Minimal Physiologically-based Pharmacokinetic Model Research Articles

Advancements in physiologically based pharmacokinetic modeling for fedratinib: updating dose guidance in the presence of a dual inhibitor of CYP3A4 and CYP2C19.

A physiologically based pharmacokinetic (PBPK) model for fedratinib was updated and revalidated to bridge a gap between the observed drug-drug interaction (DDI) of a single sub-efficacious dose in healthy participants and the potential DDI in patients with cancer at steady state. The study aimed to establish an appropriate dose for fedratinib in patients coadministered with dual CYP3A4 and CYP2C19 inhibitors, providing quantitative evidence to inform dosing guidance. The original minimal PBPK model was developed using Simcyp® Simulator v17. The model was updated by substituting a single distribution rate (Qsac) with 2 separate rates (CLin/CLout) and transitioning to v20. Model parameter updates were further informed with 3 clinical studies, and 3 more studies served as independent validation data. The validated model was applied to simulate potential DDIs between fedratinib and a known dual inhibitor of CYP3A4 and CYP2C19 (fluconazole). Coadministration of fedratinib with fluconazole in patients was predicted to increase fedratinib exposure by < 2-fold in all simulated scenarios. For patients with cancer receiving the approved dose of fedratinib 400mg once daily along with fluconazole 200mg daily, the model predicted an approximate 50% increase in fedratinib exposure at steady state. The updated PBPK model improved description of the observed pharmacokinetics and predicted a low risk of clinically significant DDIs between fedratinib and fluconazole. The quantitative evidence serves as a primary foundation for providing dose guidance in clinical practice for the coadministration of fedratinib with dual CYP3A4 and CYP2C19 inhibitors.

Abstract 875: Quantitative systems pharmacology modeling of loncastuximab tesirine combined with mosunetuzumab and glofitamab helps guide dosing for patients with DLBCL

Abstract Introduction: CD19 and CD20, B-lymphocyte surface antigens, are clinically validated therapeutic targets for the treatment of B-cell malignancies. Loncastuximab tesirine (loncastuximab tesirine-lpyl [Lonca]) is an antibody-drug conjugate comprising an anti-CD19 antibody conjugated to a pyrrolobenzodiazepine dimer cytotoxin. Mosunetuzumab (Mosun) and glofitamab (Glofit) are CD20 × CD3 T-cell-engaging bispecific antibodies (bsAbs) that redirect T cells to eliminate malignant B cells. These agents target a different B-cell surface antigen than Lonca; hence, combining Lonca with either one of these bsAbs is expected to have additive or even synergistic efficacy. Previously, a novel physiologically-based pharmacokinetic (PBPK)-quantitative systems pharmacology (QSP) model was developed (Utsey K, et al. Clin Pharmacol Drug Dev. 2023;12:123-125) and validated with Lonca monotherapy clinical observations in R/R DLBCL (Caimi P, et al. Blood. 2022;140:9548-9550). Modeling results of Lonca in combination with Mosun or Glofit in R/R DLBCL are described herein. Methods: The model was based on the previously validated and published Lonca PBPK-QSP model. This model was reduced in physiological complexity to be compatible with a published minimal PBPK model of Mosun (Hosseini I, et al. NPJ Syst Biol Appl. 2020;6:28) while maintaining the core functionality of predicting tumor dynamics during Lonca monotherapy. The following assumptions were made: (1) Lonca or Mosun/Glofit induce healthy and malignant B-cell killing; (2) the tumor comprises malignant B cells and T cells; (3) tumor volume is calculated using malignant B-cell number; and (4) T cells can enter or leave the tumor as they enter or leave other tissues. Results: Improved tumor growth inhibition (TGI) should result from Lonca + bsAb combination therapy compared with any of the agents as monotherapy. While TGI was predicted to plateau by Cycle (C) 2 with Mosun and Glofit monotherapies, maximum activity of Lonca + bsAb combination therapies may not be observed until C4 or later. Additionally, predicted TGI increased with additional treatment cycles. Conclusions: Results indicate that treatment by the end of C3 for Lonca + Mosun and by the end of C4 for Lonca + Glofit would promote substantially more TGI compared with any of these agents alone. Increased doses of Lonca in combinations were predicted to have limited additional therapeutic benefit; however, additional cycles of combination treatment were predicted to increase TGI. This model suggests that Lonca doses could be reduced to allow for improved tolerability for longer periods of time, up to the point of maximal benefit, although clinical testing is needed to explore these results. The ongoing LOTIS-7 clinical trial (NCT04970901) evaluates the safety and anticancer activity of Lonca in combination with both Glofit and Mosun. Citation Format: Yuezhe Li, A Katharina Wilkins, Tim Knab, Joseph P. Boni. Quantitative systems pharmacology modeling of loncastuximab tesirine combined with mosunetuzumab and glofitamab helps guide dosing for patients with DLBCL [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 875.

