Utility of physiologically based absorption modeling in implementing Quality by Design in drug development

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.

Physiologically based pharmacokinetic modeling to predict maternal pharmacokinetics and fetal carbamazepine exposure during pregnancy

Carbamazepine is an antiepileptic drug commonly used in pregnant women, during which the physiological changes may affect its efficacy. The aim of this study was to establish a physiologically based pharmacokinetic (PBPK) model of carbamazepine and its active metabolite carbamazepine-10,11-epoxide, and simulate maternal and fetal pharmacokinetic changes of carbamazepine and carbamazepine-10,11-epoxide in different trimesters and propose dose adjustment. We established pregnancy PBPK models for carbamazepine and carbamazepine-10,11-epoxide in PK-Sim® and Mobi® and validated the models with observed data from clinical reports. The placental transfer parameters obtained using different methods were also imported into the model and compared with the observed data to establish and validate fetal pharmacokinetic curves. The simulated results showed that mean steady-state trough plasma concentration of carbamazepine decreased by 27, 43.1, and 52 % during the first, second, and third trimesters, respectively. Therefore, to achieve an optimum therapeutic concentration, administering at least 1.4, 1.8, and 2.1 times the baseline dose of carbamazepine in the first, second, and third trimesters, respectively can be used as a dose reference. In conclusion, this study established and validated a pregnancy PBPK model of carbamazepine and carbamazepine-10,11-epoxide to assess exposure in pregnant women and fetuses, which provided a reference for the dosage adjustment of carbamazepine during pregnancy.

Phys-DAT: A physiologically-based pharmacokinetic model for unraveling the dissolution, transit and absorption processes using PhysPK®

BACKGROUND AND OBJECTIVE

In silico methods have become the key for efficiently testing and qualifying drug properties. Due to the complexity of the LADME processes and drug characteristics associated to oral drug absorption, there is a growing demand in the development of Physiologically-based Pharmacokinetic (PBPK) software with greater flexibility. Thus, the aims of this work are (i) to develop a mechanistic-based modeling framework of dissolution, transit and absorption (Phys-DAT) processes in the PhysPK platform and (ii) to assess the predictive power of the acausal MOOM methodology embedded in Phys-DAT versus reference ODE-based PBPK software.

METHODS

A PBPK model was developed including unreleased, undissolved and dissolved thermodynamic states of the drug. The gastrointestinal tract (GI) was represented by nine compartments and first-order transit kinetics was assumed for the drug fractions. Dissolution processes were described using solubility-independent or solubility-dependent mechanisms and pH effects. Linear transit and linear absorption mechanisms including gradual decrease absorption rate were considered to represent the passive diffusion process. Internal validation of the Phys-DAT model was performed through simulation-based analysis, considering different theoretical scenarios. External validation was carried out using in silico and in vivo data of GI segments and plasma concentrations. Both BCS I and II class drugs were included.

RESULTS

The model predicts plasma-concentration profiles of each compartment for undissolved, dissolved, and absorbed fractions using PhysPK® v.2.4.1. Internal and external validations demonstrate that the model aligned with the theoretical assumptions and accurately predicted Cmax, Tmax, and AUC 0-t for both BCS I and II drugs. Average Fold Error (AFE), Absolute Average Fold Error (AAFE), and Percent Prediction Error (PPE) calculations indicate good predictive performance, with predicted/observed ratios falling within the acceptable range.

CONCLUSIONS

Phys-DAT represents a mechanistic model for predicting oral absorption, including the dissolution, pH effect, transit, and absorption processes. PhysPK has shown to be a tool with strong prediction accuracy, similar to the obtained by ODE-based PBPK reference software, and the results obtained with the Phys-DAT model for oral administered drugs showed predictive reliability in healthy volunteers, setting the basis to determine the interchangeability of the acausal MOOM methodology with other modeling approaches.

