Toward improved predictions of pharmacokinetics of transported drugs in hepatic impairment: Insights from the extended clearance model.

Hepatic impairment (HI) moderately (<5-fold) affects the systemic exposure (i.e., area under the plasma concentration-time curve [AUC]) of drugs that are substrates of the hepatic sinusoidal organic anion transporting polypeptide (OATP) transporters and are excreted unchanged in the bile and/or urine. However, the effect of HI on their AUC is much greater (>10-fold) for drugs that are also substrates of cytochrome P450 (CYP) 3A enzymes. Using the extended clearance model, through simulations, we identified the ratio of sinusoidal efflux clearance (CL) over the sum of metabolic and biliary CLs as important in predicting the impact of HI on the AUC of dual OATP/CYP3A substrates. Because HI may reduce hepatic CYP3A-mediated CL to a greater extent than biliary efflux CL, the greater the contribution of the former versus the latter, the greater the impact of HI on drug AUC ratio (AUCRHI ). Using physiologically-based pharmacokinetic modeling and simulation, we predicted relatively well the AUCRHI of OATP substrates that are not significantly metabolized (pitavastatin, rosuvastatin, valsartan, and gadoxetic acid). However, there was a trend toward underprediction of the AUCRHI of the dual OATP/CYP3A4 substrates fimasartan and atorvastatin. These predictions improved when the sinusoidal efflux CL of these two drugs was increased in healthy volunteers (i.e., before incorporating the effect of HI), and by modifying the directionality of its modulation by HI (i.e., increase or decrease). To accurately predict the effect of HI on AUC of hepatobiliary cleared drugs it is important to accurately predict all hepatobiliary pathways, including sinusoidal efflux CL.

A Physiologically-Based Pharmacokinetic Model for Cannabidiol in Healthy Adults, Hepatically-Impaired Adults, and Children.

Cannabidiol (CBD) is available as a prescription oral drug that is indicated for the treatment of some types of epilepsy in children and adults. CBD is also available over-the-counter and is used to self-treat a variety of other ailments, including pain, anxiety, and insomnia. Accordingly, CBD may be consumed with other medications, resulting in possible CBD-drug interactions. Such interactions can be predicted in healthy and hepatically-impaired (HI) adults and in children through physiologically based pharmacokinetic (PBPK) modeling and simulation. These PBPK models must be populated with CBD-specific parameters, including the enzymes that metabolize CBD in adults. In vitro reaction phenotyping experiments showed that UDP-glucuronosyltransferases (UGTs, 80%), particularly UGT2B7 (64%), were the major contributors to CBD metabolism in adult human liver microsomes. Among the cytochrome P450s (CYPs) tested, CYP2C19 (5.7%) and CYP3A (6.5%) were the major CYPs responsible for CBD metabolism. Using these and other physicochemical parameters, a CBD PBPK model was developed and validated for healthy adults. This model was then extended to predict CBD systemic exposure in HI adults and children. Our PBPK model successfully predicted CBD systemic exposure in both populations within 0.5- to 2-fold of the observed values. In conclusion, we developed and validated a PBPK model to predict CBD systemic exposure in healthy and HI adults and children. This model can be used to predict CBD-drug or CBD-drug-disease interactions in these populations. SIGNIFICANCE STATEMENT: Our PBPK model successfully predicted CBD systemic exposure in healthy and hepatically-impaired adults, as well as children with epilepsy. This model could be used in the future to predict CBD-drug or CBD-drug-disease interactions in these special populations.

Predicting changes in the pharmacokinetics of CYP3A-metabolized drugs in hepatic impairment and insights into factors driving these changes.

Physiologically based pharmacokinetic models, populated with drug-metabolizing enzyme and transporter (DMET) abundance, can be used to predict the impact of hepatic impairment (HI) on the pharmacokinetics (PK) of drugs. To increase confidence in the predictive power of such models, they must be validated by comparing the predicted and observed PK of drugs in HI obtained by phenotyping (or probe drug) studies. Therefore, we first predicted the effect of all stages of HI (mild to severe) on the PK of drugs primarily metabolized by cytochrome P450 (CYP) 3A enzymes using the default HI module of Simcyp Version 21, populated with hepatic and intestinal CYP3A abundance data. Then, we validated the predictions using CYP3A probe drug phenotyping studies conducted in HI. Seven CYP3A substrates, metabolized primarily via CYP3A (fraction metabolized, 0.7-0.95), with low to high hepatic availability, were studied. For all stages of HI, the predicted PK parameters of drugs were within twofold of the observed data. This successful validation increases confidence in using the DMET abundance data in HI to predict the changes in the PK of drugs cleared by DMET for which phenotyping studies in HI are not available or cannot be conducted. In addition, using CYP3A drugs as an example, through simulations, we identified the salient PK factors that drive the major changes in exposure (area under the plasma concentration-time profile curve) to drugs in HI. This theoretical framework can be applied to any drug and DMET to quickly determine the likely magnitude of change in drug PK due to HI.

