Development of a physiologically based pharmacokinetic model of fostemsavir and its pivotal application to support dosing in pregnancy.

It is critical to understand the impact of significant physiological changes during pregnancy on the extent of maternal and fetal drug exposure. Fostemsavir (FTR) is a prodrug of temsavir (TMR) and is approved in combination with other antiretrovirals for multi-drug-resistant human immunodeficiency virus (HIV) infections. This physiologically based pharmacokinetic model (PBPK) study was used to estimate TMR PK in pregnant populations during each trimester of pregnancy to inform FTR dosing. A PBPK model was developed and validated for TMR using PK data collected following intravenous TMR and oral FTR dosing (immediate-release and extended-release tablets) in healthy volunteers. Predicted TMR concentration-time profiles accurately predicted the reported clinical data and variability in healthy (dense data) and pregnant (sparse data) populations. Predicted versus observed TMR geometric mean (CV%) clearance following intravenous administration was 18.01 (29) versus 17 (21) (L/h). Predicted versus observed TMR AUC0-inf (ng.h/mL) in healthy volunteers following FTR administration of the extended-release tablet were 9542 (66) versus 7339 (33). The validated TMR PBPK model was then applied to predict TMR PK in a population of pregnant individuals during each trimester. Simulations showed TMR AUC in pregnant individuals receiving FTR 600 mg twice daily was decreased by 25% and 38% in the second and third trimesters, respectively. However, TMR exposure remained within the range observed in nonpregnant adults with no need for dose adjustment. The current PBPK model can also be applied for the prediction of local tissue concentrations and drug-drug interactions in pregnancy.

Survey of pharmaceutical industry's best practices around in vitro transporter assessment and Implications for Drug Development: Considerations from the IQ Transporter Working Group.

The IQ Transporter Working Group had a rare opportunity to analyse a cross-pharma collation of in vitro data and assay methods for the evaluation of drug transporter substrate and inhibitor potential. Experiments were generally performed in accordance with regulatory guidelines. Discrepancies, such as not considering the impact of pre-incubation for inhibition and free or measured in vitro drug concentrations, may be due to the retrospective nature of the dataset and analysis. Lipophilicity was a frequent indicator of cross-transport inhibition (P-gp, BCRP, OATP1B and OCT1) with high molecular weight ({greater than or equal to}500 Da) also common for OATP1B and BCRP inhibitors. A high level of overlap in in vitro inhibition across transporters was identified for BCRP, OATP1B1 and MATE1 suggesting that prediction of DDIs for these transporters will be common. In contrast inhibition of OAT1 did not coincide with inhibition of any other transporter. Neutrals, bases, and compounds with intermediate-high lipophilicity tended to be P-gp and/or BCRP substrates whilst compounds with MW <500 Da tended to be OAT3 substrates. Interestingly the majority of in vitro inhibitors were not reported to be followed up with a clinical study by the submitting company, whilst those compounds identified as substrates generally were. Approaches to metabolite testing were generally found to be similar to parent testing with metabolites generally being equally or less potent than parent compounds. However, examples where metabolites inhibited transporters in vitro were identified supporting the regulatory requirement for in vitro testing of metabolites to enable integrated clinical DDI risk assessment. Significance Statement A diverse dataset showed transporter inhibition often correlated with lipophilicity and molecular weight (>500 Da). Overlapping transporter inhibition was identified, particularly that inhibition of BCRP, OATP1B1 and MATE1 was frequent if the compound inhibited other transporters. In contrast inhibition of OAT1 did not correlate with the other drug transporters tested.

Considerations for Industry-Preparing for the FDA Model-Informed Drug Development (MIDD) Paired Meeting Program.

A recent industry perspective published in this journal describes the benefits received by drug companies from participation in the MIDD Pilot Program. Along with the primary objectives of supporting good decision-making in drug development, there were substantial savings in time and development costs. Furthermore, many sponsors reported qualitative benefits such as new learnings and clarity on MIDD strategies and methodology that could be applied to other development programs. Based on the success of the Pilot Program, the FDA recently announced the continuation of the MIDD Paired Meeting Program as part of the Prescription Drug User Fee Act (PDUFA VII). In this report, we describe the collective experiences of industry participants in the MIDD Program to date, including all aspects of the process from meeting request submission to follow-up actions. The purpose is to provide future participants with information to optimize the value of the MIDD Program.

