Predicting Human Dermal Drug Concentrations Using PBPK Modeling and Simulation: Clobetasol Propionate Case Study.

Quantitative in silico tools may be leveraged to mechanistically predict the dermato-pharmacokinetics of compounds delivered from topical and transdermal formulations by integrating systems of rate equations that describe permeation through the formulation and layers of skin and pilo-sebaceous unit, and exchange with systemic circulation via local blood flow. Delivery of clobetasol-17 propionate (CP) from DermovateTM cream was simulated using the Transdermal Compartmental Absorption & Transit (TCATTM) Model in GastroPlus®. The cream was treated as an oil-in-water emulsion, with model input parameters estimated from publicly available information and quantitative structure-permeation relationships. From the ranges of values available for model input parameters, a set of parameters was selected by comparing model outputs to CP dermis concentration-time profiles measured by dermal open-flow microperfusion (Bodenlenz et al. Pharm Res. 33(9):2229-38, 2016). Predictions of unbound dermis CP concentrations were reasonably accurate with respect to time and skin depth. Parameter sensitivity analyses revealed considerable dependence of dermis CP concentration profiles on drug solubility in the emulsion, relatively less dependence on dispersed phase volume fraction and CP effective diffusivity in the continuous phase of the emulsion, and negligible dependence on dispersed phase droplet size. Effects of evaporative water loss from the cream and corticosteroid-induced vasoconstriction were also assessed. This work illustrates the applicability of computational modeling to predict sensitivity of dermato-pharmacokinetics to changes in thermodynamic and transport properties of a compound in a topical formulation, particularly in relation to rate-limiting steps in skin permeation. Where these properties can be related to formulation composition and processing, such a computational approach may support the design of topically applied formulations.

Clinical Ocular Exposure Extrapolation for Ophthalmic Solutions Using PBPK Modeling and Simulation.

BACKGROUND: The development of generic ophthalmic drug products is challenging due to the complexity of the ocular system, and a lack of sensitive testing to evaluate the interplay of physiology with ophthalmic formulations. While measurements of drug concentration at the site of action in humans are typically sparse, these measurements are more easily obtained in rabbits. The purpose of this study is to demonstrate the utility of an ocular physiologically based pharmacokinetic (PBPK) model for translation of ocular exposure from rabbit to human. METHOD: The Ocular Compartmental Absorption and Transit (OCAT™) model within GastroPlus® v9.8.2 was used to build PBPK models for levofloxacin (Lev), moxifloxacin (Mox), and gatifloxacin (Gat) ophthalmic solutions. in the rabbit eye. The models were subsequently used to predict Lev, Mox, and Gat exposure after ocular solution administrations in humans. Drug-specific parameters were used as fitted and validated in the rabbit OCAT model. The physiological parameters were scaled to match human ocular physiology. RESULTS: OCAT model simulations for rabbit well described the observed concentrations in the eye compartments following Lev, Mox, and Gat solution administrations of different doses and various administration schedules. The clinical ocular exposure following ocular administration of Lev, Mox, and Gat solutions at different doses and various administration schedules was well predicted. CONCLUSION: Even though additional case studies for different types of active pharmaceutical ingredients (APIs) and formulations will be needed, the current study represents an important step in the validation of the extrapolation method to predict human ocular exposure for ophthalmic drug products using PBPK models.

Development of PBPK model for intra-articular injection in human: methotrexate solution and rheumatoid arthritis case study.

A physiologically based model describing the dissolution, diffusion, and transfer of drug from the intra-articular (IA) space to the plasma, was developed for GastroPlus® v9.8. The model is subdivided into compartments representing the synovial fluid, synovium, and cartilage. The synovium is broken up into two sublayers. The intimal layer acts as a diffusion barrier between the synovial fluid and the subintimal layer. The subintimal layer of the synovium has fenestrated capillaries that allow the free drug to be transported into systemic circulation. The articular cartilage is broken up into 10 diffusion sublayers as it is much thicker than the synovium. The cartilage acts as a depot tissue for the drug to diffuse into from synovial fluid. At later times, the drug will diffuse from the cartilage back into synovial fluid once a portion of the dose enters systemic circulation. In this study, a listing of all relevant details and equations for the model is presented. Methotrexate was chosen as a case study to show the application and utility of the model, based on the availability of intravenous (IV), oral (PO) and IA administration data in patients presenting rheumatoid arthritis (RA) symptoms. Systemic disposition of methotrexate in RA patients was described by compartmental pharmacokinetic (PK) model with PK parameters extracted using the PKPlus™ module in GastroPlus®. The systemic PK parameters were validated by simulating PO administration of methotrexate before being used for simulation of IA administration. For methotrexate, the concentrations of drug in the synovial fluid and plasma were well described after adjustments of physiological parameters to account for RA disease state, and with certain assumptions about binding and diffusion. The results indicate that the model can correctly describe PK profiles resulting from administration in the IA space, however, additional cases studies will be required to evaluate ability of the model to scale between species and/or doses.

