Physiologically Based Pharmacokinetic Research Articles

Dealing With Variable Drug Exposure DuetoVariable Hepatic Metabolism: A Proof-of-Concept Application of Liquid Biopsy in Renal Impairment.

Precision dosing strategies require accounting for between-patient variability in pharmacokinetics (PK), affecting drug exposure, and in pharmacodynamics (PD), affecting response achieved at the same drug concentration at the site of action. Although liquid biopsy for assessing different levels of molecular drug targets has yet to be established, individual characterization of drug elimination pathways using liquid biopsy has recently been demonstrated. The feasibility of applying this approach in conjunction with modeling tools to guide individual dosing remains unexplored. In this study, we aimed to individualize physiologically-based pharmacokinetic (PBPK) models based on liquid biopsy measurements in plasma from 25 donors with different grades of renal function who were previously administered oral midazolam as part of a microdose cocktail. Virtual twin models were constructed based on demographics, renal function, and hepatic expression of relevant pharmacokinetic pathways projected from liquid biopsy output. Simulated exposure (AUC) to midazolam was in agreement with observed data (AFE = 1.38, AAFE = 1.78). Simulated AUC variability with three dosing approaches indicated higher variability with uniform dosing (14-fold) and stratified dosing (13-fold) compared with individualized dosing informed by liquid biopsy (fivefold). Further, exosome screening revealed mRNA expression of 532 targets relevant to drug metabolism and disposition (169 enzymes and 361 transporters). Data related to these targets can be used to further individualize PBPK models for pathways relevant to PK of other drugs. This study provides additional verification of liquid biopsy-informed PBPK modeling approaches, necessary to advance strategies that seek to achieve precise dosing from the start of treatment.

Skin pharmacokinetics of miltefosine in the treatment of post-kala-azar dermal leishmaniasis in South Asia.

Post-kala-azar dermal leishmaniasis (PKDL) arises as a dermal complication following a visceral leishmaniasis (VL) infection. Current treatment options for PKDL are unsatisfactory, and there is a knowledge gap regarding the distribution of antileishmanial compounds within human skin. The present study investigated the skin distribution of miltefosine in PKDL patients, with the aim to improve the understanding of the pharmacokinetics at the skin target site in PKDL. Fifty-two PKDL patients underwent treatment with liposomal amphotericin B (20 mg/kg) plus miltefosine (allometric dosing) for 21 days. Plasma concentrations of miltefosine were measured on study days 8, 15, 22 and 30, while a punch skin biopsy was taken on day 22. A physiologically based pharmacokinetic (PBPK) model was developed to evaluate the distribution of miltefosine into the skin. Following the allometric weight-based dosing regimen, median miltefosine concentrations on day 22 were 43.73 µg/g (IQR: 21.94-60.65 µg/g) in skin and 33.29 µg/mL (IQR: 25.9-42.58 µg/mL) in plasma. The median individual concentration ratio of skin to plasma was 1.19 (IQR: 0.79-1.9). In 87% (45/52) of patients, skin exposure was above the suggested EC90 PK target of 10.6 mg/L associated with in vitro susceptibility. Simulations indicated that the residence time of miltefosine in the skin would be more than 2-fold longer than in plasma, estimated by a mean residence time of 604 versus 266 hours, respectively. This study provides the first accurate measurements of miltefosine penetration into the skin, demonstrating substantial exposure and prolonged retention of miltefosine within the skin. These findings support the use of miltefosine in cutaneous manifestations of leishmaniasis. In combination with parasitological and clinical data, these results are critical for the future optimization of combination therapies with miltefosine in the treatment of PKDL.

Impact of Obesity on Hepatic Drug Clearance: What are the Influential Variables?

