Hepatic OATP1B zonal distribution: Implications for rifampicin-mediated drug-drug interactions explored within a PBPK framework.

OATP1B facilitates the uptake of xenobiotics into hepatocytes and is a prominent target for drug-drug interactions (DDIs). Reduced systemic exposure of OATP1B substrates has been reported following multiple-dose rifampicin; one explanation for this observation is OATP1B induction. Non-uniform hepatic distribution of OATP1B may impact local rifampicin tissue concentrations and rifampicin-mediated protein induction, which may affect the accuracy of transporter- and/or metabolizing enzyme-mediated DDI predictions. We incorporated quantitative zonal OATP1B distribution data from immunofluorescence imaging into a PBPK modeling framework to explore rifampicin interactions with OATP1B and CYP substrates. PBPK models were developed for rifampicin, two OATP1B substrates, pravastatin and repaglinide (also metabolized by CYP2C8/CYP3A4), and the CYP3A probe, midazolam. Simulated hepatic uptake of pravastatin and repaglinide increased from the periportal to the pericentral region (approximately 2.1-fold), consistent with OATP1B distribution data. Simulated rifampicin unbound intracellular concentrations increased in the pericentral region (1.64-fold) compared to simulations with uniformly distributed OATP1B. The absolute average fold error of the rifampicin PBPK model for predicting substrate maximal concentration (Cmax) and area under the plasma concentration-time curve (AUC) ratios was 1.41 and 1.54, respectively (nine studies). In conclusion, hepatic OATP1B distribution has a considerable impact on simulated zonal substrate uptake clearance values and simulated intracellular perpetrator concentrations, which regulate transporter and metabolic DDIs. Additionally, accounting for rifampicin-mediated OATP1B induction in parallel with inhibition improved model predictions. This study provides novel insight into the effect of hepatic OATP1B distribution on site-specific DDI predictions and the impact of accounting for zonal transporter distributions within PBPK models.

How PBPK Can Help to Understand Old Drugs and Inform their Dosing in Elderly: Amantadine Case Study.

Amantadine, despite being on the market for 55 years, has several unknown aspects of its pharmacokinetics especially related to the influence of covariates such as age, disease, or interactions linked to amantadine's renal elimination. As amantadine is used in Parkinson's disease and is considered a potential candidate in COVID treatment and other diseases, there is an unmet need for thorough understanding of its pharmacokinetic in special populations, such as the elderly. We aimed to mechanistically describe amantadine pharmacokinetics in healthy subjects and shed some light on the differences in drug behavior between healthy volunteers (18-65 years) and an elderly/geriatric population (65-98 years) using PBPK modeling and simulation. The middle-out PBPK model includes mechanistic description of drug renal elimination, specifically an organic cation transporter (OCT)2-mediated electrogenic bidirectional transport (basolateral) and multidrug and toxic compound extrusion (MATE)1-mediated efflux (apical). The model performance was verified against plasma and urine data reported after single and multiple dose administration in healthy volunteers and elderly patients from 18 independent studies. The ratios of predicted vs. observed maximal plasma concentration and area under the concentration-time curve values were within 1.25-fold. The model illustrates that renal transporter activity is expected to decrease in healthy elderly compared to healthy volunteers, which is in line with literature proteomic data for OCT2. The model was applied to assess the potential of reaching toxicity-related plasma concentrations in different age groups of geriatric subjects.

Alterations in zonal distribution and plasma membrane localization of hepatocyte bile acid transporters in patients with NAFLD.