A minimal physiologically based pharmacokinetic model to study the combined effect of antibody size, charge, and binding affinity to FcRn/antigen on antibody pharmacokinetics.

Protein therapeutics have revolutionized the treatment of a wide range of diseases. While they have distinct physicochemical characteristics that influence their absorption, distribution, metabolism, and excretion (ADME) properties, the relationship between the physicochemical properties and PK is still largely unknown. In this work we present a minimal physiologically-based pharmacokinetic (mPBPK) model that incorporates a multivariate quantitative relation between a therapeutic's physicochemical parameters and its corresponding ADME properties. The model's compound-specific input includes molecular weight, molecular size (Stoke's radius), molecular charge, binding affinity to FcRn, and specific antigen affinity. Through derived and fitted empirical relationships, the model demonstrates the effect of these compound-specific properties on antibody disposition in both plasma and peripheral tissues using observed PK data in mice and humans. The mPBPK model applies the two-pore hypothesis to predict size-based clearance and exposure of full-length antibodies (150kDa) and antibody fragments (50-100kDa) within a onefold error. We quantitatively relate antibody charge and PK parameters like uptake rate, non-specific binding affinity, and volume of distribution to capture the relatively faster clearance of positively charged mAb as compared to negatively charged mAb. The model predicts the terminal plasma clearance of slightly positively and negatively charged antibody in humans within a onefold error. The mPBPK model presented in this work can be used to predict the target-mediated disposition of a drug when compound-specific and target-specific properties are known. To our knowledge, a combined effect of antibody weight, size, charge, FcRn, and antigen has not been incorporated and studied in a single mPBPK model previously. By conclusively incorporating and relating a multitude of protein's physicochemical properties to observed PK, our mPBPK model aims to contribute as a platform approach in the early stages of drug development where many of these properties can be optimized to improve a molecule's PK and ultimately its efficacy.

PBPK modeling to predict the pharmacokinetics of pantoprazole in different CYP2C19 genotypes.

Pantoprazole is used to treat gastroesophageal reflux disease (GERD), maintain healing of erosive esophagitis (EE), and control symptoms related to Zollinger-Ellison syndrome (ZES). Pantoprazole is mainly metabolized bycytochrome P450 (CYP)2C19, converting to 4'-demethyl pantoprazole. CYP2C19 is a genetically polymorphic enzyme, and the genetic polymorphism affects the pharmacokinetics and/or pharmacodynamics of pantoprazole. In this study, we aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of pantoprazole in populations with various CYP2C19 metabolic activities. A comprehensive investigation of previous reports and drug databases was conducted to collect the clinical pharmacogenomic data, physicochemical data, and disposition properties of pantoprazole, and the collected data were used for model establishment. The model was evaluated by comparing the predicted plasma concentration-time profiles and/or pharmacokinetic parameters (AUC and Cmax) with the clinical observation results. The predicted plasma concentration-time profiles in different CYP2C19 phenotypes properly captured the observed profiles. All fold error values for AUC and Cmax were included in the two-fold range. Consequently, the minimal PBPK model for pantoprazole related to CYP2C19 genetic polymorphism was properly established and it can predict the pharmacokinetics of pantoprazole in different CYP2C19 phenotypes. The present model can broaden the insight into the individualized pharmacotherapy for pantoprazole.

A Minimal PBPK Model for Plasma and Cerebrospinal Fluid Pharmacokinetics of Trastuzumab after Intracerebroventricular Administration in Patients with HER2-Positive Brain Metastatic Localizations.