Drug clearance in obese subjects varies widely among different drugs and across subjects with different severity of obesity. This study investigates correlations between plasma clearance (CLp) and drug- and patient-related characteristics in obese subjects, and evaluates the systematic accuracy of common weight-based dosing methods. A physiologically-based pharmacokinetic (PBPK) modeling approach that uses recent information on obesity-related changes in physiology was used to simulate CLp for a normal-weight subject (body mass index [BMI] = 20) and subjects with various severities of obesity (BMI 25–60) for hypothetical hepatically cleared drugs with a wide range of properties. Influential variables for CLp change were investigated. For each drug and obese subject, the exponent that yields perfect allometric scaling of CLp from normal-weight subjects was assessed. Among all variables, BMI and relative changes in enzyme activity resulting from obesity proved highly correlated with obesity-related CLp changes. Drugs bound to α1-acid glycoprotein (AAG) had lower CLp changes compared to drugs bound to human serum albumin (HSA). Lower extraction ratios (ER) corresponded to higher CLp changes compared to higher ER. The allometric exponent for perfect scaling ranged from -3.84 to 3.34 illustrating that none of the scaling methods performed well in all situations. While all three dosing methods are generally systematically accurate for drugs with unchanged or up to 50% increased enzyme activity in subjects with a BMI below 30 kg/m2, in any of the other cases, information on the different drug properties and severity of obesity is required to select an appropriate dosing method for individuals with obesity.Graphical

In Vitro In Vivo Extrapolation and Bioequivalence Prediction for Immediate-Release Capsules of Cefadroxil Based on a Physiologically-Based Pharmacokinetic ACAT Model.

Physiologically based pharmacokinetic (PBPK) modeling is a mechanistic concept, which helps to judge the effects of biopharmceutical properties of drug product such as in vitro dissolution on its pharmacokinetic and in vivo performance. With the application of virtual bioequivalence (VBE) study, the drug product development using model-based approach can help in evaluating the possibility of extending BCS-based biowaiver. Therefore, the current study was intended to develop PBPK model as well as in vitro in vivo extrapolation (IVIVE) for BCS class III drug i.e. cefadroxil.A PBPK model was created in GastroPlus™ 9.8.3 utilizing clinical data of immediate-release cefadroxil formulations. By the examination of simulated and observed plasma drug concentration profiles, the predictability of the proposed model was assessed for the prediction errors. Furthermore, mechanistic deconvolution was used to create IVIVE, and the plasma drug concentration profiles and pharmacokinetic parameters were predicted for different virtual formulations with variable cefadroxil in vitro release. Virtual bioequivalence study was also executed to assess the bioequivalence of the generic verses the reference drug product (Duricef®).The developed PBPK model satisfactorily predicted Cmax and AUC0-t after cefadroxil single and multiple oral dose administrations, with all individual prediction errors within the limits except in a few cases. Second order polynomial correlation function obtained accurately predict in vivo drug release and plasma concentration profile of cefadroxil test and reference (Duricef®) formulation. The VBE study also proved test formulation bioequivalent to reference formulation and the statistical analysis on pharmacokinetic parameters reported 90% confidence interval for Cmax and AUC0-t in the FDA acceptable limits.The analysis found that a validated and verified PBPK model with a mechanistic background is as a suitable approach to accelerate generic drug development.

In-Depth Analysis of the Selection of PBPK Modeling Tools: Bibliometric and Social Network Analysis of the Open Systems Pharmacology Community.

Since the Open Source Initiative laid the foundation for the open source software environment in 1998, the popularity of free and open source software has been steadily increasing. Model-informed drug discovery and development (MID3), a key component of pharmaceutical research and development, heavily makes use of computational models which can be developed using various software including the Open Systems Pharmacology (OSP) software (PK-Sim/MoBi), a free and open source software tool for physiologically based pharmacokinetic (PBPK) modeling. In this study, we aimed to investigate the impact, application areas, and reach of the OSP software as well as the relationships and collaboration patterns between organizations having published OSP-related articles between 2017 and 2023. Therefore, we conducted a bibliometric analysis of OSP-related publications and a social network analysis of the organizations with which authors of OSP-related publications were affiliated. On several levels, we found evidence for a significant growth in the size of the OSP community as well as its visibility in the MID3 community since OSP's establishment in 2017. Specifically, the annual publication rate of PubMed-indexed PBPK-related articles using the OSP software outpaced that of PBPK-related articles using any software. Our bibliometric analysis and network analysis demonstrated that the expansion of the OSP community was predominantly driven by new authors and organizations without prior connections to the community involving the generation of research clusters de novo and an overall diversification of the network. These findings suggest an ongoing evolution of the OSP community toward a more segmented, diverse, and inclusive network.