Physiologically-based pharmacokinetic modeling of prominent oral contraceptive agents and applications in drug-drug interactions.

Considerable interest remains across the pharmaceutical industry and regulatory landscape in capabilities to model oral contraceptives (OCs), whether combined (COCs) with ethinyl estradiol (EE) or progestin-only pill. Acceptance of COC drug-drug interaction (DDI) assessment using physiologically-based pharmacokinetic (PBPK) is often limited to the estrogen component (EE), requiring further verification, with extrapolation from EE to progestins discouraged. There is a paucity of published progestin component PBPK models to support the regulatory DDI guidance for industry to evaluate a new chemical entity's (NCE's) DDI potential with COCs. Guidance recommends a clinical interaction study to be considered if an investigational drug is a weak or moderate inducer, or a moderate/strong inhibitor, of CYP3A4. Therefore, availability of validated OC PBPK models within one software platform, will be useful in predicting the DDI potential with NCEs earlier in the clinical development. Thus, this work was focused on developing and validating PBPK models for progestins, DNG, DRSP, LNG, and NET, within Simcyp, and assessing the DDI potential with known CYP3A4 inhibitors (e.g., ketoconazole) and inducers (e.g., rifampicin) with published clinical data. In addition, this work demonstrated confidence in the Simcyp EE model for regulatory and clinical applications by extensive verification in 70+ clinical PK and CYP3A4 interaction studies. The results provide greater capability to prospectively model clinical CYP3A4 DDI with COCs using Simcyp PBPK to interrogate the regulatory decision-tree to contextualize the potential interaction by known perpetrators and NCEs, enabling model-informed decision making, clinical study designs, and delivering potential alternative COC options for women of childbearing potential.

Innovations, Opportunities, and Challenges for Predicting Alteration in Drug-Metabolizing Enzyme and Transporter Activity in Specific Populations.

Drug-metabolizing enzymes and transporters (DMETs) are key regulators of the pharmacokinetics, efficacy, and toxicity of therapeutics. Over the past two decades, significant advancements in in vitro methodologies, targeted proteomics, in vitro to in vivo extrapolation methods, and integrated computational approaches such as physiologically based pharmacokinetic modeling have unequivocally contributed to improving our ability to quantitatively predict the role of DMETs in absorption, distribution, metabolism, and excretion and drug-drug interactions. However, the paucity of data regarding alterations in DMET activity in specific populations such as pregnant individuals, lactation, pediatrics, geriatrics, organ impairment, and disease states such as, cancer, kidney, and liver diseases and inflammation has restricted our ability to realize the full potential of these recent advancements. We envision that a series of carefully curated articles in a special supplementary issue of Drug Metabolism and Disposition will summarize the latest progress in in silico, in vitro, and in vivo approaches to characterize alteration in DMET activity and quantitatively predict drug disposition in specific populations. In addition, the supplementary issue will underscore the current scientific knowledge gaps that present formidable barriers to fully understand the clinical implications of altered DMET activity in specific populations and highlight opportunities for multistakeholder collaboration to advance our collective understanding of this rapidly emerging area. SIGNIFICANCE STATEMENT: This commentary highlights current knowledge and identifies gaps and key challenges in understanding the role of drug-metabolizing enzymes and transporters (DMETs) in drug disposition in specific populations. With this commentary for the special issue in Drug Metabolism and Disposition, the authors intend to increase interest and invite potential contributors whose research is focused or has aided in expanding the understanding around the role and impact of DMETs in drug disposition in specific populations.

Physiologically based pharmacokinetic modeling for development and applications of a virtual celiac disease population using felodipine as a model drug.