BACKGROUND: NAFLD is highly prevalent with limited treatment options. Bile acids (BAs) increase in the systemic circulation and liver during NAFLD progression. Changes in plasma membrane localization and zonal distribution of BA transporters can influence transport function and BA homeostasis. However, a thorough characterization of how NAFLD influences these factors is currently lacking. This study aimed to evaluate the impact of NAFLD and the accompanying histologic features on the functional capacity of key hepatocyte BA transporters across zonal regions in human liver biopsies. METHODS: A novel machine learning image classification approach was used to quantify relative zonal abundance and plasma membrane localization of BA transporters (bile salt export pump [BSEP], sodium-taurocholate cotransporting polypeptide, organic anion transporting polypeptide [OATP] 1B1 and OATP1B3) in non-diseased (n = 10), NAFL (n = 9), and NASH (n = 11) liver biopsies. Based on these data, membrane-localized zonal abundance (MZA) measures were developed to estimate transporter functional capacity. RESULTS: NAFLD diagnosis and histologic scoring were associated with changes in transporter membrane localization and zonation. Increased periportal BSEPMZA (mean proportional difference compared to non-diseased liver of 0.090) and decreased pericentral BSEPMZA (-0.065) were observed with NASH and also in biopsies with higher histologic scores. Compared to Non-diseased Liver, periportal OATP1B3MZA was increased in NAFL (0.041) and NASH (0.047). Grade 2 steatosis (mean proportional difference of 0.043 when compared to grade 0) and grade 1 lobular inflammation (0.043) were associated with increased periportal OATP1B3MZA. CONCLUSIONS: These findings provide novel mechanistic insight into specific transporter alterations that impact BA homeostasis in NAFLD. Changes in BSEPMZA likely contribute to altered BA disposition and pericentral microcholestasis previously reported in some patients with NAFLD. BSEPMZA assessment could inform future development and optimization of NASH-related pharmacotherapies.

Physiologically Based Pharmacokinetic Modeling for Maribavir to Inform Dosing in Drug-Drug Interaction Scenarios with CYP3A4 Inducers and Inhibitors.

Maribavir, an orally available antiviral agent, has been approved in multiple countries for the treatment of patients with refractory post-transplant cytomegalovirus (CMV) infection and/or disease. Maribavir is primarily metabolized by CYP3A4; coadministration with CYP3A4 inducers and inhibitors may significantly alter maribavir exposure, thereby affecting its efficacy and safety. The effect of CYP3A4 inducers and inhibitors on maribavir exposure was evaluated based on a drug-drug interaction (DDI) study and physiologically-based pharmacokinetic (PBPK) modeling. The effect of rifampin (a strong inducer of CYP3A4 and moderate inducer of CYP1A2), administered at a 600 mg dose once daily, on maribavir pharmacokinetics was assessed in a clinical phase 1 DDI study in healthy participants. A full PBPK model for maribavir was developed and verified using in vitro and clinical pharmacokinetic data from phase 1 studies. The verified PBPK model was then used to simulate maribavir DDI interactions with various CYP3A4 inducers and inhibitors. The DDI study results showed that coadministration with rifampin decreased the maribavir maximum plasma concentration (Cmax ), area under the plasma concentration-time curve (AUC), and trough concentration (Ctrough ) by 39%, 60%, and 82%, respectively. Based on the results from the clinical DDI study, the coadministration of maribavir with rifampin is not recommended. The PBPK model did not predict a clinically significant effect of CYP3A4 inhibitors on maribavir exposure; however, it predicted that strong or moderate CYP3A4 inducers, including carbamazepine, efavirenz, phenobarbital, and phenytoin, may reduce maribavir exposure to a clinically significant extent, and may prompt the consideration of a maribavir dosing increase, in accordance with local approved labels and/or regulations.

Interlaboratory Variability in the Madin-Darby Canine Kidney Cell Proteome.

Madin-Darby canine kidney (MDCK) cells are widely used to study epithelial cell functionality. Their low endogenous drug transporter protein levels make them an amenable system to investigate transepithelial permeation and drug transporter protein activity after their transfection. MDCK cells display diverse phenotypic traits, and as such, laboratory-to-laboratory variability in drug permeability assessments is observed. Consequently, in vitro-in vivo extrapolation (IVIVE) approaches using permeability and/or transporter activity data require calibration. A comprehensive proteomic quantification of 11 filter-grown parental or mock-transfected MDCK monolayers from 8 different pharmaceutical laboratories using the total protein approach (TPA) is provided. The TPA enables estimations of key morphometric parameters such as monolayer cellularity and volume. Overall, metabolic liability to xenobiotics is likely to be limited for MDCK cells due to the low expression of required enzymes. SLC16A1 (MCT1) was the highest abundant SLC transporter linked to xenobiotic activity, while ABCC4 (MRP4) was the highest abundant ABC transporter. Our data supports existing findings that claudin-2 levels may be linked to tight junction modulation, thus impacting trans-epithelial resistance. This unique database provides data on more than 8000 protein copy numbers and concentrations, thus allowing an in-depth appraisal of the control monolayers used in each laboratory.