Physiologically based pharmacokinetic modeling to predict the pharmacokinetics of codeine in different CYP2D6 phenotypes

ObjectivesCodeine, a prodrug used as an opioid agonist, is metabolized to the active product morphine by CYP2D6. This study aimed to establish physiologically based pharmacokinetic (PBPK) models of codeine and morphine and explore the influence of CYP2D6 genetic polymorphisms on the pharmacokinetics of codeine and morphine.MethodsAn initial PBPK modeling of codeine in healthy adults was established using PK-Sim® software and subsequently extrapolated to CYP2D6 phenotype-related PBPK modeling based on the turnover frequency (Kcat) of CYP2D6 for different phenotype populations (UM, EM, IM, and PM). The mean fold error (MFE) and geometric mean fold error (GMFE) methods were used to compare the differences between the predicted and observed values of the pharmacokinetic parameters to evaluate the accuracy of PBPK modeling. The validated models were then used to support dose safety for different CYP2D6 phenotypes.ResultsThe developed and validated CYP2D6 phenotype-related PBPK model successfully predicted codeine and morphine dispositions in different CYP2D6 phenotypes. Compared with EMs, the predicted AUC0-∞ value of morphine was 98.6% lower in PMs, 60.84% lower in IMs, and 73.43% higher in UMs. Morphine plasma exposure in IMs administered 80 mg of codeine was roughly comparable to that in EMs administered 30 mg of codeine. CYP2D6 UMs may start dose titration to achieve an optimal individual regimen and avoid a single dose of over 20 mg. Codeine should not be used in PMs for pain relief, considering its insufficient efficacy.ConclusionPBPK modeling can be applied to explore the dosing safety of codeine and can be helpful in predicting the effect of CYP2D6 genetic polymorphisms on drug–drug interactions (DDIs) with codeine in the future.

Predicting gastric emptying of drug substances taken under postprandial conditions by combination of biorelevant dissolution and mechanistic in silico modeling

Physiologically based pharmacokinetic (PBPK) models can help to understand the effects of gastric emptying on pharmacokinetics and in particular also provide a platform for understanding mechanisms of food effects, as well as extrapolation between different postprandial conditions, whether standardized clinical or patient-oriented, non-clinical conditions. By integrating biorelevant dissolution data from the GastroDuo dissolution model into a previously described mechanistic model of fed-state gastric emptying, we simulated the effects of a high-calorie high-fat meal on the pharmacokinetics of sildenafil, febuxostat, acetylsalicylic acid, theobromine and caffeine. The model was able to simulate the variability in Cmax and tmax caused by the presence of the stomach road. The main influences investigated to affect the gastric emptying process were drug solubility (theobromine and caffeine), tablet dissolution rate (acetylsalicylic acid) and sensitivity to gastric motility (sildenafil and febuxostat). Finally, we showed how PBPK models can be used to extrapolate pharmacokinetics between different prandial states using theobromine as an example with results from a clinical study being presented.

Influence of design parameters on sustained drug release properties of 3D-printed theophylline tablets

The application of three-dimensional printing (3DP) in the pharmaceutical industry brings a broad spectrum of benefits to patients by addressing individual needs and improve treatment success. This study investigates the sustained release properties of 3DP tablets containing Theophylline (TPH), which is commonly used to treat respiratory diseases and recently having a comeback due to its potential in the treatment of conditions like Covid-19. Since TPH is a narrow therapeutic window (NTW) drug with serious side effects in the event of overdose, the release properties must be observed particularly closely. We employed a state-of-the-art single screw extrusion 3D printer, which is fed with granules containing the drug. By employing a Taguchi orthogonal array design of experiments (DOE), tablet design parameters and factor related process stability were sought to be evaluated fundamentally. Following this, examinations regarding tailored TPH dosages were undertaken and a relationship between the real printed dose of selected tablet designs and their sustained drug release was established. The release profiles were analyzed using different mathematical model fits and compared in terms of mean dissolution times (MDT). Finally, in-vivo/in-vitro correlation (IVIVC) and physiologically based pharmacokinetic (PBPK) modeling showed that a paradigm patient group could be covered with the dosage forms produced.