In celiac disease (CeD), gastrointestinal CYP3A4 abundance and morphology is affected by the severity of disease. Therefore, exposure to CYP3A4 substrates and extent of drug interactions is altered. A physiologically-based pharmacokinetic (PBPK) population for different severities of CeD was developed. Gastrointestinal physiology parameters, such as luminal pH, transit times, morphology, P-gp, and CYP3A4 expression were included in development of the CeD population. Data on physiological difference between healthy and CeD subjects were incorporated into the model as the ratio of celiac to healthy. A PBPK model was developed and verified for felodipine extended-release tablet in healthy volunteers (HVs) and then utilized to verify the CeD populations. Plasma concentration-time profile and PK parameters were predicted and compared against those observed in both groups. Sensitivity analysis was carried out on key system parameters in CeD to understand their impact on drug exposure. For felodipine, the predicted mean concentration-time profiles and 5th and 95th percentile intervals captured the observed profile and variability in the HV and CeD populations. Predicted and observed clearance was 56.9 versus 56.1 (L/h) in HVs. Predicted versus observed mean ± SD area under the curve for extended release felodipine in different severities of CeD were values of 14.5 ± 9.6 versus 14.4 ± 2.1, 14.6 ± 9.0 versus 17.2 ± 2.8, and 28.1 ± 13.5 versus 25.7 ± 5.0 (ng.h/mL), respectively. Accounting for physiology differences in a CeD population accurately predicted the PK of felodipine. The developed CeD population can be applied for determining the drug concentration of CYP3A substrates in the gut as well as for systemic levels, and for application in drug-drug interaction studies.

Clinical Relevance of Hepatic and Renal P-gp/BCRP Inhibition of Drugs: An International Transporter Consortium Perspective.

The role of P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) in drug-drug interactions (DDIs) and limiting drug absorption as well as restricting the brain penetration of drugs with certain physicochemical properties is well known. P-gp/BCRP inhibition by drugs in the gut has been reported to increase the systemic exposure to substrate drugs. A previous International Transporter Consortium (ITC) perspective discussed the feasibility of P-gp/BCRP inhibition at the blood-brain barrier and its implications. This ITC perspective elaborates and discusses specifically the hepatic and renal P-gp/BCRP (referred as systemic) inhibition of drugs and whether there is any consequence for substrate drug disposition. This perspective summarizes the clinical evidence-based recommendations regarding systemic P-gp and BCRP inhibition of drugs with a focus on biliary and active renal excretion pathways. Approaches to assess the clinical relevance of systemic P-gp and BCRP inhibition in the liver and kidneys included (i) curation of DDIs involving intravenously administered substrates or inhibitors; (ii) in vitro-to-in vivo extrapolation of P-gp-mediated DDIs at the systemic level; and (iii) curation of drugs with information available about the contribution of biliary excretion and related DDIs. Based on the totality of evidence reported to date, this perspective supports limited clinical DDI risk upon P-gp or BCRP inhibition in the liver or kidneys.

Robust physiologically based pharmacokinetic model of rifampicin for predicting drug-drug interactions via P-glycoprotein induction and inhibition in the intestine, liver, and kidney.

P-glycoprotein (P-gp) is an efflux transporter that plays an important role in the pharmacokinetics of its substrate, and P-gp activities can be altered by induction and inhibition effects of rifampicin. This study aimed to establish a physiologically based pharmacokinetic (PBPK) model of rifampicin to predict the P-gp-mediated drug-drug interactions (DDIs) and assess the DDI impact in the intestine, liver, and kidney. The induction and inhibition parameters of rifampicin for P-gp were estimated using two of seven DDI cases of rifampicin and digoxin and incorporated into our previously constructed PBPK model of rifampicin. The constructed rifampicin model was verified using the remaining five DDI cases with digoxin and five DDI cases with other P-gp substrates (talinolol and quinidine). Based on the established PBPK model, following repeated dosing of 600 mg rifampicin, the deduced net effect was an approximately threefold induction in P-gp activities in the intestine, liver, and kidney. Furthermore, in all 12 cases the predicted area under the plasma concentration-time curve ratios of the P-gp substrates were within the predefined acceptance criteria with various dosing regimens. Intestinal effects of P-gp-mediated DDIs had their greatest impact on the pharmacokinetics of digoxin and talinolol, with a minimal impact on the liver and kidney. For quinidine, predicted intestinal P-gp/cytochrome P450 3A-mediated DDIs were slightly underestimated because of the complexity of nonlinearity and transporter-enzyme interplay. These findings demonstrate that our rifampicin model can be applicable to quantitatively predict the net impact of P-gp induction and/or inhibition on diverse P-gp substrates and investigate the magnitude of DDIs in each tissue.

Clinical Implications of Altered Drug Transporter Abundance/Function and PBPK Modeling in Specific Populations: An ITC Perspective.