Ocular Physiologically Based Pharmacokinetic Modeling for Ointment Formulations.

PURPOSE: The purpose of this study is to show how the Ocular Compartmental Absorption & Transit (OCAT™) model in GastroPlus® can be used to characterize ocular drug pharmacokinetic performance in rabbits for ointment formulations. METHODS: A newly OCAT™ model developed for fluorometholone, as well as a previously verified model for dexamethasone, were used to characterize the aqueous humor (AH) concentration following the administration of multiple ointment formulations to rabbit. The model uses the following parameters: application surface area (SA), a fitted application time, and the fitted Higuchi release constant to characterize the rate of passage of the active pharmaceutical ingredient from the ointment formulations into the tears in vivo. RESULTS: Parameter sensitivity analysis was performed to understand the impact of ointment formulation changes on ocular exposure. While application time was found to have a significant impact on the time of maximal concentration in AH, both the application SA and the Higuchi release constant significantly influenced both the maximum concentration and the ocular exposure. CONCLUSIONS: This initial model for ointment ophthalmic formulations is a first step to better understand the interplay between physiological factors and ophthalmic formulation physicochemical properties and their impact on in vivo ocular drug pharmacokinetic performance in rabbits.

Structure-based prediction of drug distribution across the headgroup and core strata of a phospholipid bilayer using surrogate phases.

Solvation of drugs in the core (C) and headgroup (H) strata of phospholipid bilayers affects their physiological transport rates and accumulation. These characteristics, especially a complete drug distribution profile across the bilayer strata, are tedious to obtain experimentally, to the point that even simplified preferred locations are only available for a few dozen compounds. Recently, we showed that the partition coefficient (P) values in the system of hydrated diacetyl phosphatidylcholine (DAcPC) and n-hexadecane (C16), as surrogates of the H- and C-strata of the bilayer composed of the most abundant mammalian phospholipid, PC, agree well with the preferred bilayer location of compounds. High P values are typical for lipophiles accumulating in the core, and low P values are characteristic of cephalophiles preferring the headgroups. This simple pattern does not hold for most compounds, which usually have more even distribution and may also accumulate at the H/C interface. To model complete distribution, the correlates of solvation energies are needed for each drug state in the bilayer: (1) for the H-stratum it is the DAcPC/W P value, calculated as the ratio of the C16/W and C16/DAcPC (W for water) P values; (2) for the C-stratum, the C16/W P value; (3) for the H/C interface, the P values for all plausible molecular poses are characterized using the fragment DAcPC/W and C16/W solvation parameters for the parts of the molecule embedded in the H- and C-strata, respectively. The correlates, each scaled by two Collander coefficients, were used in a nonlinear, mass-balance based model of intrabilayer distribution, which was applied to the easily measurable overall P values of compounds in the DMPC (M = myristoyl) bilayers and monolayers as the dependent variables. The calibrated model for 107 neutral compounds explains 94% of experimental variance, achieves similar cross-validation levels, and agrees well with the nontrivial, experimentally determined bilayer locations for 27 compounds. The resulting structure-based prediction system for intrabilayer distribution will facilitate more realistic modeling of passive transport and drug interactions with those integral membrane proteins, which have the binding sites located in the bilayer, such as some enzymes, influx and efflux transporters, and receptors. If only overall bilayer accumulation is of interest, the 1-octanol/W P values suffice to model the studied set.

Clinical Ocular Exposure Extrapolation for a Complex Ophthalmic Suspension Using Physiologically Based Pharmacokinetic Modeling and Simulation.