Translational two-pore PBPK model to characterize whole-body disposition of different-size endogenous and exogenous proteins.

Two-pore physiologically based pharmacokinetic (PBPK) modeling has demonstrated its potential in describing the pharmacokinetics (PK) of different-size proteins. However, all existing two-pore models lack either diverse proteins for validation or interspecies extrapolation. To fill the gap, here we have developed and optimized a translational two-pore PBPK model that can characterize plasma and tissue disposition of different-size proteins in mice, rats, monkeys, and humans. Datasets used for model development include more than 15 types of proteins: IgG (150kDa), F(ab)2 (100kDa), minibody (80kDa), Fc-containing proteins (205, 200, 110, 105, 92, 84, 81, 65, or 60kDa), albumin conjugate (85.7kDa), albumin (67kDa), Fab (50kDa), diabody (50kDa), scFv (27kDa), dAb2 (23.5kDa), proteins with an albumin-binding domain (26, 23.5, 22, 16, 14, or 13kDa), nanobody (13kDa), and other proteins (110, 65, or 60kDa). The PBPK model incorporates: (i) molecular weight (MW)-dependent extravasation through large and small pores via diffusion and filtration, (ii) MW-dependent renal filtration, (iii) endosomal FcRn-mediated protection from catabolism for IgG and albumin-related modalities, and (iv) competition for FcRn binding from endogenous IgG and albumin. The finalized model can well characterize PK of most of these proteins, with area under the curve predicted within two-fold error. The model also provides insights into contribution of renal filtration and lysosomal degradation towards total elimination of proteins, and contribution of paracellular convection/diffusion and transcytosis towards extravasation. The PBPK model presented here represents a cross-modality, cross-species platform that can be used for development of novel biologics.

A physiologically-based pharmacokinetic precision dosing approach to manage dasatinib drug-drug interactions.

Dasatinib, a second-generation tyrosine kinase inhibitor, is approved for treating chronic myeloid and acute lymphoblastic leukemia. As a sensitive cytochrome P450 (CYP) 3A4 substrate and weak base with strong pH-sensitive solubility, dasatinib is susceptible to enzyme-mediated drug-drug interactions (DDIs) with CYP3A4 perpetrators and pH-dependent DDIs with acid-reducing agents. This work aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) model of dasatinib to describe and predict enzyme-mediated and pH-dependent DDIs, to evaluate the impact of strong and moderate CYP3A4 inhibitors and inducers on dasatinib exposure and to support optimized dasatinib dosing. Overall, 63 plasma profiles from perorally administered dasatinib in healthy volunteers and cancer patients were used for model development. The model accurately described and predicted plasma profiles with geometric mean fold errors (GMFEs) for area under the concentration-time curve from the first to the last timepoint of measurement (AUClast) and maximum plasma concentration (Cmax) of 1.27 and 1.29, respectively. Regarding the DDI studies used for model development, all (8/8) predicted AUClast and Cmax ratios were within twofold of observed ratios. Application of the PBPK model for dose adaptations within various DDIs revealed dasatinib dose reductions of 50%-80% for strong and 0%-70% for moderate CYP3A4 inhibitors and a 2.3-3.1-fold increase of the daily dasatinib dose for CYP3A4 inducers to match the exposure of dasatinib administered alone. The developed model can be further employed to personalize dasatinib therapy, thereby help coping with clinical challenges resulting from DDIs and patient-related factors, such as elevated gastric pH.

Dose Optimization Informed by PBPK Modeling: State-of-the Art and Future.