Dosing regimens of trastuzumab administered by intracerebroventricular (icv) route to patients with HER2-positive brain localizations remain empirical. The objectives of this study were to describe pharmacokinetics (PK) of trastuzumab in human plasma and cerebrospinal fluid (CSF) after simultaneous icv and intravenous (iv) administration using a minimal physiologically-based pharmacokinetic model (mPBPK) and to perform simulations of alternative dosing regimens to achieve therapeutic concentrations in CSF. Plasma and CSF PK data were collected in two patients with HER2-positive brain localizations. A mPBPK model for mAbs consisting of four compartments (tight and leaky tissues, plasma and lymph) was enriched by an additional compartment for ventricular CSF. The comparison between observed and model-predicted concentrations was evaluated using prediction error (PE). The developed mPBPK model described plasma and CSF trastuzumab concentrations reasonably well with mean PE for plasma and CSF data of 41.8% [interquartile range, IQR = -9.48; 40.6] and 18.3% [-36.7; 60.6], respectively, for patient 1 and 11.4% [-10.8; 28.7] and 22.5% [-27.7; 77.9], respectively, for patient 2. Trastuzumab showed fast clearance from CSF to plasma with Cmin,ssof 0.56 and 0.85mg/L for 100 and 150mg q1wk, respectively. Repeated dosing of 100 and 150mg q3day resulted in Cmin,ssof 10.3 and 15.4mg/L, respectively. Trastuzumab CSF target concentrations are achieved rapidly and maintained above 60mg/L from 7days after a continuous perfusion at 1.0mg/h. Continuous icv infusion of trastuzumab at 1.0mg/h could be an alternative dosing regimen to rapidly achieve intraventricular CSF therapeutic concentrations.

Incorporation and Performance Verification of Hepatic Portal Blood Flow Shunting in Minimal and Full PBPK Models of Liver Cirrhosis.

Patho-physiological changes in liver cirrhosis create portacaval shunts that allow blood flow to bypass the hepatic portal vein into the systemic circulation affecting drug pharmacokinetics (PKs). The objectives of this work were to implement a physiologically-based pharmacokinetic (PBPK) framework describing shunted blood flows in virtual patients with differing degrees of liver cirrhosis; and to assess the minimal and full PBPK model's performance using drugs with intermediate to high hepatic extraction. Single dose concentration-time profiles and PK parameters for oral ibrutinib, midazolam, propranolol, and buspirone were simulated in healthy volunteers (HVs) and subjects with cirrhosis (Child-Pugh severity score (CP-A, CP-B, or CP-C)). Model performance was verified by comparing predicted to observed fold-changes in PK parameters between HVs and cirrhotic subjects. The verified model was used to simulate the PK changes for simvastatin in patients with cirrhosis. The predicted area under the curve ratios (AUCCirr :AUCHV ) for ibrutinib were 3.38, 6.87, and 11.46 using the minimal PBPK model with shunt and 1.61, 2.58, and 4.33 without the shunt, these compared with observed values of 4.33, 8.14, and 9.04, respectively. For ibrutinib, propranolol, and buspirone, including a shunt in the PBPK model improved the prediction of the AUCCirr :AUCHV and maximum plasma concentration ratios (CmaxCirr :CmaxHV ). For midazolam, an intermediate extraction drug, the differences were less clear. Simulated simvastatin dose adjustments in cirrhosis suggested that 20 mg in CP-A and 10 mg in CP-B could be used clinically. A mechanistic model-informed understanding of the anatomic and pathophysiology of cirrhosis will facilitate improved dose prediction and adjustment in this vulnerable population.

Assessment of Clinical Response to V937 Oncolytic Virus After Intravenous or Intratumoral Administration Using Physiologically-Based Modeling.

Oncolytic viruses (OVs) represent a potential therapeutic strategy in cancer treatment. However, there is currently a lack of comprehensive quantitative models characterizing clinical OV kinetics and distribution to the tumor. In this work, we present a mechanistic modeling framework for V937 OV, after intratumoral (i.t.) or intravascular (i.v.) administration in patients with cancer. A minimal physiologically-based pharmacokinetic model was built to characterize biodistribution of OVs in humans. Viral dynamics was incorporated at the i.t. cellular level and linked to tumor response, enabling the characterization of a direct OV killing triggered by the death of infected tumor cells and an indirect killing induced by the immune response. The model provided an adequate description of changes in V937 mRNA levels and tumor size obtained from phase I/II clinical trials after V937 administration. The model showed prominent role of viral clearance from systemic circulation and infectivity in addition to known tumor aggressiveness on clinical response. After i.v. administration, i.t. exposure of V937 was predicted to be several orders of magnitude lower compared with i.t. administration. These differences could be overcome if there is high virus infectivity and/or replication. Unfortunately, the latter process could not be identified at the current clinical setting. This work provides insights on selecting optimal OV considering replication rate and infectivity.

