Application of Physiologically Based Pharmacokinetic (PBPK) Modeling to Support Dose Selection: Report of an FDA Public Workshop on PBPK

Physiologically Based Pharmacokinetic Modeling to Predict Drug-Drug Interactions of Soticlestat as a Victim of CYP Induction and Inhibition, and as a Perpetrator of CYP and P-Glycoprotein Inhibition

Soticlestat (TAK-935) is a cholesterol 24-hydroxylase inhibitor. A physiologically-based pharmacokinetic model has been developed to predict potential soticlestat drug-drug interactions (DDIs) using the Simcyp v20 Population-based Simulator and verified with data from single-/multiple-rising-dose and clinical DDI studies. Simulated area under the plasma concentration-time curve from 0 to infinity (AUC0-inf) and maximal drug concentration (Cmax) based on the model were generally within 2-fold of observed values for all soticlestat doses. Model-simulated versus observed AUC0-inf and Cmax geometric mean ratios (GMRs) for soticlestat with/without itraconazole (potent cytochrome P450 [CYP] 3A inhibitor), and mefenamic acid (potent UDP glucuronosyltransferase [UGT] 1A9 inhibitor) were ≤1.10-fold. As soticlestat is primarily metabolized by UGT enzymes and Simulator v20 incorporates rifampin's induction of CYP3A only, the model underpredicted soticlestat's DDI with rifampin. However, with user-defined rifampin UGT induction, the predicted AUC0-inf GMR was within 1.5-fold of the observed value, meeting the 2-fold acceptance criteria. Hence, the model was appropriate for evaluating DDIs with CYP3A inhibitors and inducers not evaluated in clinical DDI studies; all predicted DDIs were low/not clinically relevant (<50% impact on exposure). Furthermore, no clinically significant DDIs were predicted following coadministration of soticlestat with sensitive CYP2C8, CYP2C9, CYP2C19, CYP3A4, and P-glycoprotein substrates.

Ritonavir May Prolong Sedation but is Unlikely to Increase the Risk of Respiratory Arrest in Patients Requiring Intravenous Midazolam for Procedural Sedation

Intravenous midazolam is frequently used for procedural sedation. Use of ritonavir containing antivirals in patients requiring procedural sedation with intravenous midazolam is postulated to increase the risk or prolong the consequences of exposure related adverse events. The primary objective of this study was to characterize interaction of ritonavir with IV midazolam. The secondary objective was to define the time course over with the interaction of ritonavir with IV midazolam resolves following cessation of ritonavir. Physiologically based pharmacokinetic modeling was used to conduct clinical trials with a parallel group design defining exposure to a single 5 mg IV dose of midazolam in the presence and absence of nirmatrelvir/ritonavir dosed twice daily for 5 days. Simulations comprised 50 virtual healthy subjects aged 20 to 50 years (50% female). Based on FDA criteria, a moderate/strong interaction between nirmatrelvir/ritonavir and intravenous midazolam (area under the curve [AUC] ratio >2) was observed when intravenous midazolam was administered up to 72 h following cessation of nirmatrelvir/ritonavir. The geometric mean (90% CI) midazolam AUC ratio was 9.21 (5.44 to 16.43) when coadministered on the final day of nirmatrelvir/ritonavir dosing. Importantly, there was no change in peak exposure; the geometric mean (90% CI) midazolam maximum concentration ratio was 0.99 (0.99 to 1.00). Use of ritonavir containing antivirals is unlikely to increase a patient's risk of experiencing an exposure related adverse event following administration of intravenous midazolam but may prolong complications in patients who experience an event. A meaningful interaction persists for 72 h following cessation of nirmatrelvir/ritonavir.

Insights into preclinical evaluation of dissolvable microarray patches

Drug-loaded dissolvable microarray patches (MAP) have gained significant attention due to their patient-friendly, economical, and environmentally beneficial attributes. Despite extensive research and advancements, only a limited number of MAP have progressed to clinical trials. While existing literature predominantly covers the initial stages of MAP development (e.g., manufacturing techniques, materials, design), there remains a notable gap in examining an experimental design during preclinical evaluation phase undertaken to inform progression to clinical studies. To address this gap, we present a comprehensive review of the experimental factors influencing MAP performance in preclinical research. Our in-depth analysis of the skin environment and its implications to in vitro MAP performance revealed that skin insertion methodology, media used for release and permeation testing, skin models for permeation studies, and skin metabolism are key factors that need to be considered. We critically assess current research trends and propose potential optimisations to enhance efficacy and biorelevance of in vitro methods for MAP. Additionally, we review factors influencing in vivo and in silico performance, underscoring the promising potential of in silico approaches. This article aims to provide insights that will facilitate the development and standardisation of reliable methodologies in preclinical studies of drug-loaded MAP, ultimately advancing their clinical translation.

Leveraging Omeprazole PBPK/PD Modeling to Inform Drug-Drug Interactions and Specific Recommendations for Pediatric Labeling

Background/Objectives: Omeprazole is widely used for managing gastrointestinal disorders like GERD, ulcers, and H. pylori infections. However, its use in pediatrics presents challenges due to drug interactions (DDIs), metabolic variability, and safety concerns. Omeprazole's pharmacokinetics (PK), primarily influenced by CYP2C19 metabolism, is affected by ontogenetic changes in enzyme expression, complicating dosing in children. Methods: This study aimed to develop and validate a physiologically based pharmacokinetic (PBPK) model for omeprazole and its metabolites to predict age-related variations in metabolism and response. Results: The PBPK model successfully predicted exposure to parent and metabolites in adults and pediatrics, incorporating competitive and mechanism-based inhibition of CYP2C19 and CYP3A4 by omeprazole and its metabolites. By accounting for age-dependent metabolic pathways, the model enabled priori predictions of omeprazole exposure in different age groups. Linking PK to the pharmacodynamics (PD) model, we described the impact of age-related physiological changes on intragastric pH, the primary outcome for proton pump inhibitors efficacy. Conclusions: The PBPK-PD model allowed for the virtual testing of dosing scenarios, providing an alternative to clinical studies in pediatrics where traditional DDI studies are challenging. This approach offers valuable insights for accurate dosing recommendations in pediatrics, accounting for age-dependent variability in metabolism, and underscores the potential of PBPK modeling in guiding pediatric drug development.

Assessing Drug-Drug Interaction and Food Effect for BCS Class 2 Compound BI 730357 (Retinoic Acid-Related Orphan Receptor Gamma Antagonist, Bevurogant) Using a Physiology-Based Pharmacokinetics Modeling (PBPK) Approach with Semi-Mechanistic Absorption

Background: The drug candidate BI 730357 is a Biopharmaceutics Classification System (BCS) Class II compound showing atypical absorption after oral administration in fasted and fed healthy individuals, for which conventional traditional deconvolution methods could not explain formulation dependencies. Methods: A physiologically based pharmacokinetic (PBPK) model of BI 730357 was developed using the Open Systems Pharmacology (OSP) PBPK software tool PK-Sim®, which could describe the pharmacokinetics in fasted and fed subjects after single and multiple doses. A Weibull function was used to describe the in vivo formulation kinetics, whereas colonic absorption was adopted as the main driver to describe the late phases of observed pharmacokinetics after oral administration. The food effect was applied using the implemented feature PK-Sim®. Results: The model accurately predicted an observed itraconazole drug-drug interaction (DDI) in fasted subjects and was used to explore the effects of the strong CYP3A4 inducer rifampicin on the pharmacokinetics of BI 730357 after administration in fed subjects. Conclusions: The combined results suggest that the BI 730357 PBPK model with semi-mechanistic absorption can prospectively explore the effects of CYP3A4 inhibitors and inducers on the pharmacokinetics after administration in fed or fasted subjects within the given dose range.

Evaluation of BCRP-Related DDIs Between Methotrexate and Cyclosporin A Using Physiologically Based Pharmacokinetic Modelling

BACKGROUND AND OBJECTIVE

This study provides a physiologically based pharmacokinetic (PBPK) model-based analysis of the potential drug-drug interaction (DDI) between cyclosporin A (CsA), a breast cancer resistance protein transporter (BCRP) inhibitor, and methotrexate (MTX), a putative BCRP substrate.

METHODS

PBPK models for CsA and MTX were built using open-source tools and published data for both model building and for model verification and validation. The MTX and CsA PBPK models were evaluated for their application in simulating BCRP-related DDIs. A qualification of an introduced empirical uniform in vitro scaling factor of Ki values for transporter inhibition by CsA was conducted by using a previously developed model of rosuvastatin (sensitive index BCRP substrate), and assessing if corresponding DDI ratios were well captured.

RESULTS

Within the simulated DDI scenarios for MTX in the presence of CsA, the developed models could capture the observed changes in PK parameters as changes in the area under the curve ratios (area under the curve during DDI/area under the curve control) of 1.30 versus 1.31 observed and the DDI peak plasma concentration ratios (peak plasma concentration during DDI/peak plasma concentration control) of 1.07 versus 1.28 observed. The originally reported in vitro Ki values of CsA were scaled with the uniform qualified scaling factor for their use in the in vivo DDI simulations to correct for the low intracellular unbound fraction of the CsA effector concentration. The resulting predicted versus observed ratios of peak plasma concentration and area under the curve DDI ratios with MTX were 0.82 and 0.99, respectively, indicating adequate model accuracy and choice of a scaling factor to capture the observed DDI.

