymes (e.g., cytochrome P450, P450, and limited uridine diphosphoglucuronosyltransferase, UGT enzymes) or qualitative (for most of other drug metabolism enzymes), and the impact due to the lack of quantitative information on the latter. Multiple decision trees are presented with stepwise approaches to identify specific enzymes that are involved in the metabolism of a given drug and to aid the prediction and risk assessment of drug as a victim in DDI. Modeling and simulation approaches are also discussed to better predict DDI risk in humans. Variability and parameter sensitivity analysis were emphasized when applying modeling and simulation to capture the differences within the population used and to characterize the parameters that have the most influence on the prediction outcome.

Disposition and metabolism of [(14)C] Sacubitril/Valsartan (formerly LCZ696) an angiotensin receptor neprilysin inhibitor, in healthy subjects.

Abstract 1. Sacubitril/valsartan (LCZ696) is an angiotensin receptor neprilysin inhibitor (ARNI) providing simultaneous inhibition of neprilysin (neutral endopeptidase 24.11; NEP) and blockade of the angiotensin II type-1 (AT1) receptor. 2. Following oral administration, [14C]LCZ696 delivers systemic exposure to valsartan and AHU377 (sacubitril), which is rapidly metabolized to LBQ657 (M1), the biologically active neprilysin inhibitor. Peak sacubitril plasma concentrations were reached within 0.5–1 h. The mean terminal half-lives of sacubitril, LBQ657 and valsartan were ∼1.3, ∼12 and ∼21 h, respectively. 3. Renal excretion was the dominant route of elimination of radioactivity in human. Urine accounted for 51.7–67.8% and feces for 36.9 to 48.3 % of the total radioactivity. The majority of the drug was excreted as the active metabolite LBQ657 in urine and feces, total accounting for ∼85.5% of the total dose. 4. Based upon in vitro studies, the potential for LCZ696 to inhibit or induce cytochrome P450 (CYP) enzymes and cause CYP-mediated drug interactions clinically was found to be low.

Time‐Dependent Inhibition and Induction of Human Cytochrome P4503A4/5 by an Oral IAP Antagonist, LCL161, In Vitro and In Vivo in Healthy Subjects

Tumor cells can evade programmed cell death via up‐regulation of inhibitor of apoptosis proteins (IAPs). LCL161 is a small molecule oral IAP antagonist in development for use in combination with cytotoxic agents. The effect of LCL161 on CYP3A4/5 (CYP3A) activity was investigated in vitro and in a clinical study. Results in human liver microsomes indicated LCL161 inhibited CYP3A in a concentration‐ and time‐dependent manner (KI of 0.797 µM and kinact of 0.0803 min−1). LCL161 activated human PXR in a reporter gene assay and induced CYP3A4 mRNA up to ∼5‐fold in human hepatocytes. In healthy subjects, the dual inhibitor and inductive effects of a single dose of LCL161 were characterized using single midazolam doses, given before and at three time points after the LCL161 dose. Midazolam Cmax increased 3.22‐fold and AUC(0‐inf) increased 9.32‐fold when administered four hours after LCL161. Three days later, midazolam Cmax decreased by 27% and AUC(0‐inf) decreased by 30%. No drug interaction remained one week later. The strong CYP3A inhibition by LCL161 was accurately predicted using dynamic physiologically‐based pharmacokinetic (PBPK) modeling approaches in Simcyp. However, the observed induction effect after the LCL161 dose could not be modeled; suggesting direct enzyme induction by LCL161 was not the underlying mechanism.

Evaluation of calibration curve-based approaches to predict clinical inducers and noninducers of CYP3A4 with plated human hepatocytes.

Cytochrome P450 (P450) induction is often considered a liability in drug development. Using calibration curve–based approaches, we assessed the induction parameters R3 (a term indicating the amount of P450 induction in the liver, expressed as a ratio between 0 and 1), relative induction score, Cmax/EC50, and area under the curve (AUC)/F2 (the concentration causing 2-fold increase from baseline of the dose-response curve), derived from concentration-response curves of CYP3A4 mRNA and enzyme activity data in vitro, as predictors of CYP3A4 induction potential in vivo. Plated cryopreserved human hepatocytes from three donors were treated with 20 test compounds, including several clinical inducers and noninducers of CYP3A4. After the 2-day treatment, CYP3A4 mRNA levels and testosterone 6β-hydroxylase activity were determined by real-time reverse transcription polymerase chain reaction and liquid chromatography–tandem mass spectrometry analysis, respectively. Our results demonstrated a strong and predictive relationship between the extent of midazolam AUC change in humans and the various parameters calculated from both CYP3A4 mRNA and enzyme activity. The relationships exhibited with non-midazolam in vivo probes, in aggregate, were unsatisfactory. In general, the models yielded better fits when unbound rather than total plasma Cmax was used to calculate the induction parameters, as evidenced by higher R2 and lower root mean square error (RMSE) and geometric mean fold error. With midazolam, the R3 cut-off value of 0.9, as suggested by US Food and Drug Administration guidance, effectively categorized strong inducers but was less effective in classifying midrange or weak inducers. This study supports the use of calibration curves generated from in vitro mRNA induction response curves to predict CYP3A4 induction potential in human. With the caveat that most compounds evaluated here were not strong inhibitors of enzyme activity, testosterone 6β-hydroxylase activity was also demonstrated to be a strong predictor of CYP3A4 induction potential in this assay model.