Physiologically Based Pharmacokinetic Modeling of Extracellular Vesicles

Extracellular vesicles (EVs) are lipid membrane bound-cell-derived structures that are a key player in intercellular communication and facilitate numerous cellular functions such as tumor growth, metastasis, immunosuppression, and angiogenesis. They can be used as a drug delivery platform because they can protect drugs from degradation and target specific cells or tissues. With the advancement in the technologies and methods in EV research, EV-therapeutics are one of the fast-growing domains in the human health sector. Therapeutic translation of EVs in clinics requires assessing the quality, safety, and efficacy of the EVs, in which pharmacokinetics is very crucial. We report here the application of physiologically based pharmacokinetic (PBPK) modeling as a principal tool for the prediction of absorption, distribution, metabolism, and excretion of EVs. To create a PBPK model of EVs, researchers would need to gather data on the size, shape, and composition of the EVs, as well as the physiological processes that affect their behavior in the body. The PBPK model would then be used to predict the pharmacokinetics of drugs delivered via EVs, such as the rate at which the drug is absorbed and distributed throughout the body, the rate at which it is metabolized and eliminated, and the maximum concentration of the drug in the body. This information can be used to optimize the design of EV-based drug delivery systems, including the size and composition of the EVs, the route of administration, and the dose of the drug. There has not been any dedicated review article that describes the PBPK modeling of EV. This review provides an overview of the absorption, distribution, metabolism, and excretion (ADME) phenomena of EVs. In addition, we will briefly describe the different computer-based modeling approaches that may help in the future of EV-based therapeutic research.

Progressive tools and critical strategies for development of best fit PBPK model aiming better in vitro-in vivo correlation

Nowadays, conducting discriminative dissolution experiments employing physiologically based pharmacokinetic modeling (PBPK) or physiologically based biopharmaceutical modeling (PBBM) is gaining significant importance in quantitatively predicting oral absorption of drugs. Mechanistic understanding of each process involved in drug absorption and its impact on the performance greatly facilitates designing a formulation with high confidence. Unfortunately, the biggest challenge scientists are facing in current days is the lack of standardized protocol for integrating dissolution experiment data during PBPK modeling. However, in vitro-in vivo drug release interrelation can be improved with the consideration and development of appropriate biorelevant dissolution media that closely mimic physiological conditions. Multiple reported dissolution models have described nature and functionality of different regions of the gastrointestinal tract (GI) to more accurately design discriminative dissolution media. Dissolution experiment data can be integrated either mechanistically or without a mechanism depending primarily on the formulation type, biopharmaceutics classification system (BCS) class and particle size of the drug substance. All such parameters are required to be considered for selecting the appropriate functions during PBPK modeling to produce a best fit model. The primary focus of this review is to critically discuss various progressive dissolution models and tools, existing challenges and approaches for establishing best fit PBPK model aiming better in vitro-in vivo correlation (IVIVC). Strategies for proper selection of dissolution models as an input function in PBPK/PBBM modeling have also been critically discussed. Logical and scientific pathway for selection of different type of functions and integration events in the commercially available in silico software has been described through case studies.

Current State and Challenges of Physiologically Based Biopharmaceutics Modeling (PBBM) in Oral Drug Product Development

Physiologically based biopharmaceutics modeling (PBBM) emphasizes the integration of physicochemical properties of drug substance and formulation characteristics with system physiological parameters to predict the absorption and pharmacokinetics (PK) of a drug product. PBBM has been successfully utilized in drug development from discovery to postapproval stages and covers a variety of applications. The use of PBBM facilitates drug development and can reduce the number of preclinical and clinical studies. In this review, we summarized the major applications of PBBM, which are classified into six categories: formulation selection and development, biopredictive dissolution method development, biopharmaceutics risk assessment, clinically relevant specification settings, food effect evaluation and pH-dependent drug-drug-interaction risk assessment. The current state of PBBM applications is illustrated with examples from published studies for each category of application. Despite the variety of PBBM applications, there are still many hurdles limiting the use of PBBM in drug development, that are associated with the complexity of gastrointestinal and human physiology, the knowledge gap between the in vitro and the in vivo behavior of drug products, the limitations of model interfaces, and the lack of agreed model validation criteria, among other issues. The challenges and essential considerations related to the use of PBBM are discussed in a question-based format along with the scientific thinking on future research directions. We hope this review can foster open discussions between the pharmaceutical industry and regulatory agencies and encourage collaborative research to fill the gaps, with the ultimate goal to maximize the applications of PBBM in oral drug product development.