CONCLUSIONS

All models have been comprehensively documented and made publicly available as tools to support the drug development and clinical research community and further community-driven model development.

Building Confidence in Physiologically Based Pharmacokinetic Modeling of CYP3A Induction Mediated by Rifampin: An Industry Perspective

Physiologically-based pharmacokinetic (PBPK) modeling offers a viable approach to predict induction drug-drug interactions (DDIs) with the potential to streamline or reduce clinical trial burden if predictions can be made with sufficient confidence. In the current work, the ability to predict the effect of rifampin, a well-characterized strong CYP3A4 inducer, on 20 CYP3A probes with publicly available PBPK models (often developed using a workflow with optimization following a strong inhibitor DDI study to gain confidence in fraction metabolized by CYP3A4, fm,CYP3A4, and fraction available after intestinal metabolism, Fg), was assessed. Substrates with a range of fm,CYP3A4 (0.086-1.0), Fg (0.11-1.0) and hepatic availability (0.09-0.96) were included. Predictions were most often accurate for compounds that are not P-gp substrates or that are P-gp substrates but that have high permeability. Case studies for three challenging DDI predictions (i.e., for eliglustat, tofacitinib, and ribociclib) are presented. Along with parameter sensitivity analysis to understand key parameters impacting DDI simulations, alternative model structures should be considered, for example, a mechanistic absorption model instead of a first-order absorption model might be more appropriate for a P-gp substrate with low permeability. Any mechanisms pertinent to the CYP3A substrate that rifampin might impact (e.g., induction of other enzymes or P-gp) should be considered for inclusion in the model. PBPK modeling was shown to be an effective tool to predict induction DDIs with rifampin for CYP3A substrates with limited mechanistic complications, increasing confidence in the rifampin model. While this analysis focused on rifampin, the learnings may apply to other inducers.

Applications of pharmacometrics in drug development

The last two decades have witnessed profound changes in how advanced computational tools can help leverage tons of data to improve our knowledge, and ultimately reduce cost and increase productivity in drug development. Pharmacometrics has demonstrated its impact through model-informed drug development (MIDD) approaches. It is now an indispensable component throughout the whole continuum of drug discovery, development, regulatory review, and approval. Today, applications of pharmacometrics are common in designing better trials and accelerating evidence-based decisions. Newly emerging technologies, especially those from data and computer sciences, are being integrated with existing computational tools used in the pharmaceutical industry at a remarkably fast pace. The new challenges faced by the pharmacometrics community are not what or how to contribute, but which optimal MIDD strategy should be adopted to maximize its value in the decision-making process. While we are embracing new innovative approaches and tools, this article discusses how a variety of existing modeling tools, with differentiated advantages and focus, can work in concert to inform drug development.

Reprint of: Does two-step infusion improve the pharmacokinetics/pharmacodynamics target attainment of meropenem in critically Ill patients?

The optimal method for administering meropenem remains controversial. This study was conducted to explore the optimal two-step infusion strategy (TIT), and to investigate whether TIT is superior to intermittent infusion therapy (IIT) and prolonged infusion therapy (PIT). A physiologically based pharmacokinetics model for critically ill patients was established and evaluated. The validated model was utilized to evaluate the pharmacokinetics/pharmacodynamics (PK/PD) target attainment of meropenem. The PK/PD target attainment of different TITs varied greatly, and the total infusion duration and the first-step dose greatly affected these values. The optimal TIT was 0.25 g (30 min) + 0.75 g (150 min) at MICs of ≤2 mg/L, and 0.25 g (45 min) + 0.75 g (255 min) at MICs of 4-8 mg/L. The PK/PD target attainment of optimal TIT, PIT, and IIT were 100 % at MICs of ≤1 mg/L. When MIC increased to 2-8 mg/L, the PK/PD target attainment of optimal TIT was similar to that of PIT and higher than IIT. In conclusion, TIT did not significantly improve the PK/PD target attainment of meropenem compared with PIT. IIT is adequate at MICs of ≤1 mg/L, and PIT may be the optimal meropenem infusion method in critically ill patients with MICs of 2-8 mg/L.

Physiologically based pharmacokinetic modeling of small molecules: How much progress have we made?

Physiologically based pharmacokinetic (PBPK) models of small molecules have become mainstream in drug development and in academic research. The use of PBPK models is continuously expanding, with the majority of work now focusing on predictions of drug-drug interactions, drug-disease interactions, and changes in drug disposition across lifespan. Recently, publications that use PBPK modeling to predict drug disposition during pregnancy and in organ impairment have increased reflecting the advances in incorporating diverse physiologic changes into the models. Because of the expanding computational power and diversity of modeling platforms available, the complexity of PBPK models has also increased. Academic efforts have provided clear advances in better capturing human physiology in PBPK models and incorporating more complex mathematical concepts into PBPK models. Examples of such advances include the segregated gut model with a series of gut compartments allowing modeling of physiologic blood flow distribution within an organ and zonation of metabolic enzymes and series compartment liver models allowing simulations of hepatic clearance for high extraction drugs. Despite these advances in academic research, the progress in assessing model quality and defining model acceptance criteria based on the intended use of the models has not kept pace. This Minireview suggests that awareness of the need for predefined criteria for model acceptance has increased, but many manuscripts still lack description of scientific justification and/or rationale for chosen acceptance criteria. As artificial intelligence and machine learning approaches become more broadly accepted, these tools offer promise for development of comprehensive assessment for existing observed data and analysis of model performance. SIGNIFICANCE STATEMENT: Physiologically based pharmacokinetic (PBPK) modeling has become a mainstream application in academic literature and is broadly used for predictions, analysis, and evaluation of pharmacokinetic data. Significant progress has been made in developing advanced PBPK models that better capture human physiology, but oftentimes sufficient justification for the chosen model acceptance criterion and model structure is still missing. This Minireview provides a summary of the current landscape of PBPK applications used and highlights the need for advancing PBPK modeling science and training in academia.

Model-informed drug discovery and development approaches to inform clinical trial design and regulatory decisions: A primer for the MENA region

Model-Informed Drug Discovery and Development (MID3) represents a transformative approach in pharmaceutical research, integrating quantitative models to inform and optimize decision-making throughout the drug development process. This review explores the current applications, challenges, and future prospects of MID3 within the Middle East and North Africa (MENA) region. By leveraging local data and advanced computational techniques, MID3 has the potential to significantly enhance the efficiency and success rates of drug development tailored to regional health priorities. We discussed successful case studies of applying MID3 at different phases of drug development and clinical trials. Furthermore, we emphasized the critical need for MENA countries to embrace MID3 by investing in workforce training, aligning regulatory frameworks, and fostering collaborative research initiatives. This call to action underscores the importance of a robust MID3 ecosystem, urging policymakers, academic institutions, and industry stakeholders to prioritize and support its integration into the MENA region's healthcare.

Evaluation of the effect of modafinil on the pharmacokinetics of encorafenib and binimetinib in patients with BRAF V600-mutant advanced solid tumors

BACKGROUND

A clinical drug-drug interaction (DDI) study was designed to evaluate the effect of multiple doses of modafinil, a moderate CYP3A4 inducer at a 400 mg QD dose, on the multiple oral dose pharmacokinetics (PK) of encorafenib and its metabolite, LHY746 and binimetinib and its metabolite, AR00426032.

METHODS

This study was conducted in patients with BRAF V600-mutant advanced solid tumors. Treatment of 400 mg QD modafinil was given on Day 15 through Day 21. Encorafenib 450 mg QD and binimetinib 45 mg BID were administered starting on Day 1. PK sampling was conducted from 0 to 8 h on Day 14 and Day 21. Exposure parameters were calculated for each patient by noncompartmental analysis and geometric least-squares mean ratio. Corresponding 90% confidence intervals were calculated to estimate the magnitude of effects.

RESULTS

Among 11 PK evaluable patients, encorafenib Cmax and AUClast were decreased in presence of steady-state modafinil by 20.2% and 23.8%, respectively. LHY746 exposures were not substantially changed in the presence of steady-state modafinil.

CONCLUSION

The results from this clinical study indicate modafinil 400 mg QD had a weak effect on encorafenib PK. Based on these results, encorafenib can be coadministered with a moderate CYP3A4 inducer without dosing adjustment.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT03864042, registered 6 March 2019.

Does Two-Step Infusion Improve the Pharmacokinetics/Pharmacodynamics Target Attainment of Meropenem in Critically Ill Patients?

The optimal method for administering meropenem remains controversial. This study was conducted to explore the optimal two-step infusion strategy (TIT), and to investigate whether TIT is superior to intermittent infusion therapy (IIT) and prolonged infusion therapy (PIT). A physiologically based pharmacokinetics model for critically ill patients was established and evaluated. The validated model was utilized to evaluate the pharmacokinetics/pharmacodynamics (PK/PD) target attainment of meropenem. The PK/PD target attainment of different TITs varied greatly, and the total infusion duration and the first-step dose greatly affected these values. The optimal TIT was 0.25 g (30 min) + 0.75 g (150 min) at MICs of ≤2 mg/L, and 0.25 g (45 min) + 0.75 g (255 min) at MICs of 4-8 mg/L. The PK/PD target attainment of optimal TIT, PIT, and IIT were 100 % at MICs of ≤1 mg/L. When MIC increased to 2-8 mg/L, the PK/PD target attainment of optimal TIT was similar to that of PIT and higher than IIT. In conclusion, TIT did not significantly improve the PK/PD target attainment of meropenem compared with PIT. IIT is adequate at MICs of ≤1 mg/L, and PIT may be the optimal meropenem infusion method in critically ill patients with MICs of 2-8 mg/L.