Considerations for Physiologically Based Modeling in Liver Disease: From Nonalcoholic Fatty Liver (NAFL) to Nonalcoholic Steatohepatitis (NASH).

Nonalcoholic fatty liver disease (NAFLD), representing a clinical spectrum ranging from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH), is rapidly evolving into a global pandemic. Patients with NAFLD are burdened with high rates of metabolic syndrome-related comorbidities resulting in polypharmacy. Therefore, it is crucial to gain a better understanding of NAFLD-mediated changes in drug disposition and efficacy/toxicity. Despite extensive clinical pharmacokinetic data in cirrhosis, current knowledge concerning pharmacokinetic alterations in NAFLD, particularly at different stages of disease progression, is relatively limited. In vitro-to-in vivo extrapolation coupled with physiologically based pharmacokinetic and pharmacodynamic (IVIVE-PBPK/PD) modeling offers a promising approach for optimizing pharmacologic predictions while refining and reducing clinical studies in this population. Use of IVIVE-PBPK to predict intra-organ drug concentrations at pharmacologically relevant sites of action is particularly advantageous when it can be linked to pharmacodynamic effects. Quantitative systems pharmacology/toxicology (QSP/QST) modeling can be used to translate pharmacokinetic and pharmacodynamic data from PBPK/PD models into clinically relevant predictions of drug response and toxicity. In this review, a detailed summary of NAFLD-mediated alterations in human physiology relevant to drug absorption, distribution, metabolism, and excretion (ADME) is provided. The application of literature-derived physiologic parameters and ADME-associated protein abundance data to inform virtual NAFLD population development and facilitate PBPK/PD, QSP, and QST predictions is discussed along with current limitations of these methodologies and knowledge gaps. The proposed methodologic framework offers great potential for meaningful prediction of pharmacological outcomes in patients with NAFLD and can inform both drug development and clinical practice for this population.

Non-specific binding of compounds in in vitro metabolism assays: a comparison of microsomal and hepatocyte binding in different species and an assessment of the accuracy of prediction models.

Non-specific binding in in vitro metabolism systems leads to an underestimation of the true intrinsic metabolic clearance of compounds being studied. Therefore in vitro binding needs to be accounted for when extrapolating in vitro data to predict the in vivo metabolic clearance of a compound. While techniques exist for experimentally determining the fraction of a compound unbound in in vitro metabolism systems, early in drug discovery programmes computational approaches are often used to estimate the binding in the in vitro system.Experimental fraction unbound data (n = 60) were generated in liver microsomes (fumic) from five commonly used pre-clinical species (rat, mouse, dog, minipig, monkey) and humans. Unbound fraction in incubations with mouse, rat or human hepatocytes was determined for the same 60 compounds. These data were analysed to determine the relationship between experimentally determined binding in the different matrices and across different species. In hepatocytes there was a good correlation between fraction unbound in human and rat (r2=0.86) or mouse (r2=0.82) hepatocytes. Similar correlations were observed between binding in human liver microsomes and microsomes from rat, mouse, dog, Göttingen minipig or monkey liver microsomes (r2 of >0.89, n = 51 - 52 measurements in different species). Physicochemical parameters (logP, pKa and logD) were predicted for all evaluated compounds. In addition, logP and/or logD were measured for a subset of compounds.Binding to human hepatocytes predicted using 5 different methods was compared to the measured data for a set of 59 compounds. The best methods evaluated used measured microsomal binding in human liver microsomes to predict hepatocyte binding. The collated physicochemical data were used to predict the human fumic using four different in silico models for a set of 53-60 compounds. The correlation (r2) and root mean square error between predicted and observed microsomal binding was 0.69 & 0.20, 0.47 & 0.23, 0.56 & 0.21 and 0.54 & 0.26 for the Turner-Simcyp, Austin, Hallifax-Houston and Poulin models, respectively. These analyses were extended to include measured literature values for binding in human liver microsomes for a larger set of compounds (n=697). For the larger dataset of compounds, microsomal binding was well predicted for neutral compounds (r2=0.67 - 0.70) using the Poulin, Austin, or Turner-Simcyp methods but not for acidic or basic compounds (r2<0.5) using any of the models. While the lipophilicity-based models can be used, the in vitro binding should be measured for compounds where more certainty is needed, using appropriately calibrated assays and possibly established weak, moderate, and strong binders as reference compounds to allow comparison across databases.