Regulatory utility of physiologically based pharmacokinetic modeling for assessing food impact in bioequivalence studies: A workshop summary report

This workshop report summarizes the presentations and panel discussion related to the use of physiologically based pharmacokinetic (PBPK) modeling approaches for food effect assessment, collected from Session 2 of Day 2 of the workshop titled "Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches." The US Food and Drug Administration in collaboration with the Center for Research on Complex Generics organized this workshop where this particular session titled "Oral PBPK for Evaluating the Impact of Food on BE" presented successful cases of PBPK modeling approaches for food effect assessment. Recently, PBPK modeling has started to gain popularity among academia, industries, and regulatory agencies for its potential utility during bioavailability (BA) and/or bioequivalence (BE) studies of new and generic drug products to assess the impact of food on BA/BE. Considering the promises of PBPK modeling in generic drug development, the aim of this workshop session was to facilitate knowledge sharing among academia, industries, and regulatory agencies to understand the knowledge gap and guide the path forward. This report collects and summarizes the information presented and discussed during this session to disseminate the information into a broader audience for further advancement in this area.

Why Do Dietary Flavonoids Have a Promising Effect as Enhancers of Anthracyclines? Hydroxyl Substituents, Bioavailability and Biological Activity

Anthracyclines currently play a key role in the treatment of many cancers, but the limiting factor of their use is the widespread phenomenon of drug resistance and untargeted toxicity. Flavonoids have pleiotropic, beneficial effects on human health that, apart from antioxidant activity, are currently considered small molecules-starting structures for drug development and enhancers of conventional therapeutics. This paper is a review of the current and most important data on the participation of a selected series of flavonoids: chrysin, apigenin, kaempferol, quercetin and myricetin, which differ in the presence of an additional hydroxyl group, in the formation of a synergistic effect with anthracycline antibiotics. The review includes a characterization of the mechanism of action of flavonoids, as well as insight into the physicochemical parameters determining their bioavailability in vitro. The crosstalk between flavonoids and the molecular activity of anthracyclines discussed in the article covers the most important common areas of action, such as (1) disruption of DNA integrity (genotoxic effect), (2) modulation of antioxidant response pathways, and (3) inhibition of the activity of membrane proteins responsible for the active transport of drugs and xenobiotics. The increase in knowledge about the relationship between the molecular structure of flavonoids and their biological effect makes it possible to more effectively search for derivatives with a synergistic effect with anthracyclines and to develop better therapeutic strategies in the treatment of cancer.

The Use of Physiologically Based Pharmacokinetic Analyses-in Biopharmaceutics Applications -Regulatory and Industry Perspectives

The use of physiologically based pharmacokinetic (PBPK) modeling to support the drug product quality attributes, also known as physiologically based biopharmaceutics modeling (PBBM) is an evolving field and the interest in using PBBM is increasing. The US-FDA has emphasized on the use of patient centric quality standards and clinically relevant drug product specifications over the years. Establishing an in vitro in vivo link is an important step towards achieving the goal of patient centric quality standard. Such a link can aid in constructing a bioequivalence safe space and establishing clinically relevant drug product specifications. PBBM is an important tool to construct a safe space which can be used during the drug product development and lifecycle management. There are several advantages of using the PBBM approach, though there are also a few challenges, both with in vitro methods and in vivo understanding of drug absorption and disposition, that preclude using this approach and therefore further improvements are needed. In this review we have provided an overview of experience gained so far and the current perspective from regulatory and industry point of view. Collaboration between scientists from regulatory, industry and academic fields can further help to advance this field and deliver on promises that PBBM can offer towards establishing patient centric quality standards.

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.