The development of generic ophthalmic drug products with complex formulations is challenging due to the complexity of the ocular system and a lack of sensitive testing to evaluate the interplay of its physiology with ophthalmic drugs. New methods are needed to facilitate the development of ophthalmic generic drug products. Ocular physiologically based pharmacokinetic (O-PBPK) models can provide insight into drug partitioning in eye tissues that are usually not accessible and/or are challenging to sample in humans. This study aims to demonstrate the utility of an ocular PBPK model to predict human exposure following the administration of ophthalmic suspension. Besifloxacin (Bes) suspension is presented as a case study. The O-PBPK model for Bes ophthalmic suspension (Besivance® 0.6%) accounts for nasolacrimal drainage, suspended particle dissolution in the tears, ocular absorption, and distribution in the rabbit eye. A topical controlled release formulation was used to integrate the effect of Durasite® on Bes ocular retention. The model was subsequently used to predict Bes exposure after its topical administration in humans. Drug-specific parameters were used as validated for rabbits. The physiological parameters were adjusted to match human ocular physiology. Simulated human ocular pharmacokinetic profiles were compared with the observed ocular tissue concentration data to assess the OCAT models' ability to predict human ocular exposure. The O-PBPK model simulations adequately described the observed concentrations in the eye tissues following the topical administration of Bes suspension in rabbits. After adjustment of physiological parameters to represent the human eye, the extrapolation of clinical ocular exposure following a single ocular administration of Bes suspension was successful.

Effect of Hepatic Impairment on Trofinetide Exposures Using an In Silico Physiologically Based Pharmacokinetic Model.

INTRODUCTION: Trofinetide is the first drug to be approved for the treatment of Rett syndrome. Hepatic impairment is not expected to affect the pharmacokinetic (PK) profile of trofinetide because of predominant renal excretion. This study was conducted to help understand the potential impact of any hepatic impairment on trofinetide PK. METHODS: This study used physiologically based PK modeling to estimate trofinetide exposure (maximum drug concentration and area under the concentration-time curve from time zero to infinity) in virtual patients with mild, moderate, and severe hepatic impairment (per Child-Pugh classification) compared with virtual healthy subjects following a 12 g oral trofinetide dose. RESULTS: In individual deterministic simulations for matched individuals and stochastic simulations at the population level (100 virtual individuals simulated per population), as anticipated, predicted plasma exposures were similar for healthy subjects and for patients with mild, moderate, and severe hepatic impairment. However, predicted blood concentration exposures slightly increased with increasing severity of hepatic impairment because of change in hematocrit levels. CONCLUSION: This study indicates that hepatic impairment is not expected to have a clinically relevant effect on exposure to trofinetide.

Trofinetide is the first approved treatment for Rett syndrome, a rare genetic condition that affects brain development. When a person takes trofinetide, most is removed from the body via the urine in its unchanged form (no chemical alteration). Regulatory requirements mean researchers must confirm the safety of any pharmaceutical drug and evaluate whether changes in liver function lead to harmful levels of drug exposure. Researchers used a computer model to predict how much trofinetide would be present in the blood and plasma (the liquid portion of blood) over time in virtual healthy subjects and virtual patients with varying degrees of liver disease (mild, moderate, or severe). Computer simulations showed that predicted trofinetide levels in plasma were similar in virtual healthy subjects and each virtual patient group with liver disease. Predicted levels of trofinetide in blood were slightly elevated with increasing severity of liver disease. This is because people with liver disease have fewer red blood cells, so the cell portion of blood becomes smaller relative to the liquid portion (plasma), which leads to higher trofinetide concentrations in whole blood (trofinetide minimally enters the red blood cell). The small increase in trofinetide levels in blood and the absence of any change in trofinetide levels in plasma means that people with Rett syndrome and liver disease are unlikely to be exposed to harmful levels of trofinetide after a 12 g oral dose.

Applying Physiologically Based Pharmacokinetic Modeling to Interpret Carbamazepine's Nonlinear Pharmacokinetics and Its Induction Potential on Cytochrome P450 3A4 and Cytochrome P450 2C9 Enzymes.