Model-informed drug development (MIDD) is a powerful quantitative approach that plays an integral role in drug development and regulatory review. While applied throughout the life cycle of the development of new drugs, a key application of MIDD is to inform clinical trial design including dose selection and optimization. To date, physiologically-based pharmacokinetic (PBPK) modeling, an established component of the MIDD toolkit, has mainly been used for assessment of drug-drug interactions (DDIs) and consequential dose adjustments in regulatory submissions. As a result of recent scientific advances and growing confidence in the utility of the approach, PBPK models are being increasingly applied to provide dose recommendations for subjects with differing ages, genetics, and disease states. In this review, we present our perspective on the current landscape of regulatory acceptance of PBPK applications supported by relevant case studies. We also discuss the recent progress and future challenges associated with expanding the utility of PBPK models into emerging areas for regulatory decision making, especially dose optimization in highly vulnerable and understudied populations and facilitating diversity in clinical trials.

Can in vitro/in silico tools improve colonic concentration estimations for oral extended-release formulations? A case study with upadacitinib

Upadacitinib, classified as a highly soluble drug, is commercially marketed as RINVOQ®, a modified-release formulation incorporating hydroxypropyl methylcellulose as a matrix system to target extended release throughout the gastrointestinal (GI) tract. Our study aimed to explore how drug release will occur throughout the GI tract using a plethora of in vitro and in silico tools. We built a Physiologically-Based Pharmacokinetic (PBPK) model in GastroPlus™ to predict the systemic concentrations of the drug when administered using in vitro dissolution profiles as input to drive luminal dissolution. A series of in vitro dissolution experiments were gathered using the USP Apparatus I, III and IV in presence of biorelevant media, simulating both fasted and fed state conditions. A key outcome from the current study was to establish an in vitro-in vivo correlation (IVIVC) between (i) the dissolution profiles obtained from the USP I, III and IV methods and (ii) the fraction absorbed of drug as deconvoluted from the plasma concentration-time profile of the drug. When linking the fraction dissolved as measured in the USP IV model, a Level A IVIVC was established. Moreover, when using the different dissolution profiles as input for PBPK modeling, it was also observed that predictions for plasma Cmax and AUC were most accurate for USP IV compared to the other models (based on predicted versus observed ratios). Furthermore, the PBPK model has the utility to extract the predicted concentrations at the level of the colon which can be of utmost interest when working with specific in vitro assays.

Effect of Food Composition on the PK of Isoniazid Quantitatively Explained Using Physiologically Based Biopharmaceutics Modeling.

This work shows the utilization of a physiologically based biopharmaceutics model (PBBM) to mechanistically explain the impact of diverse food types on the pharmacokinetics (PK) of isoniazid (INH) and acetyl-isoniazid (Ac-INH). The model was established and validated using published PK profiles for INH along with a combination of measured and predicted values for the physico-chemical and biopharmaceutical propertied of INH and Ac-INH. A dedicated ontogeny model was developed for N-acetyltransferase 2 (NAT2) in human integrating Michaelis Menten parameters for this enzyme in the physiologically based pharmacokinetic (PBPK) model tissues and in the gut, to explain the pre-systemic and systemic metabolism of INH across different acetylator types. Additionally, a novel equation was proposed to calculate the luminal drug degradation related to the presence of reducing sugars, using individual sugar molar concentrations in the meal. By incorporating luminal degradation into the model, adjusting bile salt concentrations and gastric emptying according to food type and quantity, the PBBM was able to accurately predict the negative effect of carbohydrate-rich diets on the PK of INH.

Prediction of physicochemical and pharmacokinetic properties of botanical constituents by computational models.

Botanicals contain complex mixtures of chemicals most of which lack pharmacokinetic data in humans. Since physicochemical and pharmacokinetic properties dictate the in vivo exposure of botanical constituents, these parameters greatly impact the pharmacological and toxicological effects of botanicals in consumer products. This study sought to use computational (i.e., in silico) models, including quantitative structure-activity relationships (QSAR) and physiologically based pharmacokinetic (PBPK) modeling, to predict properties of botanical constituents. One hundred and three major constituents (e.g., withanolides, mitragynine, and yohimbine) in 13 botanicals (e.g., ashwagandha, kratom, and yohimbe) were investigated. The predicted properties included biopharmaceutical classification system (BCS) classes based on aqueous solubility and permeability, oral absorption, liver microsomal clearance, oral bioavailability, and others. Over half of these constituents fell into BCS classes I and II at dose levels no greater than 100 mg per day, indicating high permeability and absorption (%Fa > 75%) in the gastrointestinal tract. However, some constituents such as glycosides in ashwagandha and Asian ginseng showed low bioavailability after oral administration due to poor absorption (BCS classes III and IV, %Fa < 40%). These in silico results fill data gaps for botanical constituents and could guide future safety studies. For example, the predicted human plasma concentrations may help select concentrations for in vitro toxicity testing. Additionally, the in silico data could be used in tiered or batteries of assays to assess the safety of botanical products. For example, highly absorbed botanical constituents indicate potential high exposure in the body, which could lead to toxic effects.