Physiologically based pharmacokinetic models for predicting lamotrigine exposure and dose optimization in pediatric patients receiving combination therapy with carbamazepine or valproic acid

INTRODUCTION

Lamotrigine (LTG) is an antiepileptic drug that has been used in pediatric epilepsy as a combination therapy or monotherapy after stabilization in recent years. However, there are significant drug-drug interactions (DDI) between LTG and combined drugs such as carbamazepine (CBZ) and valproic acid (VPA). It is particularly important to consider the risk of DDI in combination therapy for intractable epilepsy in pediatric patients. Therefore, it is necessary to adjust the dosage of LTG accordingly. The aim of this study was to establish and validate a pediatric physiologically based pharmacokinetic (PBPK) model for predicting LTG exposure. The model is designed to explore the potential for quantifying pharmacokinetic (PK) DDI of LTG when administered concurrently with CBZ or VPA in pediatric patients.

METHOD

Adult and pediatric PBPK models for LTG and VPA were developed using PK-Sim® software in combination with physiological information and drug-specific parameters, and a DDI model was developed in combination with the published CBZ model. The models were validated against available PK data.

RESULTS

Predictive and observational results in adults, children, and the DDI model were in good agreement. The recommended doses of LTG for preschool children (2-6 years) and school-aged children (6-12 years) in the absence of drug interactions were 1.47 and 1.2 times higher than those for adults, respectively; 3.1 and 2.6 times higher than those for adults in combination with CBZ; and 0.67 and 0.57 times lower than those for adults in combination with VPA. In addition, plasma exposures in adolescents (12-18 years) were similar to those in adults at the same doses.

CONCLUSION

We have successfully developed PBPK models and DDI models for LTG in adults and children, which provide a reference for rational drug use in the pediatric population.

Application of physiologically based pharmacokinetic modeling of novel drugs approved by the U.S. food and drug administration

Physiologically based pharmacokinetic (PBPK) models which can leverage preclinical data to predict the pharmacokinetic properties of drugs rapidly became an essential tool to improve the efficiency and quality of novel drug development. In this review, by searching the Application Review Files in Drugs@FDA, we analyzed the current application of PBPK models in novel drugs approved by the U.S. Food and Drug Administration (FDA) in the past five years. According to the results, 243 novel drugs were approved by the FDA from 2019 to 2023. During this period, 74 Application Review Files of novel drugs approved by the FDA that used PBPK models. PBPK models were used in various areas, including drug-drug interactions (DDI), organ impairment (OI) patients, pediatrics, drug-gene interaction (DGI), disease impact, and food effects. DDI was the most widely used area of PBPK models for novel drugs, accounting for 74.2 % of the total. Software platforms with graphical user interfaces (GUI) have reduced the difficulty of PBPK modeling, and Simcyp was the most popular software platform among applicants, with a usage rate of 80.5 %. Despite its challenges, PBPK has demonstrated its potential in novel drug development, and a growing number of successful cases provide experience learned for researchers in the industry.

Effect of Obesity on the Exposure of Long-acting Cabotegravir and Rilpivirine: A Modeling Study

BACKGROUND

Obesity is increasingly prevalent among people with human immunodeficiency virus (HIV, PWH). Obesity can reduce drug exposure; however, limited data are available for long-acting (LA) antiretrovirals. We performed in silico trials using physiologically based pharmacokinetic (PBPK) modeling to determine the effect of obesity on the exposure of LA cabotegravir and rilpivirine after the initial injection and after multiple injections.

METHODS

Our PBPK model was verified against available clinical data for LA cabotegravir and rilpivirine in normal weight/ overweight (body mass index [BMI] <30 kg/m2) and in obese (BMI >30 kg/m2). Cohorts of virtual individuals were generated to simulate the exposure of LA cabotegravir/rilpivirine up to a BMI of 60 kg/m2. The fold change in LA cabotegravir and rilpivirine exposures (area under the curve [AUC]) and trough concentrations (Cmin) for monthly and bimonthly administration were calculated for various BMI categories relative to normal weight (18.5-25 kg/m2).

RESULTS

Obesity was predicted to impact more cabotegravir than rilpivirine with a decrease in cabotegravir AUC and Cmin of >35% for BMI >35 kg/m2 and in rilpivirine AUC and Cmin of >18% for BMI >40 kg/m2 at steady-state. A significant proportion of morbidly obese individuals were predicted to have both cabotegravir and rilpivirine Cmin below the target concentration at steady-state with the bimonthly administration, but this was less frequent with the monthly administration.

CONCLUSIONS

Morbidly obese PWH are at risk of presenting suboptimal Cmin for cabotegravir/rilpivirine after the first injection but also at steady-state particularly with the bimonthly administration. Therapeutic drug monitoring is advised to guide dosing interval adjustment.

Physiologically based pharmacokinetic modeling in obesity: applications and challenges

INTRODUCTION

Rising global obesity rates pose a threat to people's health. Obesity causes a series of pathophysiologic changes, making the response of patients with obesity to drugs different from that of nonobese, thus affecting the treatment efficacy and even leading to adverse events. Therefore, understanding obesity's effects on pharmacokinetics is essential for the rational use of drugs in patients with obesity.

AREAS COVERED

Articles related to physiologically based pharmacokinetic (PBPK) modeling in patients with obesity from inception to October 2023 were searched in PubMed, Embase, Web of Science and the Cochrane Library. This review outlines PBPK modeling applications in exploring factors influencing obesity's effects on pharmacokinetics, guiding clinical drug development and evaluating and optimizing clinical use of drugs in patients with obesity.

EXPERT OPINION

Obesity-induced pathophysiologic alterations impact drug pharmacokinetics and drug-drug interactions (DDIs), altering drug exposure. However, there is a lack of universal body size indices or quantitative pharmacology models to predict the optimal for the patients with obesity. Therefore, dosage regimens for patients with obesity must consider individual physiological and biochemical information, and clinically individualize therapeutic drug monitoring for highly variable drugs to ensure effective drug dosing and avoid adverse effects.

Characterization of Pediatric Rectal Absorption, Drug Disposition, and Sedation Level for Midazolam Gel Using Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling

This study aims to explore and characterize the role of pediatric sedation via rectal route. A pediatric physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) model of midazolam gel was built and validated to support dose selection for pediatric clinical trials. Before developing the rectal PBPK model, an intravenous PBPK model was developed to determine drug disposition, specifically by describing the ontogeny model of the metabolic enzyme. Pediatric rectal absorption was developed based on the rectal PBPK model of adults. The improved Weibull function with permeability, surface area, and fluid volume parameters was used to extrapolate pediatric rectal absorption. A logistic regression model was used to characterize the relationship between the free concentrations of midazolam and the probability of sedation. All models successfully described the PK profiles with absolute average fold error (AAFE) < 2, especially our intravenous PBPK model that extended the predicted age to preterm. The simulation results of the PD model showed that when the free concentrations of midazolam ranged from 3.9 to 18.4 ng/mL, the probability of "Sedation" was greater than that of "Not-sedation" states. Combined with the rectal PBPK model, the recommended sedation doses were in the ranges of 0.44-2.08 mg/kg for children aged 2-3 years, 0.35-1.65 mg/kg for children aged 4-7 years, 0.24-1.27 mg/kg for children aged 8-12 years, and 0.20-1.10 mg/kg for adolescents aged 13-18 years. Overall, this model mechanistically quantified drug disposition and effect of midazolam gel in the pediatric population, accurately predicted the observed clinical data, and simulated the drug exposure for sedation that will inform dose selection for following pediatric clinical trials.

Modeling the complexity of drug-drug interactions: A physiologically-based pharmacokinetic study of Lenvatinib with Schisantherin A/Schisandrin A

BACKGROUND

Lenvatinib's efficacy as a frontline targeted therapy for radioactive iodine-refractory thyroid carcinoma and advanced hepatocellular carcinoma owes to its inhibition of multiple tyrosine kinases. However, as a CYP3A4 substrate, lenvatinib bears susceptibility to pharmacokinetic modulation by co-administered agents. Schisantherin A (STA) and schisandrin A (SIA) - bioactive lignans abundant in the traditional Chinese medicinal Wuzhi Capsule - act as CYP3A4 inhibitors, engendering the potential for drug-drug interactions (DDIs) with lenvatinib.

METHODS

To explore potential DDIs between lenvatinib and STA/SIA, we developed a physiologically-based pharmacokinetic (PBPK) model for lenvatinib and used it to construct a DDI model for lenvatinib and STA/SIA. The model was validated with clinical trial data and used to predict changes in lenvatinib exposure with combined treatment.

RESULTS

Following single-dose administration, the predicted area under the plasma concentration-time curve (AUC) and maximum plasma concentrations (Cmax) of lenvatinib increased 1.00- to 1.03-fold and 1.00- to 1.01-fold, respectively, in the presence of STA/SIA. Simulations of multiple-dose regimens revealed slightly greater interactions, with lenvatinib AUC0-t and Cmax increasing up to 1.09-fold and 1.02-fold, respectively.