The next frontier in ADME science: Predicting transporter-based drug disposition, tissue concentrations and drug-drug interactions in humans.

Predicting transporter-based drug clearance (CL) and tissue concentrations (TC) in humans is important to reduce the risk of failure during drug development. In addition, when transporters are present at the tissue:blood interface (e.g., in the liver, blood-brain barrier), predicting TC is important to predict the drug's efficacy and safety. With the advent of quantitative targeted proteomics, in vitro to in vivo extrapolation (IVIVE) of transporter-based drug CL and TC is now possible using transporter-expressing models (cells lines, membrane vesicles) and the in vivo to in vitro relative expression of transporters (REF) as a scaling factor. Unlike other approaches based on physiological scaling, the REF approach is not dependent on the availability of primary cells. Here, we review the REF approach and compare it with other IVIVE approaches such as the relative activity factor approach and physiological scaling. For each of these scaling approaches, we review their underlying principles, assumptions, methodology, predictive performance, as well as advantages and limitations. Finally, we discuss current gaps in IVIVE of transporter-based CL and TC and propose possible reasons for these gaps as well as areas to investigate to bridge these gaps.

Predicting Regional Respiratory Tissue and Systemic Concentrations of Orally Inhaled Drugs through a Novel PBPK Model.

Oral inhalation (OI) of drugs is the route of choice to treat respiratory diseases or for recreational drug use (e.g., cannabis). After OI, the drug is deposited in and systemically absorbed from various regions of the respiratory tract. Measuring regional respiratory tissue drug concentrations at the site of action is important for evaluating the efficacy and safety of orally inhaled drugs (OIDs). Because such a measurement is routinely not possible in humans, the only alternative is to predict these concentrations, for example by physiologically based pharmacokinetic (PBPK) modeling. Therefore, we developed an OI-PBPK model to integrate the interplay between regional respiratory drug deposition and systemic absorption to predict regional respiratory tissue and systemic drug concentrations. We validated our OI-PBPK model by comparing the simulated and observed plasma concentration-time profiles of two OIDs, morphine and nicotine. Furthermore, we performed sensitivity analyses to quantitatively demonstrate the impact of key parameters on the extent and pattern of regional respiratory drug deposition, absorption, and the resulting regional respiratory tissue and systemic plasma concentrations. Our OI-PBPK model can be applied to predict regional respiratory tissue and systemic drug concentrations to optimize OID formulations, delivery systems, and dosing regimens. Furthermore, our model could be used to establish the bioequivalence of generic OIDs for which systemic plasma concentrations are not measurable or are not a good surrogate of the respiratory tissue drug concentrations. SIGNIFICANCE STATEMENT: Our OI-PBPK model is the first comprehensive model to predict regional respiratory deposition, as well as systemic and regional tissue concentrations of OIDs, especially at the drug's site of action, which is difficult to measure in humans. This model will help optimize OID formulations, delivery systems, dosing regimens, and bioequivalence assessment of generic OID. Furthermore, this model can be linked with organs-on-chips, pharmacodynamic and quantitative systems pharmacology models to predict and evaluate the safety and efficacy of OID.

Exploration of the Plausible Mechanism of Ethambutol Induced Ocular Toxicity by Using Proteomics Informed Physiologically Based Pharmacokinetic (PBPK) Modeling.