Application of Minimal Physiologically-Based Pharmacokinetic Model to Simulate Lung and Trachea Exposure of Pyronaridine and Artesunate in Hamsters.

A fixed-dose combination of pyronaridine and artesunate, one of the artemisinin-based combination therapies, has been used as a potent antimalarial treatment regimen. Recently, several studies have reported the antiviral effects of both drugs against severe acute respiratory syndrome coronavirus two (SARS-CoV-2). However, there are limited data on the pharmacokinetics (PKs), lung, and trachea exposures that could be correlated with the antiviral effects of pyronaridine and artesunate. The purpose of this study was to evaluate the pharmacokinetics, lung, and trachea distribution of pyronaridine, artesunate, and dihydroartemisinin (an active metabolite of artesunate) using a minimal physiologically-based pharmacokinetic (PBPK) model. The major target tissues for evaluating dose metrics are blood, lung, and trachea, and the nontarget tissues were lumped together into the rest of the body. The predictive performance of the minimal PBPK model was evaluated using visual inspection between observations and model predictions, (average) fold error, and sensitivity analysis. The developed PBPK models were applied for the multiple-dosing simulation of daily oral pyronaridine and artesunate. A steady state was reached about three to four days after the first dosing of pyronaridine and an accumulation ratio was calculated to be 1.8. However, the accumulation ratio of artesunate and dihydroartemisinin could not be calculated since the steady state of both compounds was not achieved by daily multiple dosing. The elimination half-life of pyronaridine and artesunate was estimated to be 19.8 and 0.4 h, respectively. Pyronaridine was extensively distributed to the lung and trachea with the lung-to-blood and trachea-to-blood concentration ratios (=Cavg,tissue/Cavg,blood) of 25.83 and 12.41 at the steady state, respectively. Also, the lung-to-blood and trachea-to-blood AUC ratios for artesunate (dihydroartemisinin) were calculated to be 3.34 (1.51) and 0.34 (0.15). The results of this study could provide a scientific basis for interpreting the dose-exposure-response relationship of pyronaridine and artesunate for COVID-19 drug repurposing.

Analysis of Time-Dependent Pharmacokinetics Using In Vitro-In Vivo Extrapolation and Physiologically Based Pharmacokinetic Modeling.

SCR430, a sorafenib derivative, is an investigational drug exhibiting anti-tumor action. This study aimed to have a mechanistic understanding of SCR430's time-dependent pharmacokinetics (TDPK) through an ex vivo study combined with an in vitro-in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) modeling. A non-compartmental pharmacokinetic analysis was performed after intravenous SCR430 administration in female Sprague-Dawley rats for a control group (no treatment), a vehicle group (vehicle only, 14 days, PO), and a repeated-dosing group (SCR430, 30 mg/kg/day, 14 days, PO). In addition, hepatic uptake and metabolism modulation were investigated using isolated hepatocytes from each group of rats. The minimal PBPK model based on IVIVE was constructed to explain SCR430's TDPK. Repeated SCR430 administration decreased the systemic exposure by 4.4-fold, which was explained by increased hepatic clearance (4.7-fold). The ex vivo study using isolated hepatocytes from each group suggested that the increased hepatic uptake (9.4-fold), not the metabolic activity, contributes to the increased hepatic clearance. The minimal PBPK modeling based on an ex vivo study could explain the decreased plasma levels after the repeated doses. The current study demonstrates the TDPK after repeated dosing by hepatic uptake induction, not hepatic metabolism, as well as the effectiveness of an ex vivo approach combined with IVIVE and PBPK modeling to investigate the TDPK.