CONCLUSION

Our study developed the first PBPK and DDI models for lenvatinib as a victim drug. STA and SIA slightly increased lenvatinib exposure in simulations, providing clinically valuable information on the safety of concurrent use. Given the minimal pharmacokinetic changes, STA/SIA are unlikely to interact with lenvatinib through pharmacokinetic alterations synergistically but rather may enhance efficacy through inherent anti-cancer efficacy of STA/ SIA.

Research Landscape of Physiologically Based Pharmacokinetic Model Utilization in Different Fields: A Bibliometric Analysis (1999-2023)

PURPOSE

The physiologically based pharmacokinetic (PBPK) modeling has received increasing attention owing to its excellent predictive abilities. However, there has been no bibliometric analysis about PBPK modeling. This research aimed to summarize the research development and hot points in PBPK model utilization overall through bibliometric analysis.

METHODS

We searched for publications related to the PBPK modeling from 1999 to 2023 in the Web of Science Core Collection (WoSCC) database. The Microsoft Office Excel, CiteSpace and VOSviewers were used to perform the analyses.

RESULTS

A total of 4,649 records from 1999 to 2023 were identified, and the largest number of publications focused in the period 2018-2023. The United States was the leading country, and the Environmental Protection Agency (EPA) was the leading institution. The journal Drug Metabolism and Disposition published and co-cited the most articles. Drug-drug interactions, special populations, and new drug development are the main topics in this research field.

CONCLUSION

We first visualize the research landscape and hotspots of the PBPK modeling through bibliometric methods. Our study provides a better understanding for researchers, especially beginners about the dynamization of PBPK modeling and presents the relevant trend in the future.

Drug Exposure of Long-Acting Cabotegravir and Rilpivirine in Older People With Human Immunodeficiency Virus: A Pharmacokinetic Modeling Study

Background

The life expectancy of people with human immunodeficiency virus (PWH) has significantly increased, thanks to combined antiretrovirals with improved potency and tolerability. One further step has been achieved with the development of long-acting (LA) injectable antiretrovirals, which allow for infrequent dosing. However, the pharmacokinetics of LA antiretrovirals has been poorly characterized in older PWH, as they are generally excluded from trials. We performed virtual studies using physiologically based pharmacokinetic (PBPK) modeling to determine the anticipated exposure of LA cabotegravir/rilpivirine in older individuals.

Methods

Our PBPK model was verified against available observed data for LA cabotegravir and rilpivirine. Cohorts of virtual individuals aged 20-50, 50-65, or 65-85 years were generated to simulate the exposure of LA cabotegravir/rilpivirine for each age group. The fold changes in trough concentration (Cmin) and in drug exposure (area under the time-concentration curve [AUC]) were determined for older relative to young individuals.

Results

The verified PBPK models predicted an increase in exposure within the 0.8-1.25 fold range for monthly LA cabotegravir/rilpivirine. The Cmin and AUC were predicted to be 29% and 26% higher in older compared with young adults for LA cabotegravir administered bimonthly (every 2 months) and 46% and 41% higher for LA rilpivirine bimonthly. The Cmin and AUC of LA cabotegravir and rilpivirine were predicted to be modestly increased in female compared with male individuals for all age groups.

Conclusions

LA cabotegravir/rilpivirine exposure and trough concentrations are predicted to be higher in older than in young PWH; thus, older adults could have a lower risk to present suboptimal concentrations during the dosing interval.

Utility of Physiologically Based Pharmacokinetic Modeling to Investigate the Impact of Physiological Changes of Pregnancy and Cancer on Oncology Drug Pharmacokinetics

BACKGROUND

The treatment of cancer during pregnancy remains challenging with knowledge gaps in drug dosage, safety, and efficacy due to the under-representation of this population in clinical trials. Our aim was to investigate physiological changes reported in both pregnancy and cancer populations into a PBPK modeling framework that allows for a more accurate estimation of PK changes in pregnant patients with cancer.

METHODS

Paclitaxel and docetaxel were selected to validate a population model using clinical data from pregnant patients with cancer. The validated population model was subsequently used to predict the PK of acalabrutinib in pregnant patients with cancer.

RESULTS

The Simcyp pregnancy population model reasonably predicted the PK of docetaxel in pregnant patients with cancer, while a modified model that included a 2.5-fold increase in CYP2C8 abundance, consistent with the increased expression during pregnancy, was needed to reasonably predict the PK of paclitaxel in pregnant patients with cancer. Changes in protein binding levels of patients with cancer had a minimal impact on the predicted clearance of paclitaxel and docetaxel. PBPK modeling predicted approximately 60% lower AUC and Cmax for acalabrutinib in pregnant versus non-pregnant patients with cancer.

CONCLUSIONS

Our results suggest that PBPK modeling is a promising approach to investigate the effects of pregnancy and cancer on the PK of oncology drugs and potentially inform dosing for pregnant patients with cancer. Further evaluation and refinement of the population model are needed for pregnant patients with cancer with additional compounds and clinical PK data.

In vitro and in vivo pharmacokinetic characterization, chiral conversion and PBPK scaling towards human PK simulation of S-MRI-1867, a drug candidate for Hermansky-Pudlak syndrome pulmonary fibrosis

Hermansky-Pudlak syndrome (HPS) is a rare autosomal recessive disorder that affects lysosome-related organelles, often leading to fatal pulmonary fibrosis (PF). The search for a treatment for HPS pulmonary fibrosis (HPSPF) is ongoing. S-MRI-1867, a dual cannabinoid receptor 1 (CB1R)/inducible nitric oxide synthase (iNOS) inhibitor, has shown great promise for the treatment of several fibrotic diseases, including HPSPF. In this study, we investigated the in vitro ADME characteristics of S-MRI-1867, as well as its pharmacokinetic (PK) properties in mice, rats, dogs, and monkeys. S-MRI-1867 showed low aqueous solubility (< 1 µg/mL), high plasma protein binding (>99%), and moderate to high metabolic stability. In its preclinical PK studies, S-MRI-1867 exhibited moderate to low plasma clearance (CLp) and high steady-state volume of distribution (Vdss) across all species. Despite the low solubility and P-gp efflux, S-MRI-1867 showed great permeability and metabolic stability leading to a moderate bioavailability (21-60%) across mouse, rat, dog, and monkey. Since the R form of MRI-1867 is CB1R-inactive, we investigated the potential conversion of S-MRI-1867 to R-MRI-1867 in mice and found that the chiral conversion was negligible. Furthermore, we developed and validated a PBPK model that adequately fits the PK profiles of S-MRI-1867 in mice, rats, dogs, and monkeys using various dosing regimens. We employed this PBPK model to simulate the human PK profiles of S-MRI-1867, enabling us to inform human dose selection and support the advancement of this promising drug candidate in the treatment of HPSPF.

PBPK Modelling for Drugs Cleared by Non-CYP Enzymes: State-of-the-Art and Future Perspectives

Physiologically-based pharmacokinetic (PBPK) modeling has become the established method for predicting human pharmacokinetics (PK) and drug-drug interactions (DDI). The number of drugs cleared by non-CYP enzyme metabolism has increased steadily and to date, there is no consolidated overview of PBPK modeling for drugs cleared by non-CYP enzymes. This review aims to describe the state-of-the-art for PBPK modeling for drugs cleared via non-CYP enzymes, to identify successful strategies, to describe gaps and to provide suggestion to overcome them. To this end, we conducted a detailed literature search and found 58 articles published before the 1st of January 2023 containing 95 examples of clinical PBPK models for 62 non-CYP enzyme substrates. Reviewed articles covered the drug clearance by uridine 5'-diphospho-glucuronosyltransferases (UGTs), aldehyde oxidase (AO), flavin-containing monooxygenases (FMOs), sulfotransferases (SULTs) and carboxylesterases (CES), with UGT2B7, UGT1A9, CES1, FMO3 and AO being the enzymes most frequently involved. In vitro-in vivo extrapolation (IVIVE) of intrinsic clearance and the bottom-up PBPK modeling involving non-CYP enzymes remains challenging. We observed that the middle-out modeling approach was applied in 80% of the cases, with metabolism parameters optimized in 73% of the models. Our review could not identify a standardized approach used for model optimization based on clinical data, with manual optimization employed most frequently. Successful development of models for UGT2B7, UGT1A9, CES1, and FMO3 substrates provides a foundation for other drugs metabolized by these enzymes and guides the way forward in creating PBPK models for other enzymes in these families. Significance Statement Our review charts the rise of PBPK modeling for drugs cleared by non-CYP enzymes. Analyzing 58 articles and 62 non-CYP enzyme substrates, we found that UGTs, AO, FMOs, SULTs, and CES were the main enzyme families involved and that UGT2B7, UGT1A9, CES1, FMO3 and AO are the individual enzymes with the strongest PBPK modeling precedents. Approaches established for these enzymes can now be extended to additional substrates and to drugs metabolized by enzymes that are similarly well characterized.