Performance Verification of CYP2C19 Enzyme Abundance Polymorphism Settings within the Simcyp Simulator v21.

Physiologically based pharmacokinetic (PBPK) modeling has a number of applications, including assessing drug−drug interactions (DDIs) in polymorphic populations, and should be iteratively refined as science progresses. The Simcyp Simulator is annually updated and version 21 included updates to hepatic and intestinal CYP2C19 enzyme abundance, including addition of intermediate and rapid metabolizer phenotypes and changes to the ultra-rapid metabolizer enzyme abundance, with implications for population clearance and DDI predictions. This work details verification of the updates with sensitive CYP2C19 substrates, omeprazole and lansoprazole, using available clinical data from literature. Multiple assessments were performed, including recovery of areas under the concentration-time curve (AUC) and Cmax from compiled datasets for each drug, recovery of victim DDI ratios with CYP2C19 and/or CYP3A4 inhibition and recovery of relative exposure between phenotypes. Simulated data were within respective acceptance criteria for >80% of omeprazole AUC values, >70% of lansoprazole AUC and Cmax, >60% of AUC and Cmax DDI ratios and >80% of exposure ratios between different phenotypes. Recovery of omeprazole Cmax was lower (>50−70% within 2-fold) and possibly attributed to the variety of formulations used in the clinical dataset. Overall, the results demonstrated that the updated data used to parameterize CYP2C19 phenotypes reasonably described the pharmacokinetics of omeprazole and lansoprazole in genotyped or phenotyped individuals.

Transporter Regulation in Critical Protective Barriers: Focus on Brain and Placenta.

Drug transporters play an important role in the maintenance of chemical balance and homeostasis in different tissues. In addition to their physiological functions, they are crucial for the absorption, distribution, and elimination of many clinically important drugs, thereby impacting therapeutic efficacy and toxicity. Increasing evidence has demonstrated that infectious, metabolic, inflammatory, and neurodegenerative diseases alter the expression and function of drug transporters. However, the current knowledge on transporter regulation in critical protective barriers, such as the brain and placenta, is still limited and requires more research. For instance, while many studies have examined P-glycoprotein, it is evident that research on the regulation of highly expressed transporters in the blood-brain barrier and blood-placental barrier are lacking. The aim of this review is to summarize the currently available literature in order to better understand transporter regulation in these critical barriers.

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.

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.

Prediction of CYP-mediated DDIs involving inhibition: Approaches to address the requirements for system qualification of the Simcyp Simulator.

Physiologically-based pharmacokinetic (PBPK) modeling is being increasingly used in drug development to avoid unnecessary clinical drug-drug interaction (DDI) studies and inform drug labels. Thus, regulatory agencies are recommending, or indeed requesting, more rigorous demonstration of the prediction accuracy of PBPK platforms in the area of their intended use. We describe a framework for qualification of the Simcyp Simulator with respect to competitive and mechanism-based inhibition (MBI) of CYP1A2, CYP2D6, CYP2C8, CYP2C9, CYP2C19, and CYP3A4/5. Initially, a DDI matrix, consisting of a range of weak, moderate, and strong inhibitors and substrates with varying fraction metabolized by specific CYP enzymes that were susceptible to different degrees of inhibition, were identified. Simulations were run with 123 clinical DDI studies involving competitive inhibition and 78 clinical DDI studies involving MBI. For competitive inhibition, the overall prediction accuracy was good with an average fold error (AFE) of 0.91 and 0.92 for changes in the maximum plasma concentration (Cmax ) and area under the plasma concentration (AUC) time profile, respectively, as a consequence of the DDI. For MBI, an AFE of 1.03 was determined for both Cmax and AUC. The prediction accuracy was generally comparable across all CYP enzymes, irrespective of the isozyme and mechanism of inhibition. These findings provide confidence in application of the Simcyp Simulator (V19 R1) for assessment of the DDI potential of drugs in development either as inhibitors or victim drugs of CYP-mediated interactions. The approach described herein and the identified DDI matrix can be used to qualify subsequent versions of the platform.

Regulation of Drug Transport Proteins-From Mechanisms to Clinical Impact: A White Paper on Behalf of the International Transporter Consortium.