Carbamazepine (CBZ) is commonly prescribed for epilepsy and frequently used in polypharmacy. However, concerns arise regarding its ability to induce the metabolism of other drugs, including itself, potentially leading to the undertreatment of co-administered drugs. Additionally, CBZ exhibits nonlinear pharmacokinetics (PK), but the root causes have not been fully studied. This study aims to investigate the mechanisms behind CBZ's nonlinear PK and its induction potential on CYP3A4 and CYP2C9 enzymes. To achieve this, we developed and validated a physiologically based pharmacokinetic (PBPK) parent-metabolite model of CBZ and its active metabolite Carbamazepine-10,11-epoxide in GastroPlus®. The model was utilized for Drug-Drug Interaction (DDI) prediction with CYP3A4 and CYP2C9 victim drugs and to further explore the underlying mechanisms behind CBZ's nonlinear PK. The model accurately recapitulated CBZ plasma PK. Good DDI performance was demonstrated by the prediction of CBZ DDIs with quinidine, dolutegravir, phenytoin, and tolbutamide; however, with midazolam, the predicted/observed DDI AUClast ratio was 0.49 (slightly outside of the two-fold range). CBZ's nonlinear PK can be attributed to its nonlinear metabolism caused by autoinduction, as well as nonlinear absorption due to poor solubility. In further applications, the model can help understand DDI potential when CBZ serves as a CYP3A4 and CYP2C9 inducer.

A Physiologically Based Pharmacokinetic Modeling Approach to Assess the Potential for Drug Interactions Between Trofinetide and CYP3A4-Metabolized Drugs.

PURPOSE: Trofinetide is the first drug to be approved by the US Food and Drug Administration for use in the treatment of patients with Rett syndrome, a multisystem disorder requiring multimodal therapies. Cytochrome P450 (CYP) 3A4 metabolizes >50% of therapeutic drugs and is the CYP isozyme most commonly expressed in the liver and intestines. In vitro studies suggest the concentration of trofinetide producing 50% inhibition (IC50) of CYP3A4 is >15 mmol/L; that concentration was much greater than the target clinical concentration associated with the maximal intended therapeutic dose (12 g). Thus, trofinetide has a low potential for drug-drug interactions in the liver. However, there is potential for drug-drug interactions in the intestines given the oral route of administration and expected relatively high concentration in the gastrointestinal tract after dose administration. METHODS: Using a validated physiologically based pharmacokinetic (PBPK) model, deterministic and stochastic simulations were used for assessing the PK properties related to exposure and bioavailability of midazolam (sensitive index substrate for CYP3A4) following an oral (15 mg) or intravenous (2 mg) dose, with and without single-dose and steady-state (12 g) coadministration of oral trofinetide. FINDINGS: Following coadministration of intravenous midazolam and oral trofinetide, the PK properties of midazolam were unchanged. The trofinetide concentration in the gut wall was >15 mmol/L during the first 1.5 hours after dosing. With the coadministration of oral midazolam and trofinetide, the model predicted increases in fraction of dose reaching the portal vein, bioavailability, Cmax, and AUCinf of 30%, 30%, 18%, and 30%, respectively. IMPLICATIONS: In this study that used a PBPK modeling approach, it was shown that CYP3A4 enzyme activity in the liver was not affected by trofinetide coadministration, but trofinetide was predicted to be a weak inhibitor of intestinal CYP3A4 metabolism after oral administration at therapeutic doses.

Physiologically Based Pharmacokinetic Absorption Model for Pexidartinib to Evaluate the Impact of Meal Contents and Intake Timing on Drug Exposure.

Pexidartinib is a systemic treatment for patients with tenosynovial giant cell tumor not amenable to surgery. Oral absorption of pexidartinib is affected by food; administration with a high-fat meal (HFM) or low-fat meal (LFM) increases absorption by approximately 100% and approximately 60%, respectively, compared with the fasted state. Pexidartinib is currently dosed 250 mg orally twice daily with an LFM (approximately 11-14 g of total fat). We developed a physiologically based pharmacokinetic model to determine the impact on drug exposure of dose timing with respect to meals, meal type, and caloric content. A 15%-16% increase in plasma exposure was predicted when consuming an HFM 1 hour after dosing with an LFM, but almost no effect on pharmacokinetics was predicted when an HFM was consumed 3 hours or more before or after pexidartinib dosing with an LFM. Exposure was not significantly affected when pexidartinib was taken with a 500-kcal LFM over the range of fat (approximately 11-14 g of total fat; 20%-25% calories from fat) for an LFM. These findings on timing of pexidartinib dose with respect to meals should be considered by patients and physicians to reduce the potential for side effects.