The role of membrane transporters on pharmacokinetics (PKs), drug-drug interactions (DDIs), pharmacodynamics (PDs), and toxicity of drugs has been broadly recognized. However, our knowledge of modulation of transporter expression and/or function in the diseased patient population or specific populations, such as pediatrics or pregnancy, is still emerging. This white paper highlights recent advances in studying the changes in transporter expression and activity in various diseases (i.e., renal and hepatic impairment and cancer) and some specific populations (i.e., pediatrics and pregnancy) with the focus on clinical implications. Proposed alterations in transporter abundance and/or activity in diseased and specific populations are based on (i) quantitative transporter proteomic data and relative abundance in specific populations vs. healthy adults, (ii) clinical PKs, and emerging transporter biomarker and/or pharmacogenomic data, and (iii) physiologically-based pharmacokinetic modeling and simulation. The potential for altered PK, PD, and toxicity in these populations needs to be considered for drugs and their active metabolites in which transporter-mediated uptake/efflux is a major contributor to their absorption, distribution, and elimination pathways and/or associated DDI risk. In addition to best practices, this white paper discusses current challenges and knowledge gaps to study and quantitatively predict the effects of modulation in transporter activity in these populations, together with the perspectives from the International Transporter Consortium (ITC) on future directions.

Physiologically-based pharmacokinetic model-based translation of OATP1B-mediated drug-drug interactions from coproporphyrin I to probe drugs.

The accurate prediction of OATP1B-mediated drug-drug interactions (DDIs) is challenging for drug development. Here, we report a physiologically-based pharmacokinetic (PBPK) model analysis for clinical DDI data generated in heathy subjects who received oral doses of cyclosporin A (CysA; 20 and 75 mg) as an OATP1B inhibitor, and the probe drugs (pitavastatin, rosuvastatin, and valsartan). PBPK models of CysA and probe compounds were combined assuming inhibition of hepatic uptake of endogenous coproporphyrin I (CP-I) by CysA. In vivo Ki of unbound CysA for OATP1B (Ki,OATP1B ), and the overall intrinsic hepatic clearance per body weight of CP-I (CLint,all,unit ) were optimized to account for the CP-I data (Ki,OATP1B , 0.536 ± 0.041 nM; CLint,all,unit , 41.9 ± 4.3 L/h/kg). DDI simulation using Ki,OATP1B reproduced the dose-dependent effect of CysA (20 and 75 mg) and the dosing interval (1 and 3 h) on the time profiles of blood concentrations of pitavastatin and rosuvastatin, but DDI simulation using in vitro Ki,OATP1B failed. The Cluster Gauss-Newton method was used to conduct parameter optimization using 1000 initial parameter sets for the seven pharmacokinetic parameters of CP-I (ß, CLint, all , Fa Fg , Rdif , fbile , fsyn , and vsyn ), and Ki,OATP1B and Ki,MRP2 of CysA. Based on the accepted 546 parameter sets, the range of CLint, all and Ki,OATP1B was narrowed, with coefficients of variation of 12.4% and 11.5%, respectively, indicating that these parameters were practically identifiable. These results suggest that PBPK model analysis of CP-I is a promising translational approach to predict OATP1B-mediated DDIs in drug development.

Effect of Cyclosporin A and Impact of Dose Staggering on OATP1B1/1B3 Endogenous Substrates and Drug Probes for Assessing Clinical Drug Interactions.

This study was designed to assess the quantitative performance of endogenous biomarkers for organic anion transporting polypeptide (OATP) 1B1/1B3-mediated drug-drug interactions (DDIs). Ten healthy volunteers orally received OATP1B1/1B3 probe cocktail (0.2 mg pitavastatin, 1 mg rosuvastatin, and 2 mg valsartan) and an oral dose of cyclosporin A (CysA, 20 mg and 75 mg) separated by a 1-hour interval (20 mg (-1 hour), and 75 mg (-1 hour)). CysA 75 mg was also given with a 3-hour interval (75 mg (-3 hours)) to examine the persistence of OATP1B1/1B3 inhibition. The area under the plasma concentration-time curve ratios (AUCRs) were 1.63, 3.46, and 2.38 (pitavastatin), 1.39, 2.16, and 1.81 (rosuvastatin), and 1.42, 1.77, and 1.85 (valsartan), at 20 mg, 75 mg (-1 hour) and 75 mg (-3 hours) of CysA, respectively. CysA effect on OATP1B1/1B3 was unlikely to persist at the dose examined. Among 26 putative OATP1B1/1B3 biomarkers evaluated, AUCR and maximum concentration ratio (Cmax R) of CP-I showed the highest Pearson's correlation coefficient with CysA AUC (0.94 and 0.93, respectively). Correlation between AUCR of pitavastatin, and Cmax R or AUCR of CP-I were consistent between this study and our previous study using rifampicin as an OATP1B1/1B3 inhibitor. Nonlinear regression analysis of AUCR-1 of pitavastatin and CP-I against CysA Cmax yielded Ki,OATP1B1/1B3,app (109 ± 35 and 176 ± 42 nM, respectively), similar to the Ki ,OATP1B1/1B3 estimated by our physiologically-based pharmacokinetic model analysis described previously (107 nM). The endogenous OATP1B1/1B3 biomarkers, particularly Cmax R and AUCR of CP-I, corroborates OATP1B1/1B3 inhibition and yields valuable information that improve accurate DDI predictions in drug development, and enhance our understanding of interindividual variability in the magnitude of DDIs.