PURPOSE: Ethambutol (EMB) is a first-line anti-tubercular drug that is known to cause optic neuropathy. The exact mechanism of its eye toxicity is unknown; however, proposition is metal chelating effect of both EMB and its metabolite 2,2'-(ethylenediamino)-dibutyric acid (EDBA). The latter is formed by sequential metabolism of EMB by alcohol dehydrogenases (ADHs) and aldehyde dehydrogenases (ALDHs). The purpose of this study was to predict the levels of drug and EDBA in the eye using physiologically based pharmacokinetic (PBPK) modeling. METHODS: The PBPK model of EMB was developed using GastroPlus. The intrinsic hepatic clearance of ALDH, calculated by the model, was scaled down using proteomics data to estimate the rate of formation of EDBA in the eye. Additionally, the comparative permeability of EMB and EDBA was assessed by employing in silico and in vitro approaches. The rate of formation of EDBA in the eye and permeability data were then incorporated in a compartmental model to predict the ocular levels of EMB and EDBA. RESULTS: The simulation results of compartmental model highlighted that there was an on-site formation of EDBA upon metabolism of EMB. Furthermore, in silico and in vitro studies revealed that EDBA possessed much lower permeability than EMB. These observations meant that once EDBA was formed in the eye, it was not permeated out and hence achieved higher ocular concentration. CONCLUSION: The on-site formation of EDBA in the eye, its higher local concentration due to lower ocular clearance and its pre-known characteristic to chelate metal species better explains the ocular toxicity shown by EMB.

Estimation of Fetal-to-Maternal Unbound Steady-State Plasma Concentration Ratio of P-Glycoprotein and/or Breast Cancer Resistance Protein Substrate Drugs Using a Maternal-Fetal Physiologically Based Pharmacokinetic Model.

Pregnant women are frequently prescribed drugs to treat chronic diseases such as human immunodeficiency virus infection, but little is known about the benefits and risks of these drugs to the fetus that are driven by fetal drug exposure. The latter can be estimated by fetal-to-maternal unbound plasma concentration at steady state (Kp,uu,fetal). For drugs that are substrates of placental efflux transporters [i.e., P-glycoprotein (P-gp) or breast cancer resistance protein (BCRP)], Kp,uu,fetal is expected to be <1. Here, we estimated the in vivo Kp,uu,fetal of selective P-gp and BCRP substrate drugs by maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) modeling of umbilical vein (UV) plasma and maternal plasma (MP) concentrations obtained simultaneously at term from multiple maternal-fetal dyads. To do so, three drugs were selected: nelfinavir (P-gp substrate), efavirenz (BCRP substrate), and imatinib (P-gp/BCRP substrate). An m-f-PBPK model for each drug was developed and validated for the nonpregnant population and pregnant women using the Simcyp simulator (v20). Then, after incorporating placental passive diffusion clearance, the in vivo Kp,uu,fetal of the drug was estimated by adjusting the placental efflux clearance until the predicted UV/MP values best matched the observed data (Kp,uu,fetal) of nelfinavir = 0.41, efavirenz = 0.39, and imatinib = 0.35. Furthermore, Kp,uu,fetal of nelfinavir and efavirenz at gestational weeks (GWs) 25 and 15 were predicted to be 0.34 and 0.23 (GW25) and 0.33 and 0.27 (GW15). These Kp,uu,fetal values can be used to adjust dosing regimens of these drugs to optimize maternal-fetal drug therapy throughout pregnancy, to assess fetal benefits and risks of these dosing regimens, and to determine if these estimated in vivo Kp,uu,fetal values can be predicted from in vitro studies. SIGNIFICANCE STATEMENT: The in vivo fetal-to-maternal unbound steady-state plasma concentration ratio (Kp,uu,fetal) of nelfinavir [P-glycoprotein (P-gp) substrate], efavirenz [breast cancer resistance protein (BCRP) substrate], and imatinib (P-gp and BCRP substrate) was successfully estimated using maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) modeling. These Kp,uu,fetal values can be used to adjust dosing regimens of these drugs to optimize maternal-fetal drug therapy throughout pregnancy, to assess fetal benefits and risks of these dosing regimens, and to determine if these estimated in vivo Kp,uu,fetal values can be predicted from in vitro studies.

A Tribute to Professor Saranjit Singh - A Critical Thinker, Innovator, Mentor, and Educator.

This commentary presents contributions and accomplishments of Professor Saranjit Singh, National Institute of Pharmaceutical Education and Research (NIPER), SAS Nagar, India, to pharmaceutical research and education. Prof. Singh completed his successful tenure in October 2021. Over his 40+ years of illustrious academic career, he trained 147 Masters and 15 PhD students in the fields of drug stability testing, degradation chemistry, impurity and metabolite characterization, and advanced analytical technologies. He has published ∼250 research articles, reviews, editorials, patent, book, and book chapters, and received numerous awards, including the Professor M.L. Khorana Memorial Lecture Award from the Indian Pharmaceutical Association (IPA) and the Outstanding Analyst and Eminent Analyst awards from the Indian Drug Manufacturers' Association (IDMA). This commentary highlights Prof. Singh's inspiring personal and renowned professional journey, including early life, education, career, accomplishments, as well as his services to academia, industry, and regulatory. By sharing the contributions and accomplishments of Prof. Singh, we strongly believe that his story will inspire the next generation of scientists to continue his legacy to advance the field.