Applications of Modeling and Simulation Approaches in Support of Drug Product Development of Oral Dosage Forms and Locally Acting Drug Products: a Symposium Summary

The number of modeling and simulation applications, including physiologically based pharmacokinetic (PBPK) models, physiologically based biopharmaceutics modeling (PBBM), and empirical models, has been constantly increasing along with the regulatory acceptance of these methodologies. While aiming at minimizing unnecessary human testing, these methodologies are used today to support the development and approval of novel drug products and generics. Modeling approaches are leveraged today for assessing drug-drug interaction, informing dose adjustments in renally or hepatically impaired patients, perform dose selection in pediatrics and pregnant women and diseased populations, and conduct biopharmaceutics-related assessments such as establish clinically relevant specifications for drug products and achieve quality assurance throughout the product life cycle. In the generics space, PBPK analyses are utilized toward virtual bioequivalence assessments within the scope of alternative bioequivalence approaches, product-specific guidance development, and food effect assessments among others. Case studies highlighting the evolving and expanding role of modeling and simulation approaches within the biopharmaceutics space were presented at the symposium titled "Model Informed Drug Development (MIDD): Role in Dose Selection, Vulnerable Populations, and Biowaivers - Chemical Entities" and Prologue "PBPK/PBBM to inform the Bioequivalence Safe Space, Food Effects, and pH-mediated DDIs" at the American Association of Pharmaceutical Scientists (AAPS) PharmSci 360 Annual Meeting in Boston, MA, on October 16-19, 2022, and are summarized here.

Physiologically Based Pharmacokinetic Modeling and Simulation of Mavacamten Exposure with Drug-Drug Interactions from CYP Inducers and Inhibitors by CYP2C19 Phenotype

Mavacamten is a first-in-class, oral, selective, allosteric, reversible cardiac myosin inhibitor approved by the US Food and Drug Administration for the treatment of adults with symptomatic New York Heart Association functional class II-III obstructive hypertrophic cardiomyopathy. Mavacamten is metabolized in the liver, predominantly via cytochrome P450 (CYP) enzymes CYP2C19 (74%), CYP3A4 (18%), and CYP2C9 (8%). A physiologically-based pharmacokinetic (PBPK) model was developed using Simcyp version 19 (Certara, Princeton, NJ). Following model verification, the PBPK model was used to explore the effects of strong CYP3A4 and CYP2C19 inducers, and strong, moderate, and weak CYP2C19 and CYP3A4 inhibitors on mavacamten pharmacokinetics (PK) in a healthy population, with the effect of CYP2C19 phenotype predicted for poor, intermediate, normal, and ultrarapid metabolizers. The PBPK model met the acceptance criteria for all verification simulations (> 80% of model-predicted PK parameters within 2-fold of those observed clinically). A weak induction effect was predicted when mavacamten was administered with a strong CYP3A4 inducer in poor metabolizers. Moderate reductions in mavacamten exposure were predicted with a strong CYP2C19/CYP3A4 inducer in all CYP2C19 phenotypes. Except for the effect of strong CYP2C19 inhibitors on ultrarapid metabolizers, steady-state area under plasma concentration-time curve and maximum plasma concentration values were weakly affected (< 2-fold) or not affected (< 1.25-fold), regardless of CYP2C19 phenotype. In conclusion, a fit-for-purpose PBPK model was developed and verified, which accurately predicted the available clinical data and was used to simulate the potential impact of CYP induction and inhibition on mavacamten PKs, stratified by CYP2C19 phenotype.

3D printing combined with biopredictive dissolution and PBPK/PD modeling optimization and personalization of pharmacotherapy: Are we there yet?

Precision medicine requires selecting the appropriate dosage regimen for a patient using the right drug, at the right time. Model-Informed Precision Dosing (MIPD) is a concept suggesting utilization of model-based prediction methods for optimizing the treatment benefit-harm balance, based on individual characteristics of the patient, disease, treatment method, and other factors. Here, we discuss a theoretical workflow comprising several elements, beginning from the physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models, through 3D printed tablets with the model proposed dose, information range and flow, and the patient themselves. We also describe each of these elements, and the connection between them, highlighting challenges and potential obstacles.

Understanding Statin-Roxadustat Drug-Drug-Disease Interaction Using Physiologically-Based Pharmacokinetic Modeling

A different drug-drug interaction (DDI) scenario may exist in patients with chronic kidney disease (CKD) compared with healthy volunteers (HVs), depending on the interplay between drug-drug and disease (drug-drug-disease interaction (DDDI)). Physiologically-based pharmacokinetic (PBPK) modeling, in lieu of a clinical trial, is a promising tool for evaluating these complex DDDIs in patients. However, the prediction confidence of PBPK modeling in the severe CKD population is still low when nonrenal pathways are involved. More mechanistic virtual disease population and robust validation cases are needed. To this end, we aimed to: (i) understand the implications of severe CKD on statins (atorvastatin, simvastatin, and rosuvastatin) pharmacokinetics (PK) and DDI; and (ii) predict untested clinical scenarios of statin-roxadustat DDI risks in patients to guide suitable dose regimens. A novel virtual severe CKD population was developed incorporating the disease effect on both renal and nonrenal pathways. Drug and disease PBPK models underwent a four-way validation. The verified PBPK models successfully predicted the altered PKs in patients for substrates and inhibitors and recovered the observed statin-rifampicin DDIs in patients and the statin-roxadustat DDIs in HVs within 1.25- and 2-fold error. Further sensitivity analysis revealed that the severe CKD effect on statins PK is mainly mediated by hepatic BCRP for rosuvastatin and OATP1B1/3 for atorvastatin. The magnitude of statin-roxadustat DDI in patients with severe CKD was predicted to be similar to that in HVs. PBPK-guided suitable dose regimens were identified to minimize the risk of side effects or therapeutic failure of statins when co-administered with roxadustat.

Use of Developmental Midazolam and 1-Hydroxymidazolam Data with Pediatric Physiologically Based Modeling to Assess Cytochrome P450 3A4 and Uridine Diphosphate Glucuronosyl Transferase 2B4 Ontogeny In Vivo

Pediatric physiologically based pharmacokinetics modeling in drug development has grown in the past decade but uncertainty remains regarding ontogeny of some drug metabolizing enzymes. In this study, a midazolam and 1-hydroxymidazolam physiologically based pharmacokinetic model (PBPK) model was developed and used to define the ontogeny for hepatic cytochrome P450 (CYP) 3A4 and uridine diphosphate glucuronosyl transferase (UGT) 2B4. Data for model development and pharmacokinetic studies on intravenous midazolam in adults and pediatrics were collated from the literature. The PBPK model was verified in the adult population and then used to compare the performance of two ontogeny profiles for CYP3A4 in terms of parent drug elimination in pediatrics. Four studies also published data on the 1-hydroxymidazolam, and this was used to evaluate the known ontogeny for UGT2B4.For midazolam elimination, the Upreti CYP3A4 ontogeny performed better than Salem; mean error (bias) and mean squared error (precision) were 0.14 and 0.064 compared with 0.69 and 1.21, respectively. For 1-hydroxymidazolam elimination, the Simcyp default ontogeny of UGT2B4 appeared to perform best for studies covering the age range 0.5 to 15.7 years, while for a study in younger ages 0 to 1 years it was the Badee UGT2B4 ontogeny. In preterm neonates, overall expression of UGT appeared to be around 10% of that in adults.Identifying the optimal model of CYP3A4 ontogeny is important for the regulatory use of PBPK. The results for midazolam are conclusive but research about other CYP3A4 metabolized compounds will underpin generalizability of the CYP3A4 ontogeny. UGT2B4 ontogeny is less certain, but this study indicates the most likely scenarios. SIGNIFICANCE STATEMENT: A PBPK model for midazolam and 1-hydroxymidazolam was developed to test various ontogeny scenarios for CYP3A4 and UGT2B4. The CYP3A4 ontogeny of Upreti resulted in more accurate prediction of midazolam CL across nine clinical studies, age range birth to 18 years. 1-Hydroxy midazolam was used as a marker of UGT. The Simcyp default 'no ontogeny' profiles for UGT2B4 performed the best; however, for <1 year of age, there was some evidence of overactivity of this enzyme compared to adults.

Application of Modelling and Simulation Approaches to Predict Pharmacokinetics of Therapeutic Monoclonal Antibodies in Pediatric Population

Ethical regulations and limited paediatric participants are key challenges that contribute to a median delay of 6 years in paediatric mAb approval. To overcome these barriers, modelling and simulation methodologies have been adopted to design optimized paediatric clinical studies and reduce patient burden. The classical modelling approach in paediatric pharmacokinetic studies for regulatory submissions is to apply body weight-based or body surface area-based allometric scaling to adult PK parameters derived from a popPK model to inform the paediatric dosing regimen. However, this approach is limited in its ability to account for the rapidly changing physiology in paediatrics, especially in younger infants. To overcome this limitation, PBPK modelling, which accounts for the ontogeny of key physiological processes in paediatrics, is emerging as an alternative modelling strategy. While only a few mAb PBPK models have been published, PBPK modelling shows great promise demonstrating a similar prediction accuracy to popPK modelling in an Infliximab paediatric case study. To facilitate future PBPK studies, this review consolidated comprehensive data on the ontogeny of key physiological processes in paediatric mAb disposition. To conclude, this review discussed different use-cases for pop-PK and PBPK modelling and how they can complement each other to increase confidence in pharmacokinetic predictions.