Current Practices, Gap Analysis, and Proposed Workflows for PBPK Modeling of Cytochrome P450 Induction: An Industry Perspective.

The International Consortium for Innovation and Quality (IQ) Physiologically Based Pharmacokinetic (PBPK) Modeling Induction Working Group (IWG) conducted a survey across participating companies around general strategies for PBPK modeling of induction, including experience with its utility to address various questions, regulatory interactions, and regulatory acceptance. The results highlight areas where PBPK modeling is used with high confidence and identifies opportunities where confidence is lower and further evaluation is needed. To enhance the survey results, the PBPK-IWG also collected case studies and analyzed recent literature examples where PBPK models were applied to predict CYP3A induction-mediated drug-drug interactions. PBPK modeling of induction has evolved and progressed significantly, proving to have great potential to accelerate drug discovery and development. With the aim of enabling optimal use for new molecular entities that are either substrates and/or inducers of CYP3A, the PBPK-IWG proposes initial workflows for PBPK application, discusses future trends, and identifies gaps that need to be addressed.

When special populations intersect with drug-drug interactions: Application of physiologically-based pharmacokinetic modeling in pregnant populations.

Pregnancy results in significant physiological changes that vary across trimesters and into the postpartum period, and may result in altered disposition of endogenous substances and drug pharmacokinetics. Pregnancy represents a unique special population where physiologically-based pharmacokinetic modeling (PBPK) is well suited to mechanistically explore pharmacokinetics and dosing paradigms without subjecting pregnant women or their fetuses to extensive clinical studies. A critical review of applications of pregnancy PBPK models (pPBPK) was conducted to understand its current status for prediction of drug exposure in pregnant populations and to identify areas of further expansion. Evaluation of existing pPBPK modeling efforts highlighted improved understanding of cytochrome P450 (CYP)-mediated changes during pregnancy and identified knowledge gaps for non-CYP enzymes and the physiological changes of the postpartum period. Examples of the application of pPBPK beyond simple dose regimen recommendations are limited, particularly for prediction of drug-drug interactions (DDI) or differences between genotypes for polymorphic drug metabolizing enzymes. A raltegravir pPBPK model implementing UGT1A1 induction during the second and third trimesters of pregnancy was developed in the current work and verified against clinical data. Subsequently, the model was used to explore UGT1A1-related DDI risk with atazanavir and rifampicin along with the effect of enzyme genotype on raltegravir apparent clearance. Simulations of pregnancy-related induction of UGT1A1 either exacerbated UGT1A1 induction by rifampicin or negated atazanavir UGT1A1 inhibition. This example illustrated the advantages of pPBPK modeling for mechanistic evaluation of complex interplays of pregnancy- and drug-related effects in support of model-informed approaches in drug development.

Physiologically-based Pharmacokinetic (PBPK) Modelling of Transporter Mediated Drug Absorption, Clearance and Drug-drug Interactions.