PBPK Modeling Approach to Predict the Behavior of Drugs Cleared by Metabolism in Pregnant Subjects and Fetuses.

This study aimed to develop a physiologically based pharmacokinetic (PBPK) model that simulates metabolically cleared compounds' pharmacokinetics (PK) in pregnant subjects and fetuses. This model accounts for the differences in tissue sizes, blood flow rates, enzyme expression levels, plasma protein binding, and other physiological factors affecting the drugs' PK in both the pregnant woman and the fetus. The PBPKPlus™ module in GastroPlus® was used to model the PK of metoprolol, midazolam, and metronidazole for both non-pregnant and pregnant groups. For each of the three compounds, the model was first developed and validated against PK data in healthy non-pregnant volunteers and then applied to predict the PK in the pregnant groups. The model accurately described the PK in both the non-pregnant and pregnant groups and explained well the differences in the plasma concentration due to pregnancy. When available, the fetal plasma concentration, placenta, and fetal tissue concentrations were also predicted reasonably well at different stages of pregnancy. The work described the use of a PBPK approach for drug development and demonstrates the ability to predict differences in PK in pregnant subjects and fetal exposure for metabolically cleared compounds.

The Role of Model Master Files for Sharing, Acceptance, and Communication with FDA.

With the evolving role of Model Integrated Evidence (MIE) in generic drug development and regulatory applications, the need for improving Model Sharing, Acceptance, and Communication with the FDA is warranted. Model Master File (MMF) refers to a quantitative model or a modeling platform that has undergone sufficient model Verification & Validation to be recognized as sharable intellectual property that is acceptable for regulatory purposes. MMF provides a framework for regulatorily acceptable modeling practice, which can be used with confidence to support MIE by both the industry and the U.S. Food and Drug Administration (FDA). In 2022, the FDA and the Center for Research on Complex Generics (CRCG) hosted a virtual public workshop to discuss the best practices for utilizing modeling approaches to support generic product development. This report summarizes the presentations and panel discussions of the workshop symposium entitled "Model Sharing, Acceptance, and Communication with the FDA". The symposium and this report serve as a kick-off discussion for further utilities of MMF and best practices of utilizing MMF in drug development and regulatory submissions. The potential advantages of MMFs have garnered acknowledgment from model developers, industries, and the FDA throughout the workshop. To foster a unified comprehension of MMFs and establish best practices for their application, further dialogue and cooperation among stakeholders are imperative. To this end, a subsequent workshop is scheduled for May 2-3, 2024, in Rockville, Maryland, aiming to delve into the practical facets and best practices of MMFs pertinent to regulatory submissions involving modeling and simulation methodologies.

Development of Mechanistic In Vitro-In Vivo Extrapolation to Support Bioequivalence Assessment of Long-Acting Injectables.

Long-acting injectable (LAI) formulations provide sustained drug release over an extended period ranging from weeks to several months to improve efficacy, safety, and compliance. Nevertheless, many challenges arise in the development and regulatory assessment of LAI drug products due to a limited understanding of the tissue response to injected particles (e.g., inflammation) impacting in vivo performance. Mechanism-based in silico methods may support the understanding of LAI-physiology interactions. The objectives of this study were as follows: (1) to use a mechanistic modeling approach to delineate the in vivo performance of DepoSubQ Provera® and formulation variants in preclinical species; (2) to predict human exposure based on the knowledge gained from the animal model. The PBPK model evaluated different elements involved in LAI administration and showed that (1) the effective in vivo particle size is potentially larger than the measured in vitro particle size, which could be due to particle aggregation at the injection site, and (2) local inflammation is a key process at the injection site that results in a transient increase in depot volume. This work highlights how a mechanistic modeling approach can identify critical physiological events and product attributes that may affect the in vivo performance of LAIs.

Structural determinants of drug partitioning in surrogates of phosphatidylcholine bilayer strata.