Opportunities and challenges of physiologically based pharmacokinetic modeling in drug delivery

Physiologically based pharmacokinetic (PBPK) modeling is an important in silico tool to bridge drug properties and in vivo PK behaviors during drug development. Over the recent decade, the PBPK method has been largely applied to drug delivery systems (DDS), including oral, inhaled, transdermal, ophthalmic, and complex injectable products. The related therapeutic agents have included small-molecule drugs, therapeutic proteins, nucleic acids, and even cells. Simulation results have provided important insights into PK behaviors of new dosage forms, which strongly support drug regulation. In this review, we comprehensively summarize recent progress in PBPK applications in drug delivery, which shows large opportunities for facilitating drug development. In addition, we discuss the challenges of applying this methodology from a practical viewpoint.

Physiologically Based Biopharmaceutics Model of Vildagliptin Modified Release (MR) Tablets to Predict In Vivo Performance and Establish Clinically Relevant Dissolution Specifications

The objective of the study was to predict pharmacokinetic (PK) and pharmacodynamic (PD) parameters of matrix-based modified release (MR) drug product of vildagliptin. Physiologically based biopharmaceutics modeling (PBBM) was developed using GastroPlus™ based on the available data including immediate-release (IR) drug product of vildagliptin. In vitro-in vivo correlation (IVIVC) was developed using mechanistic deconvolution to predict plasma concentration-time profile and PK parameters for a MR drug product planned for clinical use. Both methods, i.e., PBBM and IVIVC, were compared for the predicted PK parameters. Integration of DDDPlus™ and GastroPlus™ modeling was performed to explore clinically relevant dissolution specifications for vildagliptin MR tablets. The bioequivalence (BE) between batches with different dissolution specifications was evaluated using virtual clinical trials. The PD effect of dipeptidyl peptidase-IV (DPP-IV) inhibition was simulated utilizing PDPlus™ model in GastroPlus™. The results indicated that IVIVC best correlated the simulated PK parameters with those observed with the clinical study. The outcomes highlight the importance of integration of in vitro and in silico tools towards predictability of PK and PD parameters for a MR drug product. However, the post absorptive phase was found to be more dependent on the demographics of the healthy subjects.

Lilly Absorption Modeling Platform: A Tool for Early Absorption Assessment

Oral drug absorption modeling has developed at a rapid pace in the 40 years or so since the first ideas for mathematical approaches to oral absorption were introduced. The success of compartmental approaches accelerated the uptake of absorption modeling, and over the last 20 years, work on absorption modeling has shifted almost exclusively to the compartmental framework. This report describes a new noncompartmental absorption modeling framework, the Lilly Absorption Modeling Platform (LAMP). LAMP connects a well-mixed stomach to a continuous tube model of the small intestine with plug flow. Within the continuous tube framework, the model includes intestinal mixing and a novel highly tunable precipitation model that can describe a combination of rapid nucleation and slow growth. The framework is designed to balance speed, consistency, and ease of use with a minimum of model complexity to capture the essential features of gastrointestinal (GI) physiology and critical elements of the oral absorption process. The model was validated based on predictions of the fraction absorbed and the maximum absorbable dose for a set of Eli Lilly and Company clinical compounds.

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.

Artemisinin Cocrystals for Bioavailability Enhancement. Part 2: In Vivo Bioavailability and Physiologically Based Pharmacokinetic Modeling

We report the evaluation and prediction of the pharmacokinetic (PK) performance of artemisinin (ART) cocrystal formulations, that is, 1:1 artemisinin/orcinol (ART-ORC) and 2:1 artemisinin/resorcinol (ART²-RES), using in vivo murine animal and physiologically based pharmacokinetic (PBPK) models. The efficacy of the ART cocrystal formulations along with the parent drug ART was tested in mice infected with Plasmodium berghei. When given at the same dose, the ART cocrystal formulation showed a significant reduction in parasitaemia at day 4 after infection compared to ART alone. PK parameters including C_max (maximum plasma concentration), T_max (time to C_max), and AUC (area under the curve) were obtained by determining drug concentrations in the plasma using liquid chromatography-high-resolution mass spectrometry (LC-HRMS), showing enhanced ART levels after dosage with the cocrystal formulations. The dose-response tests revealed that a significantly lower dose of the ART cocrystals in the formulation was required to achieve a similar therapeutic effect as ART alone. A PBPK model was developed using a PBPK mouse simulator to accurately predict the in vivo behavior of the cocrystal formulations by combining in vitro dissolution profiles with the properties of the parent drug ART. The study illustrated that information from classical in vitro and in vivo experimental investigations of the parent drug of ART formulations can be coupled with PBPK modeling to predict the PK parameters of an ART cocrystal formulation in an efficient manner. Therefore, the proposed modeling strategy could be used to establish in vitro and in vivo correlations for different cocrystals intended to improve dissolution properties and to support clinical candidate selection, contributing to the assessment of cocrystal developability and formulation development.