Physiologically based pharmacokinetic modeling the reversible metabolism and tissue-specific partitioning of methylprednisolone and methylprednisone in rats.

The pharmacokinetics (PK) of methylprednisolone (MPL) exhibited tissue-specific saturable binding and reversible conversion with its metabolite, methylprednisone (MPN). Blood and 11 tissues were collected in male rats after intravenous (IV) bolus doses of 50 mg/kg MPL and 20 mg/kg MPN and upon IV infusion of MPL and MPN at 0.3, 3, and 10 mg/h/kg. The concentrations of MPL and MPN were simultaneously measured. A comprehensive physiologically based pharmacokinetic (PBPK) model was applied to describe the plasma and tissue profiles and estimate PK parameters of the MPL/MPN interconversion system. Both dosed and formed MPL and MPN were in rapid equilibrium or achieved steady-state rapidly in plasma and tissues. MPL tissue partitioning was nonlinear with highest capacity in liver (322.9 ng/mL), followed by kidney, heart, intestine, skin, spleen, bone, brain, muscle, and lowest in adipose (2.74 ng/mL), and displayed high penetration in lung. The tissue partition coefficient of MPN was linear but widely variable (0.15~5.38) across most tissues with nonlinear binding in liver and kidney. The conversion of MPL to MPN occurred in kidney, lung, and intestine with total clearance of 429 mL/h, and the back conversion occurred in liver and kidney at 1342 mL/h. The irreversible elimination clearance of MPL was 789 mL/h from liver and that of MPN was 2758 mL/h with liver accounting for 44%, lung 35%, and kidney 21%. The reversible metabolism elevated MPL exposure in rats by 13%. This highly complex PBPK model provided unique and comprehensive insights into the disposition of a major corticosteroid. Significance Statement Our dual PBPK study and model of MPL/MPN with multiple complexities reasonably characterized and parameterized their disposition, localized their reversible conversion, rendered advanced appreciation of tissue partitioning, and provided greater insights into the interpretation of their pharmacodynamics in rats. Drug knowledge gained in this study may be translatable to higher-order species to appreciate the clinical utility of MPL. The complex model itself is instructive for advanced PBPK analysis of drugs with reversible metabolism and/or nonlinear tissue partitioning features.

Physiologically based pharmacokinetic modeling to predict the impact of liver cirrhosis on glucuronidation via UGT1A4 & UGT2B7/2B4 - a case study with midazolam.