Membrane transport proteins are involved in the absorption, disposition, efficacy, and/or toxicity of many drugs. Numerous mechanisms (e.g., nuclear receptors, epigenetic gene regulation, microRNAs, alternative splicing, post-translational modifications, and trafficking) regulate transport protein levels, localization, and function. Various factors associated with disease, medications, and dietary constituents, for example, may alter the regulation and activity of transport proteins in the intestine, liver, kidneys, brain, lungs, placenta, and other important sites, such as tumor tissue. This white paper reviews key mechanisms and regulatory factors that alter the function of clinically relevant transport proteins involved in drug disposition. Current considerations with in vitro and in vivo models that are used to investigate transporter regulation are discussed, including strengths, limitations, and the inherent challenges in predicting the impact of changes due to regulation of one transporter on compensatory pathways and overall drug disposition. In addition, translation and scaling of in vitro observations to in vivo outcomes are considered. The importance of incorporating altered transporter regulation in modeling and simulation approaches to predict the clinical impact on drug disposition is also discussed. Regulation of transporters is highly complex and, therefore, identification of knowledge gaps will aid in directing future research to expand our understanding of clinically relevant molecular mechanisms of transporter regulation. This information is critical to the development of tools and approaches to improve therapeutic outcomes by predicting more accurately the impact of regulation-mediated changes in transporter function on drug disposition and response.

Guide to development of compound files for PBPK modeling in the Simcyp population-based simulator.

The Simcyp Simulator is a software platform for population physiologically-based pharmacokinetic (PBPK) modeling and simulation. It links in vitro data to in vivo absorption, distribution, metabolism, excretion and pharmacokinetic/pharmacodynamic outcomes to explore clinical scenarios and support drug development decisions, including regulatory submissions and drug labels. This tutorial describes the different input parameters required, as well as the considerations needed when developing a PBPK model within the Simulator, for a small molecule intended for oral administration. A case study showing the development and application of a PBPK model for ondansetron is herein used to aid the understanding of different PBPK model development concepts.

In Vitro to In Vivo Extrapolation Linked to Physiologically Based Pharmacokinetic Models for Assessing the Brain Drug Disposition.

Drug development for the central nervous system (CNS) is a complex endeavour with low success rates, as the structural complexity of the brain and specifically the blood-brain barrier (BBB) poses tremendous challenges. Several in vitro brain systems have been evaluated, but the ultimate use of these data in terms of translation to human brain concentration profiles remains to be fully developed. Thus, linking up in vitro-to-in vivo extrapolation (IVIVE) strategies to physiologically based pharmacokinetic (PBPK) models of brain is a useful effort that allows better prediction of drug concentrations in CNS components. Such models may overcome some known aspects of inter-species differences in CNS drug disposition. Required physiological (i.e. systems) parameters in the model are derived from quantitative values in each organ. However, due to the inability to directly measure brain concentrations in humans, compound-specific (drug) parameters are often obtained from in silico or in vitro studies. Such data are translated through IVIVE which could be also applied to preclinical in vivo observations. In such exercises, the limitations of the assays and inter-species differences should be adequately understood in order to verify these predictions with the observed concentration data. This report summarizes the state of IVIVE-PBPK-linked models and discusses shortcomings and areas of further research for better prediction of CNS drug disposition. Graphical abstract.

Application of proteomic data in the translation of in vitro observations to associated clinical outcomes.

Translation of information on drug exposure and effect is facilitated by in silico models that enable extrapolation of in vitro measurements to in vivo clinical outcomes. These models integrate drug-specific data with information describing physiological processes and pathological changes, including alterations to proteins involved in drug absorption, distribution and elimination. Over the past 15 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. In this review, we explore current and emerging applications of targeted and global (untargeted) proteomics in translational pharmacology as well as strategies for improved integration into model-based drug development.

Unraveling pleiotropic effects of rifampicin by using physiologically based pharmacokinetic modeling: Assessing the induction magnitude of P-glycoprotein-cytochrome P450 3A4 dual substrates.