Drug Interaction Potential As a Result of Cytokine Release Syndrome Using a Physiologically Based Pharmacokinetic Model: Case Study of Teclistamab

Introduction: Teclistamab is a B-cell maturation antigen (BCMA) × CD3 bispecific IgG4 antibody that redirects CD3+ T cells to mediate T-cell activation and subsequent lysis of BCMA-expressing multiple myeloma (MM) cells. Interleukin-6 (IL-6) is a biomarker of inflammation that is known to downregulate cytochrome P450 (CYP) enzyme activity. A physiologically based pharmacokinetic (PBPK) model was developed to evaluate the impact of IL-6 serum level observed in the MajesTEC-1 study at the recommended phase 2 dosing regimen (RP2D) of teclistamab (1.5 mg/kg subcutaneous weekly treatment dose, with the first treatment dose preceded by step-up doses of 0.06 and 0.3 mg/kg) on the exposure of coadministered CYP substrates. Methods: A PBPK model was developed for IL-6 based on the literature (Xu Y et al. CPT Pharmacometrics Syst Pharmacol. 2015;4:507-15). Volume of distribution was modelled by a minimal PBPK model. Clearance was modelled nonmechanistically. Drug-drug interaction (DDI) toward different CYP substrates (caffeine [CYP1A2], s-warfarin [CYP2C9], omeprazole [CYP2C19], midazolam and cyclosporine [CYP3A4 and CYP3A5], and simvastatin [CYP3A4]) were evaluated where substrates were administered as a single dose when the minimum (or the maximum for CYP1A2) enzymatic activity was reached. First, ability of the PBPK model to capture such DDI was validated using data from the literature (Schmitt C et al. Clin Pharmacol Ther. 2011;89:735-40; Jiang X et al. AAPS J. 2016;18:767-76). Then, prospective simulations were performed using observed IL-6 data following teclistamab administered at RP2D without or prior to tocilizumab administration in MajesTEC-1 as of a March 16, 2022, cut-off. Observed data were recovered by adjusting the dosing regimen of IL-6, modelled as an intravenous infusion. Two scenarios were envisioned: the observed IL-6 mean serum profile and the worst-case scenario, corresponding to the IL-6 profile observed in the patient presenting the highest IL-6 Cmax value. In addition, the time to reach the maximum change in CYP activity due to IL-6, and the return to 80% of the baseline enzymatic activity, were evaluated, with the start of cycle 1 as reference. Results: Observed DDIs from literature with CYP1A2, CYP2C9, CYP2C19, CYP3A4, and CYP3A5 substrates in the presence of steady state concentrations of IL-6 at 50 pg/mL were well predicted, providing confidence in the application of the model to assess IL-6 as a perpetrator of these CYP substrates. Using the PBPK model, the IL-6 kinetic profile following teclistamab administered at RP2D was predicted to result in a limited change in exposure of CYP1A2, CYP2C9, CYP2C19, CYP3A4, and CYP3A5 substrates (0.87 ≤ area under the curve [AUC] ratio ≤ 1.20) when mean IL-6 profile was considered (mean Cmax = 21 pg/mL). When the IL-6 kinetic profile with the highest Cmax (288 pg/mL) was considered, the impact on the exposure of CYP2C19, CYP3A4, and CYP3A5 substrates (eg, omeprazole, simvastatin, cyclosporine) could be moderate (1.90 ≤ AUC ratio ≤ 2.23), and the impact on the exposure of CYP1A2 and CYP2C9 substrates (eg, caffeine and s-warfarin) was minimal (AUC ratio = 0.82 and 1.25, respectively). For both scenarios, the maximum change in exposure for the studied substrates occurred 3 to 4 days after the start of cycle 1. For the patient with the highest IL-6 Cmax, return to 80% of the baseline enzymatic activity was observed approximately 7 days after the start of cycle 1. Conclusions: PBPK modeling and simulation results suggested DDI from IL-6 effect on CYP450 activities to have little clinical significance with minimal or moderate impact on CYP substrates up to 7 days after teclistamab first treatment dose in cycle 1 or during a cytokine release syndrome event.

Review of the Existing Translational Pharmacokinetics Modeling Approaches Specific to Monoclonal Antibodies (mAbs) to Support the First-In-Human (FIH) Dose Selection.

The interest in therapeutic monoclonal antibodies (mAbs) has continuously growing in several diseases. However, their pharmacokinetics (PK) is complex due to their target-mediated drug disposition (TMDD) profiles which can induce a non-linear PK. This point is particularly challenging during the pre-clinical and translational development of a new mAb. This article reviews and describes the existing PK modeling approaches used to translate the mAbs PK from animal to human for intravenous (IV) and subcutaneous (SC) administration routes. Several approaches are presented, from the most empirical models to full physiologically based pharmacokinetic (PBPK) models, with a focus on the population PK methods (compartmental and minimal PBPK models). They include the translational approaches for the linear part of the PK and the TMDD mechanism of mAbs. The objective of this article is to provide an up-to-date overview and future perspectives of the translational PK approaches for mAbs during a model-informed drug development (MIDD), since the field of PK modeling has gained recently significant interest for guiding mAbs drug development.