Hepatic impairment, due to liver cirrhosis, decreases the activity of cytochrome P450 enzymes (CYPs). The use of physiologically-based pharmacokinetic (PBPK) modeling to predict this effect for CYP substrates has been well-established, but the effect of cirrhosis on uridine-glucuronosyltransferase (UGT) activities is less studied and few PBPK models have been reported. UGT enzymes are involved in primary N-glucuronidation of midazolam and glucuronidation of 1'-OH-midazolam following CYP3A hydroxylation. In this study Simcyp® was used to establish PBPK models for midazolam, its primary metabolites midazolam-N-glucuronide (UGT1A4) and 1'-OH midazolam (CYP3A4/3A5) and the secondary metabolite 1'-OH-midazolam-O-glucuronide (UGT2B7/2B4), allowing to simulate the impact of liver cirrhosis on the primary and secondary glucuronidation of midazolam. The model was verified in non-cirrhotic subjects before extrapolation to cirrhotic patients of Child-Pugh (CP) classes A, B, and C. Our model successfully predicted the exposures of midazolam and its metabolites in non-cirrhotic and cirrhotic patients, with 86% of observed plasma concentrations within 5th-95th percentiles of predictions and observed geometrical mean of AUCinf and Cmax within 0.7-1.43-fold of predictions. The simulated metabolic ratio (AUCglucuronide/AUCparent, MR), was calculated for midazolam-N-glucuronide to midazolam (indicative of UGT1A4 activity) and decreased by 40% (CP A), 48% (CP B), and 75% (CP C). For 1'-OH-midazolam-O-glucuronide to 1'-OH-midazolam the MR (indicative of UGT2B7/2B4 activity) dropped by 35% (CP A), 51% (CP B), and 64% (CP C). These predicted MRs were corroborated by the observed data. This work thus increases confidence in Simcyp® predictions of the effect of liver cirrhosis on the pharmacokinetics of UGT1A4 and UGT2B7/UGT2B4 substrates. Significance Statement This paper presents a PBPK model for midazolam and its metabolites and verifies the accurate simulation of pharmacokinetic profiles when using the Simcyp® hepatic impairment population models. Exposure changes of midazolam-N-glucuronide and 1'-OH-midazolam-O-glucuronide reflect the impact of decreases in UGT1A4 and UGT2B7/2B4 glucuronidation activity in cirrhotic patients. The approach used in this study may be extended to verify the modeling of other UGT enzymes affected by liver cirrhosis.

Differential tissue abundance of membrane-bound drug metabolizing enzymes and transporter proteins by global proteomics.

Protein abundance data of drug-metabolizing enzymes and transporters (DMETs) are critical for scaling in vitro and animal data to humans for accurate prediction and interpretation of drug clearance and toxicity. Targeted DMET proteomics which relies on synthetic stable isotope-labeled surrogate peptides as calibrators, is routinely used for the quantification of selected proteins; however, the technique is limited to the quantification of a small number of proteins. Although the global proteomics-based total protein approach (TPA) is emerging as a better alternative for large-scale protein quantification, the conventional TPA doesn't consider differential sequence coverage by identifying unique peptides across proteins. Here, we optimized the TPA approach by correcting protein abundance data by the sequence coverage (SC-TPA), which was applied to quantify 54 DMETs for characterization of i) differential tissue DMET abundance in the human liver, kidney, and intestine, and ii) interindividual variability of DMET proteins in individual intestinal samples (n=13). UGT2B7, MGST1, MGST2, MGST3, CES2, and MRP2 were expressed in all three tissues, whereas, as expected CYP3A4, CYP3A5, CYP2C9, CYP4F2, UGT1A1, UGT2B17, CES1, FMO5, MRP3, and P-gp were present in the liver and intestine. The top three DMET proteins in individual tissues were: CES1>CYP2E1>UGT2B7 (liver), CES2>UGT2B17>CYP3A4 (intestine), and MGST1>UGT1A6>MGST2 (kidney). CYP3A4, CYP3A5, UGT2B17, CES2, and MGST2 showed high interindividual variability in the intestine. These data are relevant for enhancing in vitro to in vivo extrapolation (IVIVE) of drug absorption and disposition and can be used to enhance the accuracy of physiologically based pharmacokinetic (PBPK) prediction of systemic and tissue concentration of drugs. Significance Statement We quantified the abundance and compositions of drug-metabolizing enzymes and transporters (DMETs) in pooled human liver, intestine, and kidney microsomes using an optimized sequence coverage-informed total protein approach. The quantification of DMETs revealed quantitative differences in their levels in the liver, intestine, and kidney. Further, the analysis of individual intestine samples confirmed high variability in the levels of CYP3A4, CYP3A5, UGT2B17, CES2, and MGST2. These data are applicable for the prediction of first-pass metabolism and tissue-specific drug clearance.

Sex, Age, and Species Differences of Perfluorooctanoic Acid Modeled by Flow- versus Permeability-limited Physiologically-Based Pharmacokinetic Models.