Prediction of Pregnancy-Induced Changes in Secretory and Total Renal Clearance of Drugs Transported by Organic Anion Transporters.

Pregnancy can significantly change the pharmacokinetics of drugs, including those renally secreted by organic anion transporters (OATs). Quantifying these changes in pregnant women is logistically and ethically challenging. Hence, predicting the in vivo plasma renal secretory clearance (CLsec) and renal CL (CLrenal) of OAT drugs in pregnancy is important to design correct dosing regimens of OAT drugs. Here, we first quantified the fold-change in renal OAT activity in pregnant versus nonpregnant individual using available selective OAT probe drug CLrenal data (training dataset; OAT1: tenofovir, OAT2: acyclovir, OAT3: oseltamivir carboxylate). The fold-change in OAT1 activity during the 2nd and 3rd trimester was 2.9 and 1.0 compared with nonpregnant individual, respectively. OAT2 activity increased 3.1-fold during the 3rd trimester. OAT3 activity increased 2.2, 1.7 and 1.3-fold during the 1st, 2nd, and 3rd trimester, respectively. Based on these data, we predicted the CLsec, CLrenal and total clearance ((CLtotal) of drugs in pregnancy, which are secreted by multiple OATs (verification dataset; amoxicillin, pravastatin, cefazolin and ketorolac, R-ketorolac, S-ketorolac). Then, the predicted clearances (CLs) were compared with the observed values. The predicted/observed CLsec, CLrenal, and CLtotal of drugs in pregnancy of all verification drugs were within 0.80-1.25 fold except for CLsec of amoxicillin in the 3rd trimester (0.76-fold) and cefazolin in the 2nd trimester (1.27-fold). Overall, we successfully predicted the CLsec, CLrenal, and CLtotal of drugs in pregnancy that are renally secreted by multiple OATs. This approach could be used in the future to adjust dosing regimens of renally secreted OAT drugs which are administered to pregnant women. SIGNIFICANCE STATEMENT: To the authors' knowledge, this is the first report to successfully predict renal secretory clearance and renal clearance of multiple OAT substrate drugs during pregnancy. The data presented here could be used in the future to adjust dosing regimens of renally secreted OAT drugs in pregnancy. In addition, the mechanistic approach used here could be extended to drugs transported by other renal transporters.

Contribution of Uptake and Efflux Transporters to Oral Pharmacokinetics of Furosemide.

Furosemide is a widely used diuretic for treating excessive fluid accumulation caused by disease conditions like heart failure and liver cirrhosis. Furosemide tablet formulation exhibits variable pharmacokinetics (PK) with bioavailability ranging from 10 to almost 100%. To explain the variable absorption, we integrated the physicochemical, in vitro dissolution, permeability, distribution, and the elimination parameters of furosemide in a physiologically-based pharmacokinetic (PBPK) model. Although the intravenous PBPK model reasonably described the observed in vivo PK data, the reported low passive permeability failed to capture the observed data after oral administration. To mechanistically justify this discrepancy, we hypothesized that transporter-mediated uptake contributes to the oral absorption of furosemide in conjunction with passive permeability. Our in vitro results confirmed that furosemide is a substrate of intestinal breast cancer resistance protein (BCRP), multidrug resistance-associated protein 4 (MRP4), and organic anion transporting polypeptide 2B1 (OATP2B1), but it is not a substrate of P-glycoprotein (P-gp) and MRP2. We then estimated the net transporter-mediated intestinal uptake and integrated it into the PBPK model under both fasting and fed conditions. Our in vitro data and PBPK model suggest that the absorption of furosemide is permeability-limited, and OATP2B1 and MRP4 are important for its permeability across intestinal membrane. Further, as furosemide has been proposed as a probe substrate of renal organic anion transporters (OATs) for assessing clinical drug-drug interactions (DDIs) during drug development, the confounding effects of intestinal transporters identified in this study on furosemide PK should be considered in the clinical transporter DDI studies.

Characterization of stable and reactive metabolites of piperine formed on incubation with human liver microsomes.