In silico bioavailability for BCS class II efavirenz tablets using biorelevant dissolution media for IVIVR and simulation of formulation changes

OBJECTIVE

This work aims to evaluate the ability of biorelevant dissolution media to simulate the bioavailability of efavirenz tablets, establish an in vitro-in vivo relationship (IVIVR) based on in vivo data using GastroPlus^® and simulate formulation changes using DDDPlus™.

METHODS

Solubility and drug release profiles were conducted in SLS 0.5% and biorelevant media, such as FaSSIF, FeSSIF, FaSSIF-V2, and FeSSIF-V2. The efavirenz physicochemical properties were used to simulate the plasma concentration profile and compare the simulated pharmacokinetic parameters in fasted and fed states. An IVIVR was developed using Loo-Riegelman as the deconvolution method to estimate drug bioavailability. DDDPlus™ was used to perform virtual trials of formulations to evaluate whether formulations changes and the efavirenz particle size could influence the bioavailability.

RESULTS

The drug dissolution displayed higher levels in the biorelevant media that simulated gut-fed state (FeSSIF and FeSSIF-V2). The absorption model successfully predicted the efavirenz pharmacokinetics, and FeSSIF-V2 was chosen as the predictive dissolution media, while an IVIVR was established using the Loo-Riegelman deconvolution method.

CONCLUSIONS

The present work provides valuable information about efavirenz solubility and kinetics in the gastrointestinal tract, allowing an IVIVR to support future formulation changes. This understanding is essential for rational science-driven formulation development. At least, this study also showed the validity and applicability of in vitro and in silico tools in the regulatory scenario helping on drug development.

In Silico Modeling and Simulation to Guide Bioequivalence Testing for Oral Drugs in a Virtual Population

Model-informed drug discovery and development (MID3) shows great advantages in facilitating drug development. A physiologically based pharmacokinetic model is one of the powerful computational approaches of MID3, and the emerging field of virtual bioequivalence is well recognized to be the future of the physiologically based pharmacokinetic model. Based on the translational link between in vitro, in silico, and in vivo, virtual bioequivalence study can evaluate the similarity and potential difference of pharmacokinetic and clinical performance between test and reference formulations. With the aid of virtual bioequivalence study, the pivotal information of clinical trials can be provided to streamline the development for both new and generic drugs. However, a regulatory framework of virtual bioequivalence study has not reached its full maturity. Therefore, this article aims to present an overview of the current status of bioequivalence study, identify the framework of virtual bioequivalence studies for oral drugs, and also discuss the future opportunities of virtual bioequivalence in supporting the waiver and optimization of in vivo clinical trials.

Biowaiver Monograph for Immediate-Release Solid Oral Dosage Forms: Carbamazepine

Literature relevant to assessing whether BCS-based biowaivers can be applied to immediate release (IR) solid oral dosage forms containing carbamazepine as the single active pharmaceutical ingredient are reviewed. Carbamazepine, which is used for the prophylactic therapy of epilepsy, is a non-ionizable drug that cannot be considered "highly soluble" across the range of pH values usually encountered in the upper gastrointestinal tract. Furthermore, evidence in the open literature suggests that carbamazepine is a BCS Class 2 drug. Nevertheless, the oral absolute bioavailability of carbamazepine lies between 70 and 78% and both in vivo and in vitro data support the classification of carbamazepine as a highly permeable drug. Since the therapeutic and toxic plasma level ranges overlap, carbamazepine is considered to have a narrow therapeutic index. For these reasons, a BCS based biowaiver for IR tablets of carbamazepine cannot be recommended. Interestingly, in nine out of ten studies, USP dissolution conditions (900 mL water with 1% SLS, paddle, 75 rpm) appropriately discriminated among bioinequivalent products and this may be a way forward to predicting whether a given formulation will be bioequivalent to the comparator product.