Differential Preincubation Effects of Nicardipine on OATP1B1- and OATP1B3-Mediated Transport in the Presence and Absence of Protein: Implications in Assessing OATP1B1- and OATP1B3-Mediated Drug-Drug Interactions

Impaired transport activity of hepatic OATP1B1 and OATP1B3 due to drug-drug interactions (DDIs) often leads to increased systemic exposure to substrate drugs (e.g., lipid-lowering statins). Since dyslipidemia and hypertension frequently coexist, statins are often concurrently used with antihypertensives, including calcium channel blockers (CCBs). OATP1B1/1B3-related DDIs in humans have been reported for several CCBs. To date, the OATP1B1/1B3-mediated DDI potential of CCB nicardipine has not been assessed. The current study was designed to assess the OATP1B1- and OATP1B3-mediated DDI potential of nicardipine using the R-value model, following the US-FDA guidance. IC50 values of nicardipine against OATP1B1 and OATP1B3 were determined in transporter-overexpressing human embryonic kidney 293 cells using [3H]-estradiol 17β-D-glucuronide and [3H]-cholecystokinin-8 as substrates, respectively, with or without nicardipine-preincubation in protein-free Hanks' Balanced Salt Solution (HBSS) or in fetal bovine serum (FBS)-containing culture medium. Preincubation with nicardipine for 30 min in protein-free HBSS buffer produced lower IC50 and higher R-values for both OATP1B1 and OATP1B3 compared to in FBS-containing medium, yielding IC50 values of 0.98 and 1.63 µM and R-values of 1.4 and 1.3 for OATP1B1 and OATP1B3, respectively. The R-values were higher than the US-FDA cut-off value of 1.1, supporting that nicardipine has the potential to cause OATP1B1/3-mediated DDIs. Current studies provide insight into the consideration of optimal preincubation conditions when assessing the OATP1B1/3-mediated DDIs in vitro.

Precision antiplatelet therapy

A State of the Art lecture titled "Personalizing Antiplatelet Therapy Based on Platelet Turnover and Metabolic Phenotype" was presented by Bianca Rocca at the International Society on Thrombosis and Haemostasis (ISTH) Congress in 2022. Increased variability in drug response may be associated with serious, mechanism-based and off-target side effects, especially in the case of drugs that do not routinely undergo therapeutic drug monitoring, such as antiplatelet drugs or direct oral anticoagulants. Precision pharmacology can be defined as the identification of a drug regimen that maximizes the benefit/risk balance at the level of an individual patient. Key tools for identifying relevant sources of variability and developing precision drug dosing are represented by genetic, biochemical, and pharmacological biomarkers recognized as a valid surrogate or strong predictor of major clinical complications. Pharmacodynamic, pharmacokinetic, and/or disease-related biomarkers are central to identifying the right population to be targeted, characterizing the sources of variability in drug response, guiding precision treatments that maximize benefits and minimize risks, and designing precision dosing trials. Another valuable tool for guiding precision pharmacology is represented by in silico pharmacokinetic/pharmacodynamic models and simulations instructed by real-world data of validated biomarkers. This review critically analyzes the tools for precision dosing and exemplifies conditions in which precision dosing can considerably optimize the efficacy and safety of antiplatelet drugs, namely aspirin and P2Y12 receptor blockers, used alone and in combination. Finally, we summarize relevant new data on this topic presented during the 2022 ISTH Congress.

Understanding the Risk of Drug Interactions Between Ritonavir-Containing COVID-19 Therapies and Small-Molecule Kinase Inhibitors in Patients With Cancer

PURPOSE

The introduction of COVID-19 therapies containing ritonavir has markedly expanded the scope of use for this medicine. As a strong cytochrome P450 3A4 inhibitor, the use of ritonavir is associated with a high drug interaction risk. There are currently no data to inform clinician regarding the likely magnitude and duration of interaction between ritonavir-containing COVID-19 therapies and small-molecule kinase inhibitors (KIs) in patients with cancer.

METHODS

Physiologically based pharmacokinetic modeling was used to conduct virtual clinical trials with a parallel group study design in the presence and absence of ritonavir (100 mg twice daily for 5 days). The magnitude and time course of changes in KI exposure when coadministered with ritonavir was evaluated as the primary outcome.

RESULTS

Dosing of ritonavir resulted in a > 2-fold increase in steady-state area under the plasma concentration-time curve and maximal concentration for six of the 10 KIs. When the KI was coadministered with ritonavir, dose reductions to between 10% and 75% of the original dose were required to achieve an area under the plasma concentration-time curve within 1.25-fold of the value in the absence of ritonavir.

CONCLUSION

To our knowledge, this study provides the first data to assist clinicians' understanding of the drug interaction risk associated with administering ritonavir-containing COVID-19 therapies to patients with cancer who are currently being treated with KIs. These data may support clinicians to make more informed dosing decisions for patients with cancer undergoing treatment with KIs who require treatment with ritonavir-containing COVID-19 antiviral therapies.

Use of physiological based pharmacokinetic modeling for cross-species prediction of pharmacokinetic and tissue distribution profiles of a novel niclosamide prodrug

Introduction: Niclosamide (Nc) is an FDA-approved anthelmintic drug that was recently identified in a drug repurposing screening to possess antiviral activity against SARS-CoV-2. However, due to the low solubility and permeability of Nc, its in vivo efficacy was limited by its poor oral absorption. Method: The current study evaluated a novel prodrug of Nc (PDN; NCATS-SM4705) in improving in vivo exposure of Nc and predicted pharmacokinetic profiles of PDN and Nc across different species. ADME properties of the prodrug were determined in humans, hamsters, and mice, while the pharmacokinetics (PK) of PDN were obtained in mice and hamsters. Concentrations of PDN and Nc in plasma and tissue homogenates were measured by UPLC-MS/MS. A physiologically based pharmacokinetic (PBPK) model was developed based on physicochemical properties, pharmacokinetic and tissue distribution data in mice, validated by the PK profiles in hamsters and applied to predict pharmacokinetic profiles in humans. Results: Following intravenous and oral administration of PDN in mice, the total plasma clearance (CL_p) and volume of distribution at steady-state (Vd_ss) were 0.061-0.063 L/h and 0.28-0.31 L, respectively. PDN was converted to Nc in both liver and blood, improving the systemic exposure of Nc in mice and hamsters after oral administration. The PBPK model developed for PDN and in vivo formed Nc could adequately simulate plasma and tissue concentration-time profiles in mice and plasma profiles in hamsters. The predicted human CL_p/F and Vd_ss/F after an oral dose were 2.1 L/h/kg and 15 L/kg for the prodrug respectively. The predicted Nc concentrations in human plasma and lung suggest that a TID dose of 300 mg PDN would provide Nc lung concentrations at 8- to 60-fold higher than in vitro IC₅₀ against SARS-CoV-2 reported in cell assays. Conclusion: In conclusion, the novel prodrug PDN can be efficiently converted to Nc in vivo and improves the systemic exposure of Nc in mice after oral administration. The developed PBPK model adequately depicts the mouse and hamster pharmacokinetic and tissue distribution profiles and highlights its potential application in the prediction of human pharmacokinetic profiles.

Utilization of Physiologically Based Pharmacokinetic Modeling in Pharmacokinetic Study of Natural Medicine: An Overview

Natural medicine has been widely used for clinical treatment and health care in many countries and regions. Additionally, extracting active ingredients from traditional Chinese medicine and other natural plants, defining their chemical structure and pharmacological effects, and screening potential druggable candidates are also uprising directions in new drug research and development. Physiologically based pharmacokinetic (PBPK) modeling is a mathematical modeling technique that simulates the absorption, distribution, metabolism, and elimination of drugs in various tissues and organs in vivo based on physiological and anatomical characteristics and physicochemical properties. PBPK modeling in drug research and development has gradually been recognized by regulatory authorities in recent years, including the U.S. Food and Drug Administration. This review summarizes the general situation and shortcomings of the current research on the pharmacokinetics of natural medicine and introduces the concept and the advantages of the PBPK model in the study of pharmacokinetics of natural medicine. Finally, the pharmacokinetic studies of natural medicine using the PBPK models are summed up, followed by discussions on the applications of PBPK modeling to the enzyme-mediated pharmacokinetic changes, special populations, new drug research and development, and new indication adding for natural medicine. This paper aims to provide a novel strategy for the preclinical research and clinical use of natural medicine.

Unravelling sex-specific BPA toxicokinetics in children using a pediatric PBPK model

Bisphenol A (BPA) is a widely known endocrine disruptor (ED) found in many children's products such as toys, feeding utensils, and teething rings. Recent epidemiology association studies have shown postnatal BPA exposure resulted in developing various diseases such as diabetes, obesity, and neurodegeneration, etc., later in their lives. However, little is known about its sex-specific metabolism and consequently internal exposure. The aim of this study was to develop a sex-specific pediatric physiologically based pharmacokinetic model (PBPK) for BPA to compare their toxicokinetic differences. First, the published adult PBPK model was re-validated, and then this model was extended by interpolation to incorporate pediatric sex specific physiological and biochemical parameters. We used both the classical body weight and ontogeny-based scaling approach to interpolate the metabolic process. Then, the pharmacokinetic attributes of the models using the two-scaling approach mentioned above were compared with adult model. Further, a sex-specific PBPK model with an ontogeny scaling approach was preferred to evaluate the pharmacokinetic differences. Moreover, this model was used to reconstruct the BPA exposure from two cohorts (Helix and PBAT Cohort) from 7 EU countries. The half-life of BPA was found to be almost the same in boys and girls at the same exposure levels. Our model estimated BPA children's exposure to be about 1500 times higher than the tolerable daily intake (TDI) recently set by European Food Safety Authority (EFSA) i.e., 0.04 ng/kg BW/day. The model demonstrated feasibility of extending the adult PBPK to sex-specific pediatric, thus investigate a gender-specific health risk assessment.