The knowledge of drug concentrations in bilayer headgroups, core, and at the interface between them is a prerequisite for quantitative modeling of drug interactions with many membrane-bound transporters, metabolizing enzymes and receptors, which have the binding sites located in the bilayer. This knowledge also helps understand the rates of trans-bilayer transport because balanced interactions of drugs with the bilayer strata lead to high rates, while excessive affinities for any stratum cause a slowdown. Experimental determination of bilayer location is so tedious and costly that the data are only available for some fifty compounds. To extrapolate these valuable results to more compounds at a higher throughput, surrogate phases have been used to obtain correlates of the drug affinities for individual strata. We introduced a novel system, consisting of a diacetyl phosphatidylcholine (DAcPC) solution with the water content of the fluid bilayer as the headgroup surrogate and n-hexadecane (C16) representing the core. The C16/DAcPC partition coefficients were measured for 113 selected compounds, containing structural fragments that are frequently occurring in approved drugs. The data were deconvoluted into the ClogP-based fragment solvation characteristics and processed using a solvatochromic correlation. Increased H-bond donor ability and excess molar refractivity of compounds promote solvation in the DAcPC phase as compared to bulk water, contrary to H-bond acceptor ability, dipolarity/polarizability, and volume. The results show that aromates have more balanced distribution in bilayer strata, and thus faster trans-bilayer transport, than similar alkanes. This observation is in accordance with the frequent occurrence of aromatic rings in approved drugs and with the role of rigidity of drug molecules in promoting intestinal absorption. Bilayer locations, predicted using the C16/DAcPC system, are in excellent agreement with available experimental data, in contrast to other surrogate systems.

Structural determinants of drug partitioning in n-hexadecane/water system.

Surrogate phases have been widely used as correlates for modeling transport and partitioning of drugs in biological systems, taking advantage of chemical similarity between the surrogate and the phospholipid bilayer as the elementary unit of biological phases, which is responsible for most of the transport and partitioning. Solvation in strata of the phospholipid bilayer is an important drug characteristic because it affects the rates of absorption and distribution, as well as the interactions with the membrane proteins having the binding sites located inside the bilayer. The bilayer core can be emulated by n-hexadecane (C16), and the headgroup stratum is often considered a hydrophilic phase because of the high water content. Therefore, we tested the hypothesis that the C16/water partition coefficients (P) can predict the bilayer locations of drugs and other small molecules better than other surrogate systems. Altogether 514 PC16/W values for nonionizable (458) and completely ionized (56) compounds were collected from the literature or measured, when necessary. With the intent to create a fragment-based prediction system, the PC16/W values were factorized into the fragment solvation parameters (f) and correction factors based on the ClogP fragmentation scheme. A script for the PC16/W prediction using the ClogP output is provided. To further expand the prediction system and reveal solvation differences, the fC16/W values were correlated with their more widely available counterparts for the 1-octanol/water system (O/W) using solvatochromic parameters. The analysis for 50 compounds with known bilayer location shows that the available and predicted PC16/W and PO/W values alone or the PC16/O values representing their ratio do not satisfactorily predict the preference for drug accumulation in bilayer strata. These observations indicate that the headgroups stratum, albeit well hydrated, does not have solvation characteristics similar to water and is also poorly described by the O/W partition characteristics.

Drug-drug interaction prediction of ziritaxestat using a physiologically based enzyme and transporter pharmacokinetic network interaction model.

Ziritaxestat, an autotaxin inhibitor, was under development for the treatment of idiopathic pulmonary fibrosis. It is a substrate of cytochrome P450 3A4 (CYP3A4) and P-glycoprotein and a weak inhibitor of the CYP3A4 and OATP1B1 pathways. We developed a physiologically based pharmacokinetic (PBPK) network interaction model for ziritaxestat that incorporated its metabolic and transporter pathways, enabling prediction of its potential as a victim or perpetrator of drug-drug interactions (DDIs). Concurrently, we evaluated CYP3A4 autoinhibition, including time-dependent inhibition. In vitro information and clinical data from healthy volunteer studies were used for model building and validation. DDIs with rifampin, itraconazole, voriconazole, pravastatin, and rosuvastatin were predicted, followed by validation against a test dataset. DDIs of ziritaxestat as a victim or perpetrator were simulated using the final model. Predicted-to-observed DDI ratios for the maximum plasma concentration (Cmax ) and the area under the plasma concentration-time curve (AUC) were within a two-fold ratio for both the metabolic and transporter-mediated simulated DDIs. The predicted impact of autoinhibition/autoinduction or time-dependent inhibition of CYP3A4 was a 12% decrease in exposure. Model-based predictions for ziritaxestat as a victim of DDIs with a moderate CYP3A4 inhibitor (fluconazole) suggested a 2.6-fold increase in the AUC of ziritaxestat, while multiple doses of a strong inhibitor (voriconazole) would increase the AUC by 15-fold. Efavirenz would yield a three-fold decrease in the AUC of ziritaxestat. As a perpetrator, ziritaxestat was predicted to increase the AUC of the CYP3A4 index substrate midazolam by 2.7-fold. An overarching PBPK model was developed that could predict DDI liability of ziritaxestat for both CYP3A4 and the transporter pathways.