Physiologically-based pharmacokinetic modelling and dosing evaluation of gentamicin in neonates using PhysPK.

Each year, infections caused around the 25% of neonatal deaths. Early empirical treatments help to reduce this mortality, although optimized dosing regimens are still lacking. The aims were to develop and validate a gentamicin physiologically-based pharmacokinetic (PBPK) model and then potentially explore dosing regimens in neonates using pharmacokinetic and pharmacodynamic criteria. The PBPK model developed consisted of 2 flow-limited tissues: kidney and other tissues. It has been implemented on a new tool called PhysPK, which allows structure reusability and evolution as predictive engine in Model-Informed Precision Dosing (MIPD). Retrospective pharmacokinetic information based on serum levels data from 47 neonates with gestational age between 32 and 39 weeks and younger than one-week postnatal age were used for model validation. The minimal PBPK model developed adequately described the gentamicin serum concentration-time profile with an average fold error nearly 1. Extended interval gentamicin dosing regimens (6 mg/kg q36h and 6 mg/kg q48h for term and preterm neonates, respectively) showed efficacy higher than 99% with toxicity lower than 10% through Monte Carlo simulation evaluations. The gentamicin minimal PBPK model developed in PhysPK from literature information, and validated in preterm and term neonates, presents adequate predictive performance and could be useful for MIPD strategies in neonates.

A Minimal Physiologically Based Pharmacokinetic Model to Characterize CNS Distribution of Metronidazole in Neuro Care ICU Patients

Understanding antibiotic concentration-time profiles in the central nervous system (CNS) is crucial to treat severe life-threatening CNS infections, such as nosocomial ventriculitis or meningitis. Yet CNS distribution is likely to be altered in patients with brain damage and infection/inflammation. Our objective was to develop a physiologically based pharmacokinetic (PBPK) model to predict brain concentration-time profiles of antibiotics and to simulate the impact of pathophysiological changes on CNS profiles. A minimal PBPK model consisting of three physiological brain compartments was developed from metronidazole concentrations previously measured in plasma, brain extracellular fluid (ECF) and cerebrospinal fluid (CSF) of eight brain-injured patients. Volumes and blood flows were fixed to their physiological value obtained from the literature. Diffusion clearances characterizing transport across the blood–brain barrier and blood–CSF barrier were estimated from system- and drug-specific parameters and were confirmed from a Caco-2 model. The model described well unbound metronidazole pharmacokinetic profiles in plasma, ECF and CSF. Simulations showed that with metronidazole, an antibiotic with extensive CNS distribution simply governed by passive diffusion, pathophysiological alterations of membrane permeability, brain ECF volume or cerebral blood flow would have no effect on ECF or CSF pharmacokinetic profiles. This work will serve as a starting point for the development of a new PBPK model to describe the CNS distribution of antibiotics with more limited permeability for which pathophysiological conditions are expected to have a greater effect.

Population PBPK modeling using parametric and nonparametric methods of the Simcyp Simulator, and Bayesian samplers

Physiologically‐based pharmacokinetic (PBPK) models usually include a large number of parameters whose values are obtained using in vitro to in vivo extrapolation. However, such extrapolations can be uncertain and may benefit from inclusion of evidence from clinical observations via parametric inference. When clinical interindividual variability is high, or the data sparse, it is essential to use a population pharmacokinetics inferential framework to estimate unknown or uncertain parameters. Several approaches are available for that purpose, but their relative advantages for PBPK modeling are unclear. We compare the results obtained using a minimal PBPK model of a canonical theophylline dataset with quasi‐random parametric expectation maximization (QRPEM), nonparametric adaptive grid estimation (NPAG), Bayesian Metropolis‐Hastings (MH), and Hamiltonian Markov Chain Monte Carlo sampling. QRPEM and NPAG gave consistent population and individual parameter estimates, mostly agreeing with Bayesian estimates. MH simulations ran faster than the others methods, which together had similar performance.

Minimal Physiologically-based Pharmacokinetic Model to Investigate the Effect of Charge on the Pharmacokinetics of Humanized anti-HCV-E2 IgG Antibodies in Sprague-Dawley Rats.