Black pepper, though commonly employed as a spice, has many medicinal properties. It consists of volatile oils, alkaloids, pungent resins, etc., of which piperine is a major constituent. Though safe at low doses, piperine causes alteration in the activity of drug metabolising enzymes and transporters at high dose and is known to precipitate liver toxicity. It has a potential to form reactive metabolite(s) (RM) owing to the presence of structural alerts, such as methylenedioxyphenyl (MDP), α, ß-unsaturated carbonyl group (Michael acceptor), and piperidine. The present study was designed to detect and characterize stable and RM(s) of piperine formed on in vitro incubation with human liver microsomes. The investigation of RMs was done with the aid of trapping agents, viz, glutathione (GSH) and N-acetylcysteine (NAC). The samples were analysed by ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UHPLC-HRMS) using Thermo Scientific Q Exactive Plus Orbitrap. Full scan MS followed by data-dependent MS2 (Full MS-ddMS2 ) mode was used to establish mass spectrometric fragmentation pathways of protonated piperine and its metabolites. In total, four stable metabolites and their isomers (M1a-c, M2a-b, M3a-c, and M4a-b) were detected. Their formation involved removal of carbon (3, M1a-c), hydroxylation (2, M2a-b), hydroxylation with hydrogenation (3, M3a-c), and dehydrogenation (2, M4a-b). Out of these metabolites, M1, M2, and M3 are reported earlier in the literature, but their isomers and two M4 variants are novel. In addition, six novel conjugates of RMs, including three GSH conjugates of m/z 579 and three NAC conjugates of m/z 435, were also observed.

A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation.

Population factors such as age, gender, ethnicity, genotype and disease state can cause inter-individual variability in pharmacokinetic (PK) profile of drugs. Primarily, this variability arises from differences in abundance of drug metabolizing enzymes and transporters (DMET) among individuals and/or groups. Hence, availability of compiled data on abundance of DMET proteins in different populations can be useful for developing physiologically based pharmacokinetic (PBPK) models. The latter are routinely employed for prediction of PK profiles and drug interactions during drug development and in case of special populations, where clinical studies either are not feasible or have ethical concerns. Therefore, the main aim of this work was to develop a repository of literature-reported DMET abundance data in various human tissues, which included compilation of information on sample size, technique(s) involved, and the demographic factors. The collation of literature reported data revealed high inter-laboratory variability in abundance of DMET proteins. We carried out unbiased meta-analysis to obtain weighted mean and percent coefficient of variation (%CV) values. The obtained %CV values were then integrated into a PBPK model to highlight the variability in drug PK in healthy adults, taking lamotrigine as a model drug. The validated PBPK model was extrapolated to predict PK of lamotrigine in paediatric and hepatic impaired populations. This study thus exemplifies importance of the DMET protein abundance database, and use of determined values of weighted mean and %CV after meta-analysis in PBPK modelling for the prediction of PK of drugs in healthy and special populations.

Ontogeny of Hepatic Sulfotransferases and Prediction of Age-Dependent Fractional Contribution of Sulfation in Acetaminophen Metabolism.

Cytosolic sulfotransferases (SULTs), including SULT1A, SULT1B, SULT1E, and SULT2A isoforms, play noteworthy roles in xenobiotic and endobiotic metabolism. We quantified the protein abundances of SULT1A1, SULT1A3, SULT1B1, and SULT2A1 in human liver cytosol samples (n = 194) by liquid chromatography-tandem mass spectrometry proteomics. The data were analyzed for their associations by age, sex, genotype, and ethnicity of the donors. SULT1A1, SULT1B1, and SULT2A1 showed significant age-dependent protein abundance, whereas SULT1A3 was invariable across 0-70 years. The respective mean abundances of SULT1A1, SULT1B1, and SULT2A1 in neonatal samples was 24%, 19%, and 38% of the adult levels. Interestingly, unlike UDP-glucuronosyltransferases and cytochrome P450 enzymes, SULT1A1 and SULT2A1 showed the highest abundance during early childhood (1 to <6 years), which gradually decreased by approx. 40% in adolescents and adults. SULT1A3 and SULT1B1 abundances were significantly lower in African Americans compared with Caucasians. Multiple linear regression analysis further confirmed the association of SULT abundances by age, ethnicity, and genotype. To demonstrate clinical application of the characteristic SULT ontogeny profiles, we developed and validated a proteomics-informed physiologically based pharmacokinetic model of acetaminophen. The latter confirmed the higher fractional contribution of sulfation over glucuronidation in the metabolism of acetaminophen in children. The study thus highlights that the ontogeny-based age-dependent fractional contribution (fm) of individual drug-metabolizing enzymes has better potential in prediction of drug-drug interactions and the effect of genetic polymorphisms in the pediatric population.