Rifampicin induces both P-glycoprotein (P-gp) and cytochrome P450 3A4 (CYP3A4) through regulating common nuclear receptors (e.g., pregnane X receptor). The interplay of P-gp and CYP3A4 has emerged to be an important factor in clinical drug-drug interactions (DDIs) with P-gp-CYP3A4 dual substrates and requires qualitative and quantitative understanding. Although physiologically based pharmacokinetic (PBPK) modeling has become a widely accepted approach to assess DDIs and is able to reasonably predict DDIs caused by CYP3A4 induction and P-gp induction individually, the predictability of PBPK models for the effect of simultaneous P-gp and CYP3A4 induction on P-gp-CYP3A4 dual substrates remains to be systematically evaluated. In this study, we used a PBPK modeling approach for the assessment of DDIs between rifampicin and 12 drugs: three sensitive P-gp substrates, seven P-gp-CYP3A4 dual substrates, and two P-gp-CYP3A4 dual substrates and inhibitors. A 3.5-fold increase of intestinal P-gp abundance was incorporated in the PBPK models to account for rifampicin-mediated P-gp induction at steady state. The simulation results showed that accounting for P-gp induction in addition to CYP3A4 induction improved the prediction accuracy of the area under the concentration-time curve and maximum (peak) plasma drug concentration ratios compared with considering CYP3A4 induction alone. Furthermore, the interplay of relevant drug-specific parameters and its impact on the magnitude of DDIs were evaluated using sensitivity analysis. The PBPK approach described herein, in conjunction with robust in vitro and clinical data, can help in the prospective assessment of DDIs involving other P-gp and CYP3A4 dual substrates. The database reported in the present study provides a valuable aid in understanding the combined effect of P-gp and CYP3A4 induction during drug development.

Comparison of Canine and Human Physiological Factors: Understanding Interspecies Differences that Impact Drug Pharmacokinetics.

This review is a summary of factors affecting the drug pharmacokinetics (PK) of dogs versus humans. Identifying these interspecies differences can facilitate canine-human PK extrapolations while providing mechanistic insights into species-specific drug in vivo behavior. Such a cross-cutting perspective can be particularly useful when developing therapeutics targeting diseases shared between the two species such as cancer, diabetes, cognitive dysfunction, and inflammatory bowel disease. Furthermore, recognizing these differences also supports a reverse PK extrapolations from humans to dogs. To appreciate the canine-human differences that can affect drug absorption, distribution, metabolism, and elimination, this review provides a comparison of the physiology, drug transporter/enzyme location, abundance, activity, and specificity between dogs and humans. Supplemental material provides an in-depth discussion of certain topics, offering additional critical points to consider. Based upon an assessment of available state-of-the-art information, data gaps were identified. The hope is that this manuscript will encourage the research needed to support an understanding of similarities and differences in human versus canine drug PK.

Food constituent- and herb-drug interactions in oncology: Influence of quantitative modelling on Drug labelling.

AIMS: Herbal products, spices and/or fruits are perceived as inherently healthy; for instance, St. John's wort (SJW) is marketed as a natural antidepressant and patients often self-administer it concomitantly with oncology medications. However, food constituents/herbs can interfere with drug pharmacokinetics, with risk of altering pharmacodynamics and efficacy. The objective of this work was to develop a strategy to prioritize herb- or food constituent-drug interactions (FC-DIs) to better assess oncology drug clinical risk. METHODS: Physiologically based pharmacokinetic (PBPK) models were developed by integrating in vitro parameters with the clinical pharmacokinetics of food constituents in grapefruit juice (bergamottin), turmeric (curcumin) or SJW (hyperforin). Perpetrator files were linked to verified victim PBPK models through appropriate interaction mechanisms (cytochrome P450 3A, breast cancer resistance protein, P-glycoprotein) and applied in prospective PBPK simulations to inform the likelihood and magnitude of changes in exposure to osimertinib, olaparib or acalabrutinib. RESULTS: Reported FC-DIs with oncology drugs were well recovered, with absolute average fold error values of 1.10 (bergamottin), 1.05 (curcumin) and 1.01 (hyperforin). Prospective simulations with grapefruit juice and turmeric showed clinically minor to insignificant changes in exposure (<1.50-fold) to acalabrutinib, osimertinib and olaparib, but predicted 1.57-fold FC-DI risk between acalabrutinib and curcumin. Moderate DDI risk was expected when acalabrutinib, osimertinib or olaparib were dosed with SJW. CONCLUSIONS: A model-informed decision tree based on mechanistic understanding of transporter and/or enzyme-mediated FC-DI is proposed based on bergamottin, curcumin and hyperforin FC-DI clinical data. Adopting this quantitative modelling approach should streamline herbal product safety assessments, assist in FC-DI management, and ultimately promote safe clinical use of oncology drugs.

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.