To develop a minimal physiologically-based pharmacokinetic (mPBPK) model in quantifying the relationships between the charge and pharmacokinetics (PK) of therapeutic monoclonal IgG antibody (TMAb). PK data used in this study were native IgG and five humanized anti-HCVE2-IgG antibodies in rats. Different models that related the effect of charge on interstitial distribution, transcapillary transport, and cellular uptake for FcRn-mediated metabolism were tested. External validation was conducted to assess if the charge-parameter relationships derived from rats could be used to predict the PK of TMAbs in mice. The final mPBPK model was used to construct the relationships between the FcRn binding and charge on the PK of TMAbs. Increasing the isoelectric point (pI) of IgG was associated with higher interstitial space distribution and cellular uptake. The transcapillary transport of IgG from plasma to interstitial space remains constant with pI values below 7.96 and then increased linearly with pI. The model-based simulation results suggested that improving the FcRn binding affinity can overcome the problems of low plasma/interstitial space exposures associated with TMAbs with higher pI values by reducing the FcRn-mediated metabolism and hence increasing drug exposure in the interstitial space that has close contact with many solid tumors. The final mPBPK model was developed and used to construct complex quantitative relationships between the pI/FcRn binding affinity and PK of TMAbs and such relationships are useful to select the discovery of a "sweet spot" of designing future generation of TMAbs with optimal PK properties to achieve desirable plasma and tissue drug exposures.

Model-Based Assessment of the Contribution of Monocytes and Macrophages to the Pharmacokinetics of Monoclonal Antibodies.

We have hypothesized that a high concentration of circulating monocytes and macrophages may contribute to the fast weight-based clearance of monoclonal antibodies (mAbs) in young children. Exploring this hypothesis, this work uses modeling to clarify the role of monocytes and macrophages in the elimination of mAbs. Leveraging pre-clinical data from mice, a minimal physiologically-based pharmacokinetic model was developed to characterize mAb uptake and FcRn-mediated recycling in circulating monocytes, macrophages, and endothelial cells. The model characterized IgG disposition in complex scenarios of site-specific FcRn deletion and variable endogenous IgG levels. Evaluation was performed for predicting IgG disposition with co-administration of high dose IVIG. A one-at-a-time sensitivity analysis quantified the role of relevant cellular parameters on IgG elimination in various scenarios. The plasma AUC of mAbs was highly sensitive to endothelial cell parameters, but had near-nil sensitivity to monocyte and macrophage parameters, even in scenarios with 90% loss of FcRn expression/activity. In mice with normal FcRn expression, simulations suggest that less than 2% of an IV dose is eliminated in macrophages, while endothelial cells are predicted to dominate mAb elimination. The model suggests that the role of monocytes and macrophages in IgG homeostasis includes extensive uptake and highly efficient FcRn-mediated protection, but not appreciable degradation when FcRn is present. Therefore, it is very unlikely that a high concentration of circulating monocytes can contribute to explaining the fast weight-based clearance of mAbs in very young children, even if FcRn expression/activity was 90% lower in children than in adults.

Extrapolation of physiologically based pharmacokinetic model for tacrolimus from renal to liver transplant patients

Physiologically based pharmacokinetic (PBPK) modeling is useful for evaluating differences in drug exposure among special populations, but it has not yet been employed to evaluate the absorption process of tacrolimus. In this study, we developed a minimal PBPK model with a compartmental absorption and transit model for renal transplant patients using available data in the literature and clinical data from our hospital. The effective permeability value of tacrolimus absorption and parameters for the single adjusting compartment were optimized via sensitivity analyses, generating a PBPK model of tacrolimus for renal transplant patients with good predictability. Next, we extrapolated the pharmacokinetics of tacrolimus for liver transplant patients by changing the population demographic parameters of the model. When the physiological parameters of a population with normal liver function were changed to those of a population with impaired hepatic function (Child-Pugh class A) in the constructed renal transplant PBPK model, the predicted tacrolimus concentrations were consistent with the observed concentrations in liver transplant patients. In conclusion, the constructed tacrolimus PBPK model for renal transplant patients could predict the pharmacokinetics in liver transplant patients by slightly reducing the hepatic function, even at three weeks post-transplantation.