Predicting the correct dose in children: Role of computational Pediatric Physiological-based pharmacokinetics modeling tools

The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically-based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P-PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P-PBPK modeling. We summarized the theories and applications of this software and discussed the application trends and future perspectives in the area. The modeling software's extensive use will undoubtedly make it easier to predict dose prediction for young patients.

A Physiologically Based Pharmacokinetic Model to Predict the Impact of Metabolic Changes Associated with Metabolic Associated Fatty Liver Disease on Drug Exposure

Metabolic associated fatty liver disease (MAFLD) is the most common chronic liver disease, with an estimated prevalence of between 20 and 30% worldwide. Observational data supported by in vitro and pre-clinical animal models of MAFLD suggest meaningful differences in drug disposition in MAFLD patients. This study aimed to build a physiologically based pharmacokinetic (PBPK) model reflecting observed changes in physiological and molecular parameters relevant to drug disposition that are associated with MAFLD. A comprehensive literature review and meta-analysis was conducted to identify all studies describing in vivo physiological changes along with in vitro and pre-clinical model changes in CYP 1A2, 2C9, 2C19, 2D6 and 3A4 protein abundance associated with MAFLD. A MAFLD population profile was constructed in Simcyp (version 19.1) by adapting demographic and physiological covariates from the Sim-Healthy population profile based on a meta-analysis of observed data from the published literature. Simulations demonstrated that single dose and steady state area under the plasma concentration time curve (AUC) for caffeine, clozapine, omeprazole, metoprolol, dextromethorphan and midazolam, but not s-warfarin or rosiglitazone, were increased by >20% in the MAFLD population compared to the healthy control population. These findings indicate that MAFLD patients are likely to be experience meaningfully higher exposure to drugs that are primarily metabolized by CYP 1A2, 2C19, 2D6 and 3A4, but not CYP2C9. Closer monitoring of MAFLD patients using drugs primarily cleared by CYP 1A2, 2C19 and 3A4 is warranted as reduced metabolic activity and increased drug exposure are likely to result in an increased incidence of toxicity in this population.

Innovative approaches and recent advances in the study of ontogeny of drug metabolism and transport

The disposition of a drug is driven by various processes, such as drug metabolism, drug transport, glomerular filtration and body composition. These processes are subject to developmental changes reflecting growth and maturation along the paediatric continuum. However, knowledge gaps exist on these changes and their clinical impact. Filling these gaps may aid better prediction of drug disposition and creation of age-appropriate dosing guidelines. We present innovative approaches to study these developmental changes in relation to drug metabolism and transport. First, analytical methods such as including liquid chromatography-mass spectrometry for proteomic analyses allow quantitation of the expressions of a wide variety of proteins, e.g. membrane transporters, in a small piece of organ tissue. The latter is specifically important for paediatric research, where tissues are scarcely available. Second, innovative study designs using radioactive labelled microtracers allowed study-without risk for the child-of the oral bioavailability of compounds used as markers for certain drug metabolism pathways. Third, the use of modelling and simulation to support dosing recommendations for children is supported by both the European Medicines Agency and the US Food and Drug Administration. This may even do away with the need for a paediatric trial. Physiologically based pharmacokinetics models, which include age-specific physiological information are, therefore, increasingly being used, not only to aid paediatric drug development but also to improve existing drug therapies.

Quality Control Dissolution Data Is Biopredictive for a Modified Release Ropinirole Formulation: Virtual Experiment with the Use of Re-Developed and Verified PBPK Model

Physiologically based pharmacokinetic and absorption modeling are being used by industry and regulatory bodies to address various scientifically challenging questions. While there is high confidence in the prediction of exposure for the BCS class I drugs administered as immediate-release formulations, in the case of prolonged-release formulations, special attention should be given to the input dissolution data. Our goal was to develop and verify a PBPK model for a BCS class I compound, ropinirole, and check the biopredictiveness of the dissolution data for the prolonged-release formulation administered by Parkinson’s patients. The model was built based on quality control dissolution data reported in the certificates of analysis and verified with the use of data derived from five clinical trial reports. The simulated pharmacokinetic parameters being within a two-fold range of the observed values confirmed acceptable model performance, in vivo relevance of the in vitro dissolution profiles, and indirectly indicated ropinirole stable release from the formulation in the patients’ gastro-intestinal tract. Ropinirole PBPK model will be used for exploring potential clinical scenarios while developing a new formulation.

Determining the Effects of Chronic Kidney Disease on Organic Anion Transporter1/3 Activity Through Physiologically Based Pharmacokinetic Modeling

BACKGROUND AND OBJECTIVE

The renal excretion of drugs via organic anion transporters 1 and 3 (OAT1/3) is significantly decreased in patients with renal impairment. This study uses physiologically based pharmacokinetic models to quantify the reduction in OAT1/3-mediated secretion of drugs throughout varying stages of chronic kidney disease.

METHODS

Physiologically based pharmacokinetic models were constructed for four OAT1/3 substrates in healthy individuals: acyclovir, meropenem, furosemide, and ciprofloxacin. Observed data from drug-drug interaction studies with probenecid, a potent OAT1/3 inhibitor, were used to parameterize the contribution of OAT1/3 to the renal elimination of each drug. The models were then translated to patients with chronic kidney disease by accounting for changes in glomerular filtration rate, kidney volume, renal blood flow, plasma protein binding, and hematocrit. Additionally, a relationship was derived between the estimated glomerular filtration rate and the reduction in OAT1/3-mediated secretion of drugs based on the renal extraction ratios of ƿ-aminohippuric acid in patients with varying degrees of renal impairment. The relationship was evaluated in silico by evaluating the predictive performance of each final model in describing the pharmacokinetics (PK) of drugs across stages of chronic kidney disease.

RESULTS

OAT1/3-mediated renal excretion of drugs was found to be decreased by 27-49%, 50-68%, and 70-96% in stage 3, stage 4, and stage 5 of chronic kidney disease, respectively. In support of the parameterization, physiologically based pharmacokinetic models of four OAT1/3 substrates were able to adequately characterize the PK in patients with different degrees of renal impairment. Total exposure after intravenous administration was predicted within a 1.5-fold error and 85% of the observed data points fell within a 1.5-fold prediction error. The models modestly under-predicted plasma concentrations in patients with end-stage renal disease undergoing intermittent hemodialysis. However, results should be interpreted with caution because of the limited number of molecules analyzed and the sparse sampling in observed chronic kidney disease pharmacokinetic studies.

CONCLUSIONS

A quantitative understanding of the reduction in OAT1/3-mediated excretion of drugs in differing stages of renal impairment will contribute to better predictive accuracy for physiologically based pharmacokinetic models in drug development, assisting with clinical trial planning and potentially sparing this population from unnecessary toxic exposures.

Recent advances in the translation of drug metabolism and pharmacokinetics science for drug discovery and development

Drug metabolism and pharmacokinetics (DMPK) is an important branch of pharmaceutical sciences. The nature of ADME (absorption, distribution, metabolism, excretion) and PK (pharmacokinetics) inquiries during drug discovery and development has evolved in recent years from being largely descriptive to seeking a more quantitative and mechanistic understanding of the fate of drug candidates in biological systems. Tremendous progress has been made in the past decade, not only in the characterization of physiochemical properties of drugs that influence their ADME, target organ exposure, and toxicity, but also in the identification of design principles that can minimize drug-drug interaction (DDI) potentials and reduce the attritions. The importance of membrane transporters in drug disposition, efficacy, and safety, as well as the interplay with metabolic processes, has been increasingly recognized. Dramatic increases in investments on new modalities beyond traditional small and large molecule drugs, such as peptides, oligonucleotides, and antibody-drug conjugates, necessitated further innovations in bioanalytical and experimental tools for the characterization of their ADME properties. In this review, we highlight some of the most notable advances in the last decade, and provide future perspectives on potential major breakthroughs and innovations in the translation of DMPK science in various stages of drug discovery and development.

Applications, Challenges, and Outlook for PBPK Modeling and Simulation: A Regulatory, Industrial and Academic Perspective

Several regulatory guidances on the use of physiologically based pharmacokinetic (PBPK) analyses and physiologically based biopharmaceutics model(s) (PBBM(s)) have been issued. Workshops are routinely held, demonstrating substantial interest in applying these modeling approaches to address scientific questions in drug development. PBPK models and PBBMs have remarkably contributed to model-informed drug development (MIDD) such as anticipating clinical PK outcomes affected by extrinsic and intrinsic factors in general and specific populations. In this review, we proposed practical considerations for a "base" PBPK model construction and development, summarized current status, challenges including model validation and gaps in system models, and future perspectives in PBPK evaluation to assess a) drug metabolizing enzyme(s)- or drug transporter(s)- mediated drug-drug interactions b) dosing regimen prediction, sampling timepoint selection and dose validation in pediatric patients from newborns to adolescents, c) drug exposure in patients with renal and/or and hepatic organ impairment, d) maternal-fetal drug disposition during pregnancy, and e) pH-mediated drug-drug interactions in patients treated with proton pump inhibitors/acid-reducing agents (PPIs/ARAs) intended for gastric protection. Since PBPK can simulate outcomes in clinical studies with enrollment challenges or ethical issues, the impact of PBPK models on waivers and how to strengthen study waiver is discussed.