Pharmacokinetics of the CYP3A4 and CYP2B6 Inducer Carbamazepine and Its Drug-Drug Interaction Potential: A Physiologically Based Pharmacokinetic Modeling Approach

The anticonvulsant carbamazepine is frequently used in the long-term therapy of epilepsy and is a known substrate and inducer of cytochrome P450 (CYP) 3A4 and CYP2B6. Carbamazepine induces the metabolism of various drugs (including its own); on the other hand, its metabolism can be affected by various CYP inhibitors and inducers. The aim of this work was to develop a physiologically based pharmacokinetic (PBPK) parent-metabolite model of carbamazepine and its metabolite carbamazepine-10,11-epoxide, including carbamazepine autoinduction, to be applied for drug-drug interaction (DDI) prediction. The model was developed in PK-Sim, using a total of 92 plasma concentration-time profiles (dosing range 50-800 mg), as well as fractions excreted unchanged in urine measurements. The carbamazepine model applies metabolism by CYP3A4 and CYP2C8 to produce carbamazepine-10,11-epoxide, metabolism by CYP2B6 and UDP-glucuronosyltransferase (UGT) 2B7 and glomerular filtration. The carbamazepine-10,11-epoxide model applies metabolism by epoxide hydroxylase 1 (EPHX1) and glomerular filtration. Good DDI performance was demonstrated by the prediction of carbamazepine DDIs with alprazolam, bupropion, erythromycin, efavirenz and simvastatin, where 14/15 DDI AUClast ratios and 11/15 DDI Cmax ratios were within the prediction success limits proposed by Guest et al. The thoroughly evaluated model will be freely available in the Open Systems Pharmacology model repository.

Physiologically-based pharmacokinetics modeling to investigate formulation factors influencing the generic substitution of dabigatran etexilate

The exposure‐response relationship of direct acting oral anti‐coagulants (DOACs) for bleeding risk is steep relative to ischemic stroke reduction. As a result, small changes in exposure may lead to bleeding events. The overall goal of this project was to determine the effect of critical formulation parameters on the pharmacokinetics (PKs) and thus safety and efficacy of generic DOACs. In this first installment of our overall finding, we developed and verified a physiologically‐based PK (PBPK) model for dabigatran etexilate (DABE) and its metabolites. The model was developed following a middle out approach leveraging available in vitro and in vivo data. External validity of the model was confirmed by overlapping predicted and observed PK profiles for DABE as well as free and total dabigatran for a dataset not used during model development. The verified model was applied to interrogate the impact of modulating the microenvironment pH on DABE systemic exposure. The PBPK exploratory analyses highlighted the high sensitivity of DABE exposure to supersaturation ratio and precipitation kinetics.

The emerging role of physiologically-based pharmacokinetic/biopharmaceutics modeling in formulation development

Computer-based (in silico) modeling & simulation tools have been embraced in different fields of pharmaceutics for a variety of applications. Among these, physiologically-based pharmacokinetic/biopharmaceutics modeling (PBPK/PBBM) emerged as a particularly useful tool in formulation development. PBPK/PBBM facilitated strategies have been increasingly evaluated over the past few years, as demonstrated by several reports from the pharmaceutical industry, and a number of research and review papers on this subject. Also, the leading regulatory authorities have recently issued guidance on the use of PBPK modeling in formulation design. In silico PBPK models can comprise different dosing routes (oral, intraoral, parenteral, inhalation, ocular, dermal etc.), although the majority of published examples refer to modeling of oral drugs performance. In order to facilitate the use of PBPK modeling tools, a couple of companies have launched commercially available software such as GastroPlus™, Simcyp™ PBPK Simulator and PK-Sim®. This paper highlights various application fields of PBPK/PBBM modeling, along with the basic principles, advantages and limitations of this approach, and provides relevant examples to demonstrate the practical utility of modeling & simulation tools in different stages of formulation development.