Long-Acting Injectable Aqueous Suspensions-Summary From an AAPS Workshop.

Through many years of clinical application of long-acting injectables, there is clear proof that this type of formulation does not just provide the patient with convenience, but more importantly a more effective treatment of the medication provided. The formulation approach therefore contains huge untapped potential to improve the quality of life of many patients with a variety of different diseases. This review provides a summary of some of the central talks provided at the workshop with focus on aqueous suspensions and their use as a long-acting injectable. Elements as formulation, manufacturing, in vitro dissolution methods, in vitro and in vivo correlation, in silico modelling provide an insight into some of the current understandings, learnings, and not least gaps in the field.

Leveraging Physiologically Based Modelling to Provide Insights on the Absorption of Paliperidone Extended-Release Formulation under Fed and Fasting Conditions.

Paliperidone was approved by the US FDA in 2006 as an extended-release (ER) tablet (Invega®) for the once-daily treatment of schizophrenia. This osmotic-controlled release oral delivery system (OROS) offers advantages, such as the prevention of plasma concentration fluctuation and reduced dosing frequency. The administration of the ER after a high-fat/high-calorie meal leads to increased maximum plasma concentration and area under the curve values by 60% and 54%, respectively. Food has various effects on gastrointestinal (GI) physiology, including changed transit times, changed volumes, altered pH in different GI compartments, secretion of bile salts, and increased hepatic blood flow. This may affect solubility, the dissolution rate, absorption, and the pharmacokinetics. The aim of this study was to apply physiologically based absorption modeling (PBAM) to provide insights on paliperidone ER absorption under fed and fasting conditions. The PBAM adequately predicted absorption from the OROS formulation under both conditions. Absorption primarily occurs in the ascending colon and caecum. After a high-fat/high-calorie meal, absorption is increased through the jejunum, ileum, and colon due to either increased solubilization or the better efficiency of the OROS technology. PBAM-guided approaches can improve the understanding of branded drugs and thereby aid in guiding the development of generic formulations or formulation alternatives.

Comprehensive Physiologically Based Pharmacokinetic Model to Assess Drug-Drug Interactions of Phenytoin.

Regulatory agencies worldwide expect that clinical pharmacokinetic drug-drug interactions (DDIs) between an investigational new drug and other drugs should be conducted during drug development as part of an adequate assessment of the drug's safety and efficacy. However, it is neither time nor cost efficient to test all possible DDI scenarios clinically. Phenytoin is classified by the Food and Drug Administration as a strong clinical index inducer of CYP3A4, and a moderate sensitive substrate of CYP2C9. A physiologically based pharmacokinetic (PBPK) platform model was developed using GastroPlus® to assess DDIs with phenytoin acting as the victim (CYP2C9, CYP2C19) or perpetrator (CYP3A4). Pharmacokinetic data were obtained from 15 different studies in healthy subjects. The PBPK model of phenytoin explains the contribution of CYP2C9 and CYP2C19 to the formation of 5-(4'-hydroxyphenyl)-5-phenylhydantoin. Furthermore, it accurately recapitulated phenytoin exposure after single and multiple intravenous and oral doses/formulations ranging from 248 to 900 mg, the dose-dependent nonlinearity and the magnitude of the effect of food on phenytoin pharmacokinetics. Once developed and verified, the model was used to characterize and predict phenytoin DDIs with fluconazole, omeprazole and itraconazole, i.e., simulated/observed DDI AUC ratio ranging from 0.89 to 1.25. This study supports the utility of the PBPK approach in informing drug development.