Membrane transporters play an important role in intestinal absorption, distribution and clearance of drugs. Additionally transporters along with enzymes regulate tissue exposures (e.g. liver, kidney and brain), which are important for safety and efficacy considerations. Early identification of transporters involved guides generation of in vitro and in vivo data needed to gain mechanistic understanding on the role of transporters in organ clearance, tissue exposures and enables development of physiological-based pharmacokinetic (PBPK) models. A lot of progress has been made in developing several in vitro assay systems and mechanistic in silico models to determine kinetic parameters for transporters, which are incorporated into PBPK models. Although, intrinsic clearance and inhibition data from in vitro systems generally tend to underpredict in vivo clearance and magnitude of drug-drug interactions (DDIs), empirical scaling factors derived from a sizable dataset are often used to offset underpredictions. PBPK models are increasing used to predict the impact of transporters on intestinal absorption, clearance, victim and perpetrator DDIs prior to first in human clinical trials. The models are often refined when clinical data is available and are used to predict pharmacokinetics in untested scenarios such as the impact of polymorphisms, ontogeny, ethnicity, disease states and DDIs with other perpetrator drugs. The aim of this review is to provide an overview of (i) regulatory requirements around transporters, (ii) in vitro systems and their limitations in predicting transporter mediated drug disposition and DDIs, (iii) PBPK modelling tactics and case studies used for internal decision making and/or for regulatory submissions.

Intestinal P-gp and Putative Hepatic OATP1B Induction: International Transporter Consortium Perspective on Drug Development Implications.

There is an increasing interest in transporter induction (i.e., decreased systemic drug exposure due to increased efflux-limited absorption or transporter-mediated clearance) as a mechanism of drug-drug interactions (DDIs), although evidence of clinical relevance is still evolving. Intestinal P-glycoprotein (P-gp) and hepatic organic anion transporting polypeptides 1B (OATP1B) can be important determinants of drug absorption and disposition, as well as targets for DDIs. Current data indicate that intestinal P-gp protein levels can be induced up to threefold to fourfold in humans primarily with pregnane X receptor (PXR) activators, and that this induction can decrease the systemic exposure of drugs with P-gp efflux-limited absorption (e.g., ≤ 67% decrease in the exposure of total dabigatran following rifampin multiple oral dosing). Evaluation of the clinical relevance of P-gp induction as a DDI mechanism must consider the induction potential of the perpetrator drug for P-gp and attenuation of exposure of the victim drug in the context of its therapeutic window. Practical drug development recommendations are provided herein. Reports are contradictory on OATP1B induction by PXR activators in human hepatocytes and liver biopsies. Some clinical investigations demonstrated that rifampin pretreatment decreased exposure of OATP1B substrates, while other studies found no differences, and the potential involvement of other mechanisms in these observed DDIs cannot be definitively ruled out. Thus, further studies are needed to understand hepatic OATP1B induction and potential involvement of other mechanisms contributing to reduced exposure of OATP1B substrates. This review critically summarizes the state-of-the-art on intestinal P-gp and hepatic OATP1B induction, and highlights implications for drug development.

Drug Interactions for Low-Dose Inhaled Nemiralisib: A Case Study Integrating Modeling, In Vitro, and Clinical Investigations.

In vitro data for low-dose inhaled phosphoinositide 3-kinase delta inhibitor nemiralisib revealed that it was a substrate and a potent metabolism-dependent inhibitor of cytochrome P450 (P450) 3A4 and a P-glycoprotein (P-gp) substrate. An integrated in silico, in vitro, and clinical approach including a clinical drug interaction study as well as a bespoke physiologically based pharmacokinetic (PBPK) model was used to assess the drug-drug interaction (DDI) risk. Inhaled nemiralisib (100 µg, single dose) was coadministered with itraconazole, a potent P4503A4/P-gp inhibitor, following 200 mg daily administrations for 10 days in 20 male healthy subjects. Systemic exposure to nemiralisib (AUC0-inf) increased by 2.01-fold versus nemiralisib alone. To extrapolate the clinical data to other P4503A4 inhibitors, an inhaled PBPK model was developed using Simcyp software. Retrospective simulation of the victim risk showed good agreement between simulated and observed data (AUC0-inf ratio 2.3 vs. 2.01, respectively). Prospective DDI simulations predicted a weak but manageable drug interaction when nemiralisib was coadministered with other P4503A4 inhibitors, such as the macrolides clarithromycin and erythromycin (simulated AUC0-inf ratio of 1.7), both common comedications in the intended patient populations. PBPK and static mechanistic models were also used to predict a negligible perpetrator DDI effect for nemiralisib on other P4503A4 substrates, including midazolam (a sensitive probe substrate of P4503A4) and theophylline (a narrow therapeutic index drug and another common comedication). In summary, an integrated in silico, in vitro, and clinical approach including an inhalation PBPK model has successfully discharged any potential patient DDI risks in future nemiralisib clinical trials. SIGNIFICANCE STATEMENT: This paper describes the integration of in silico, in vitro, and clinical data to successfully discharge potential drug-drug interaction risks for a low-dose inhaled drug. This work featured assessment of victim and perpetrator risks of drug transporters and cytochrome P450 enzymes, utilizing empirical and mechanistic approaches combined with clinical data (drug interaction and human absorption, metabolism, and pharmacokinetics) and physiologically based pharmacokinetic modeling approaches to facilitate bespoke risk assessment in target patient populations.

Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations.

Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling.

Clinical Extrapolation of the Effects of Dolutegravir and Other HIV Integrase Inhibitors on Folate Transport Pathways.

Preliminary analysis of ongoing birth surveillance study identified evidence of potential increased risk for neural tube defects (NTDs) in newborns associated with exposure to dolutegravir at the time of conception. Folate deficiency is a common cause of NTDs. Dolutegravir and other HIV integrase inhibitor drugs were evaluated in vitro for inhibition of folate transport pathways: proton-coupled folate transporter (PCFT), reduced folate carrier (RFC), and folate receptor α (FRα)-mediated endocytosis. Inhibition of folate transport was extrapolated to the clinic by using established approaches for transporters in intestine, distribution tissues, and basolateral and apical membranes of renal proximal tubules (2017 FDA Guidance). The positive controls, methotrexate and pemetrexed, demonstrated clinically relevant inhibition of PCFT, RFC, and FRα in folate absorption, distribution, and renal sparing. Valproic acid was used as a negative control that elicits folate-independent NTDs; valproic acid did not inhibit PCFT, RFC, or FRα At clinical doses and exposures, the observed in vitro inhibition of FRα by dolutegravir and cabotegravir was not flagged as clinically relevant; PCFT and RFC inhibition was not observed in vitro. Bictegravir inhibited both PCFT and FRα, but the observed inhibition did not reach the criteria for clinical relevance. Elvitegravir and raltegravir inhibited PCFT, but only raltegravir inhibition of intestinal PCFT was flagged as potentially clinically relevant at the highest 1.2-g dose (not the 400-mg dose). These studies showed that dolutegravir is not a clinical inhibitor of folate transport pathways, and it is not predicted to elicit clinical decreases in maternal and fetal folate levels. Clinically relevant HIV integrase inhibitor drug class effect on folate transport pathways was not observed. SIGNIFICANCE STATEMENT: Preliminary analysis of ongoing birth surveillance study identified evidence of potential increased risk for neural tube defects (NTDs) in newborns associated with exposure to the HIV integrase inhibitor dolutegravir at the time of conception; folate deficiency is a common cause of NTDs. Dolutegravir and other HIV integrase inhibitor drugs were evaluated in vitro for inhibition of the major folate transport pathways: proton-coupled folate transporter, reduced folate carrier, and folate receptor α-mediated endocytosis. The present studies showed that dolutegravir is not a clinical inhibitor of folate transport pathways, and it is not predicted to elicit clinical decreases in maternal and fetal folate levels. Furthermore, clinically relevant HIV integrase inhibitor drug class effect on folate transport pathways was not observed.

Can Bile Salt Export Pump Inhibition Testing in Drug Discovery and Development Reduce Liver Injury Risk? An International Transporter Consortium Perspective.

Bile salt export pump (BSEP) inhibition has emerged as an important mechanism that may contribute to the initiation of human drug-induced liver injury (DILI). Proactive evaluation and understanding of BSEP inhibition is recommended in drug discovery and development to aid internal decision making on DILI risk. BSEP inhibition can be quantified using in vitro assays. When interpreting assay data, it is important to consider in vivo drug exposure. Currently, this can be undertaken most effectively by consideration of total plasma steady state drug concentrations (Css,plasma ). However, because total drug concentrations are not predictive of pharmacological effect, the relationship between total exposure and BSEP inhibition is not causal. Various follow-up studies can aid interpretation of in vitro BSEP inhibition data and may be undertaken on a case-by-case basis. BSEP inhibition is one of several mechanisms by which drugs may cause DILI, therefore, it should be considered alongside other mechanisms when evaluating possible DILI risk.