A minimal physiologically based pharmacokinetic model for high-dose methotrexate

PurposeHigh-dose methotrexate (HDMTX) is administered for the treatment of a variety of malignant tumors. Wide intra- and inter-individual variabilities characterize the pharmacokinetics of MTX, which is mostly excreted renally. HDMTX dosages are prescribed as a function of body surface area whereas dose adjustments depending on renal function are not well defined. We develop a population pharmacokinetic model with a physiological description of renal excretion as the basis for clinical tools able to suggest model-informed dosages and support therapeutic monitoring.MethodsThis article presents a minimal physiologically based pharmacokinetic (PBPK) model for HDMTX, which specifically accounts for individual characteristics such as body weight, height, gender, age, hematocrit, and serum creatinine to provide individualized predictions. The model supplies a detailed and mechanistic description of capillary and cellular exchanges between plasma, interstitial fluid, and intracellular fluid compartments, and focuses on an individualized description of renal excretion.ResultsThe minimal PBPK model is identified and validated with a literature dataset based on Chinese patients suffering from primary central nervous system lymphoma. A comparison with a pharmacokinetic model from the literature suggests that the proposed model provides improved predictions. Remarkably, the model does not present any significant bias in a wide range of degrees of renal function.ConclusionResults show that model predictions can capture the wide intra- and inter-individual variability of HDMTX, and highlight the role played by the individual degree of renal function. The proposed model can be the basis for the development of clinical decision-support systems for individualized dosages and therapeutic monitoring.

PBPK Model of Coproporphyrin I: Evaluation of the Impact of SLCO1B1 Genotype, Ethnicity, and Sex on its Inter-Individual Variability.

Coproporphyrin I (CPI) is an endogenous biomarker of OATP1B activity and associated drug‐drug interactions. In this study, a minimal physiologically‐based pharmacokinetic model was developed to investigate the impact of OATP1B1 genotype (c.521T>C), ethnicity, and sex on CPI pharmacokinetics and interindividual variability in its baseline. The model implemented mechanistic descriptions of CPI hepatic transport between liver blood and liver tissue and renal excretion. Key model parameters (e.g., endogenous CPI synthesis rate, and CPI hepatic uptake clearance) were estimated by fitting the model simultaneously to three independent CPI clinical datasets (plasma and urine data) obtained from white (n = 16, men and women) and Asian‐Indian (n = 26, all men) subjects, with c.521 variants (TT, TC, and CC). The optimized CPI model successfully described the observed data using c.521T>C genotype, ethnicity, and sex as covariates. CPI hepatic active was 79% lower in 521CC relative to the wild type and 42% lower in Asian‐Indians relative to white subjects, whereas CPI synthesis was 23% higher in male relative to female subjects. Parameter sensitivity analysis showed marginal impact of the assumption of CPI synthesis site (blood or liver), resulting in comparable recovery of plasma and urine CPI data. Lower magnitude of CPI‐drug interaction was simulated in 521CC subjects, suggesting the risk of underestimation of CPI‐drug interaction without prior OATP1B1 genotyping. The CPI model incorporates key covariates contributing to interindividual variability in its baseline and highlights the utility of the CPI modeling to facilitate the design of prospective clinical studies to maximize the sensitivity of this biomarker.

Development of a Minimal Physiologically-Based Pharmacokinetic Model to Simulate Lung Exposure in Humans Following Oral Administration of Ivermectin for COVID-19 Drug Repurposing

SARS-CoV-2 utilizes the IMPα/β1 heterodimer to enter host cell nuclei after gaining cellular access through the ACE2 receptor. Ivermectin has shown antiviral activity by inhibiting the formation of the importin-α (IMPα) and IMPβ1 subunits as well as dissociating the IMPα/β1 heterodimer and has in vitro efficacy against SARS-CoV-2. Plasma and lung ivermectin concentrations vs. time profiles in cattle were used to determine the apparent plasma to lung tissue partition coefficient of ivermectin. This coefficient, together with a simulated geometric mean plasma profile of ivermectin from a published population pharmacokinetic model, was utilized to develop a minimal physiologically-based pharmacokinetic (mPBPK) model. The mPBPK model accurately described the simulated ivermectin plasma concentration profile in humans. The mPBPK model was also used to simulate human lung exposure to ivermectin after 12, 30, and 120 mg oral doses. The simulated ivermectin lung exposures reached a maximum concentration of 772 ng/mL, far less than the estimated 1750 ng/mL IC50 reported for ivermectin against SARS-CoV-2 in vitro. Further studies of ivermectin either reformulated for inhaled delivery or in combination with other antivirals with differing mechanisms of action is needed to assess its therapeutic potential.