An IQ Consortium Perspective on Connecting Dissolution Methods to In Vivo Performance: Analysis of an Industrial Database and Case Studies to Propose a Workflow

Assessment of bioperformance to inform formulation selection and development decisions is an important aspect of drug development. There is high demand in the pharmaceutical industry to develop an efficient and streamlined approach for better understanding and predicting drug product performance to support acceleration of clinical timelines. This manuscript presents an effort from the IQ Formulation Bioperformance Prediction Working Group composed of members from 12 pharmaceutical companies under the IQ Consortium to develop a database around the topic of formulation bioperformance prediction and report findings from the database analysis. Six case studies described in the manuscript demonstrate how bioperformance models were used to predict in vivo performance and to provide guidance addressing questions encountered during oral solid dosage form development. The case studies also described findings of a correlation between in vitro dissolution and in vivo performance and how dissolution data can be incorporated into physiologically based biopharmaceutical modeling. Finally, a workflow for how in vitro dissolution data can be utilized to predict clinical bioperformance of oral solid dosage forms is proposed.

Probabilistic risk assessment - the keystone for the future of toxicology

Safety sciences must cope with uncertainty of models and results as well as information gaps. Acknowledging this uncer-tainty necessitates embracing probabilities and accepting the remaining risk. Every toxicological tool delivers only probable results. Traditionally, this is taken into account by using uncertainty / assessment factors and worst-case / precautionary approaches and thresholds. Probabilistic methods and Bayesian approaches seek to characterize these uncertainties and promise to support better risk assessment and, thereby, improve risk management decisions. Actual assessments of uncertainty can be more realistic than worst-case scenarios and may allow less conservative safety margins. Most importantly, as soon as we agree on uncertainty, this defines room for improvement and allows a transition from traditional to new approach methods as an engineering exercise. The objective nature of these mathematical tools allows to assign each methodology its fair place in evidence integration, whether in the context of risk assessment, sys-tematic reviews, or in the definition of an integrated testing strategy (ITS) / defined approach (DA) / integrated approach to testing and assessment (IATA). This article gives an overview of methods for probabilistic risk assessment and their application for exposure assessment, physiologically-based kinetic modelling, probability of hazard assessment (based on quantitative and read-across based structure-activity relationships, and mechanistic alerts from in vitro studies), indi-vidual susceptibility assessment, and evidence integration. Additional aspects are opportunities for uncertainty analysis of adverse outcome pathways and their relation to thresholds of toxicological concern. In conclusion, probabilistic risk assessment will be key for constructing a new toxicology paradigm - probably!

Integration of advanced methods and models to study drug absorption and related processes: An UNGAP perspective

This collection of contributions from the European Network on Understanding Gastrointestinal Absorption-related Processes (UNGAP) community assembly aims to provide information on some of the current and newer methods employed to study the behaviour of medicines. It is the product of interactions in the immediate pre-Covid period when UNGAP members were able to meet and set up workshops and to discuss progress across the disciplines. UNGAP activities are divided into work packages that cover special treatment populations, absorption processes in different regions of the gut, the development of advanced formulations and the integration of food and pharmaceutical scientists in the food-drug interface. This involves both new and established technical approaches in which we have attempted to define best practice and highlight areas where further research is needed. Over the last months we have been able to reflect on some of the key innovative approaches which we were tasked with mapping, including theoretical, in silico, in vitro, in vivo and ex vivo, preclinical and clinical approaches. This is the product of some of us in a snapshot of where UNGAP has travelled and what aspects of innovative technologies are important. It is not a comprehensive review of all methods used in research to study drug dissolution and absorption, but provides an ample panorama of current and advanced methods generally and potentially useful in this area. This collection starts from a consideration of advances in a priori approaches: an understanding of the molecular properties of the compound to predict biological characteristics relevant to absorption. The next four sections discuss a major activity in the UNGAP initiative, the pursuit of more representative conditions to study lumenal dissolution of drug formulations developed independently by academic teams. They are important because they illustrate examples of in vitro simulation systems that have begun to provide a useful understanding of formulation behaviour in the upper GI tract for industry. The Leuven team highlights the importance of the physiology of the digestive tract, as they describe the relevance of gastric and intestinal fluids on the behaviour of drugs along the tract. This provides the introduction to microdosing as an early tool to study drug disposition. Microdosing in oncology is starting to use gamma-emitting tracers, which provides a link through SPECT to the next section on nuclear medicine. The last two papers link the modelling approaches used by the pharmaceutical industry, in silico to Pop-PK linking to Darwich and Aarons, who provide discussion on pharmacometric modelling, completing the loop of molecule to man.

Physiologically Based Pharmacokinetic Modeling of Meropenem in Preterm and Term Infants

BACKGROUND

Meropenem is a broad-spectrum carbapenem antibiotic approved by the US Food and Drug Administration for use in pediatric patients, including treating complicated intra-abdominal infections in infants < 3 months of age. The impact of maturation in glomerular filtration rate and tubular secretion by renal transporters on meropenem pharmacokinetics, and the effect on meropenem dosing, remains unknown. We applied physiologically based pharmacokinetic (PBPK) modeling to characterize the disposition of meropenem in preterm and term infants.

METHODS

An adult meropenem PBPK model was developed in PK-Sim® (Version 8) and scaled to infants accounting for renal transporter ontogeny and glomerular filtration rate maturation. The PBPK model was evaluated using 645 plasma concentrations from 181 infants (gestational age 23-40 weeks; postnatal age 1-95 days). The PBPK model-based simulations were performed to evaluate meropenem dosing in the product label for infants < 3 months of age treated for complicated intra-abdominal infections.

RESULTS

Our model predicted plasma concentrations in infants in agreement with the observed data (average fold error of 0.90). The PBPK model-predicted clearance in a virtual infant population was successfully able to capture the post hoc estimated clearance of meropenem in this population, estimated by a previously published model. For 90% of virtual infants, a 4-mg/L target plasma concentration was achieved for > 50% of the dosing interval following product label-recommended dosing.

CONCLUSIONS

Our PBPK model supports the meropenem dosing regimens recommended in the product label for infants <3 months of age.

Physiologically based pharmacokinetic/pharmacodynamic modeling to evaluate the absorption of midazolam rectal gel

OBJECTIVE

We aimed to 1) develop physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models of a novel midazolam rectal gel in healthy adults, 2) assess the contribution of different physiologically relevant factors in rectal absorption, and 3) to provide supports for future clinical studies of midazolam rectal gel.

METHODS

We developed the rectal PBPK model after built the intravenous and the oral PBPK model. Then, the physiological progress of rectal route was described in terms of the drug release, the rectal absorption and the particle first-pass elimination. Next, the validated PBPK model was combined with the sigmoid E_max PD model. This PBPK/PD model was used to identify the dose range and the critical parameters to ensure safety sedation.

RESULTS

Based on the simulations, the recommended maximum dose for adults' sedation was 15 mg. And the retention time of midazolam rectal gel should be longer than 3 h to reach over 80% pharmacokinetics and pharmacodynamics effects.

CONCLUSION

We successfully developed a PBPK/PD model for the midazolam rectal gel, which accurately described the PK/PD behavior in healthy adults and indicated the transit time of rectum was the most sensitive parameter for absorption. This PBPK/PD model would be expected to support the future clinical studies and pediatric application.

PBPK Modeling and Simulation of Antibiotics Amikacin, Gentamicin, Tobramycin, and Vancomycin Used in Hospital Practice

The importance of closely observing patients receiving antibiotic therapy, performing therapeutic drug monitoring (TDM), and regularly adjusting dosing regimens has been extensively demonstrated. Additionally, antibiotic resistance is a contemporary concerningly dangerous issue. Optimizing the use of antibiotics is crucial to ensure treatment efficacy and prevent toxicity caused by overdosing, as well as to combat the prevalence and wide spread of resistant strains. Some antibiotics have been selected and reserved for the treatment of severe infections, including amikacin, gentamicin, tobramycin, and vancomycin. Critically ill patients often require long treatments, hospitalization, and require particular attention regarding TDM and dosing adjustments. As these antibiotics are eliminated by the kidneys, critical deterioration of renal function and toxic effects must be prevented. In this work, clinical data from a Portuguese cohort of 82 inpatients was analyzed and physiologically based pharmacokinetic (PBPK) modeling and simulation was used to study the influence of different therapeutic regimens and parameters as biological sex, body weight, and renal function on the biodistribution and pharmacokinetic (PK) profile of these four antibiotics. Renal function demonstrated the greatest impact on plasma concentration of these antibiotics, and vancomycin had the most considerable accumulation in plasma over time, particularly in patients with impaired renal function. Thus, through a PBPK study, it is possible to understand which pharmacokinetic parameters will have the greatest variation in a given population receiving antibiotic administrations in hospital context.