This study aimed to investigate sex, age, and species differences of perfluorooctanoic acid (PFOA) using physiologically-based pharmacokinetic (PBPK) models in rats and humans. PBPK models were generally developed as either flow- or permeability-limited models. The flow-limited model is cost-effective and allows for human PK prediction through simple allometric scaling, while the permeability-limited model can incorporate detailed information on the disposition process through in vitro-in vivo extrapolation (IVIVE). PFOA was administered via oral or intravenous administration with 5mg/kg in male and female rats of different ages and the data was used to develop the PBPK models. Our results showed that both models successfully captured sex differences in rats, while only the flow-limited model with male rats and the permeability-limited model with both male and female rats provided comparable predictions in the human clinical study. More than the flow-limited model, the permeability-limited model effectively explained sex differences in rats and species differences through IVIVE. Additionally, the ontogeny-based mechanistic description of PFOA disposition enabled the interpretation of age- and sex-dependent pharmacokinetics. Although the flow-limited PBPK model lacked mechanistic interpretability compared to the permeability-limited model, it demonstrated reliable human prediction through simple allometric scaling. In conclusion, the permeability PBPK model could interpret age, sex, and species differences and it could improve the accuracy of human prediction.

Bioequivalence risk assessment of oral formulations containing racemic ibuprofen through a chiral physiologically based pharmacokinetic model of ibuprofen enantiomers

The characterization of the time course of ibuprofen enantiomers can be useful in the selection of the most sensitive analyte in bioequivalence studies. Physiologically based pharmacokinetic (PBPK) modelling and simulation represents the most efficient methodology to virtually assess bioequivalence outcomes. In this work, we aim to develop and verify a PBPK model for ibuprofen enantiomers administered as a racemic mixture with different immediate release dosage forms to anticipate bioequivalence outcomes based on different particle size distributions. A PBPK model incorporating stereoselectivity and non-linearity in plasma protein binding and metabolism as well as R-to-S unidirectional inversion has been developed in Simcyp®. A dataset composed of 11 Phase I clinical trials with 54 scenarios (27 per enantiomer) and 14,452 observations (7129 for R-ibuprofen and 7323 for S-ibuprofen) was used. Prediction errors for AUC0-t and Cmax for both enantiomers fell within the 0.8–1.25 range in 50/54 (93 %) and 42/54 (78 %) of scenarios, respectively. Outstanding model performance, with 10/10 (100 %) of Cmax and 9/10 (90 %) of AUC0-t within the 0.9–1.1 range, was demonstrated for oral suspensions, which strongly supported its use for bioequivalence risk assessment. The deterministic bioequivalence risk assessment has revealed R-ibuprofen as the most sensitive analyte to detect differences in particle size distribution for oral suspensions containing 400 mg of racemic ibuprofen, suggesting that achiral bioanalytical methods would increase type II error and declare non-bioequivalence for formulations that are bioequivalent for the eutomer.

Physiologically-based pharmacokinetic modelling guided dose evaluations of nirmatrelvir/ritonavir in renal impairment for the management of COVID-19.

We aimed to address factors contributing to the pharmacokinetic changes of nirmatrelvir/ritonavir in renal impaired (RI) patients and recommend dosing adjustment via a physiologically-based pharmacokinetic (PBPK) modelling approach. A PBPK model of nirmatrelvir/ritonavir was developed via Simcyp® Simulator. Sensitivity analysis of the influence of hepatic CYP3A4 intrinsic clearance and abundance, as well as hepatic non-CYP3A4 metabolism (other human liver microsomes [HLM] CLint) was performed to evaluate the effects of RI on oral clearance of nirmatrelvir. Other HLM CLint, the most sensitive parameter, was adjusted, and the simulated plasma concentration profiles of nirmatrelvir in severe RI subjects were within the therapeutic index of 292-10 000 ng/mL for dosing regimens of loading doses of 300/100 mg followed by 150/100 mg or 75/100 mg twice daily of nirmatrelvir/ritonavir. Considering that nirmatrelvir is available as a 150 mg tablet, we recommend 300/100 mg followed by 150/100 mg twice daily as the dosing regimen to be investigated in severe RI.