5-Fluorouracil Loaded Biogenic and Albumin Capped Gold Nanoparticles Using Bacterial Enzyme—In Vitro-In Silico Gastroplus® Simulation and Prediction

The study investigated in situ biosynthesis of albumin capped 5-fluorouracil (5-FU) loaded gold nanoparticles (NPs) using bacterial extract for enhanced efficacy against MCF-7 and in silico prediction using a GastroPlus® software. The optimized formulations were characterized for morphology, size, zeta potential, drug loading (%DL) and entrapment (%EE), compatibility, in vitro drug release, in vitro hemolysis, cellular toxicity and apoptosis studies. The results exhibited highly dispersed albumin capped mono-metallic stable NPs. Spherical size, negative zeta potential and polydispersity index were in range of 38.25–249.62 nm, 18.18–29.87 mV and 0.11–0.283, respectively. F11, F7 and F3 showed a progressive increase in %DL and %EE with increased concentration of the cellular lysate (100% > 50% > 10%). The drug release was relatively extended over 48 h as compared to drug solution (96.64% release within 5 h). The hemolysis result ensured hemocompatibility (<14%) at the explored concentration. The biogenic F11 was more cytotoxic (81.99% inhibition by F11 and 72.04% by pure 5-FU) to the MCF-7 cell lines as compared to others which may be attributed to the preferential accumulation by the tumor cell and capped albumin as the source of energy to the cancer cells. Finally, GastroPlus® predicted the key factors responsible for improved pharmacokinetics parameters and regional absorption from various segments of human intestine. Thus, the approach can be more efficacious and suitable to control breast cancer when administered transdermally or orally.

Well-tempered MCMC simulations for population pharmacokinetic models

A full Bayesian statistical treatment of complex pharmacokinetic or pharmacodynamic models, in particular in a population context, gives access to powerful inference, including on model structure. Markov Chain Monte Carlo (MCMC) samplers are typically used to estimate the joint posterior parameter distribution of interest. Among MCMC samplers, the simulated tempering algorithm (TMCMC) has a number of advantages: it can sample from sharp multi-modal posteriors; it provides insight into identifiability issues useful for model simplification; it can be used to compute accurate Bayes factors for model choice; the simulated Markov chains mix quickly and have assured convergence in certain conditions. The main challenge when implementing this approach is to find an adequate scale of auxiliary inverse temperatures (perks) and associated scaling constants. We solved that problem by adaptive stochastic optimization and describe our implementation of TMCMC sampling in the GNU MCSim software. Once a grid of perks is obtained, it is easy to perform posterior-tempered MCMC sampling or likelihood-tempered MCMC (thermodynamic integration, which bridges the joint prior and the posterior parameter distributions, with assured convergence of a single sampling chain). We compare TMCMC to other samplers and demonstrate its efficient sampling of multi-modal posteriors and calculation of Bayes factors in two stylized case-studies and two realistic population pharmacokinetic inference problems, one of them involving a large PBPK model.

Improved Oral Pharmacokinetics of Pentoxifylline with Palm Oil and Capmul® MCM Containing Self-Nano-Emulsifying Drug Delivery System

Pentoxifylline (PTX), an anti-hemorrhage drug used in the treatment of intermittent claudication, is extensively metabolized by the liver resulting in a reduction of the therapeutic levels within a short duration of time. Self-nano-emulsifying drug delivery system (SNEDDS) is well reported to enhance the bio-absorption of drugs by forming nano-sized globules upon contact with the biological fluids after oral administration. The present study aimed to formulate, characterize, and improve the oral bioavailability of PTX using SNEDDS. The formulated SNEDDS consisted of palm oil, Capmul® MCM, and Tween® 80 as oil, surfactant, and co-surfactant, respectively. The mixture design module under the umbrella of the design of experiments was used for the optimization of SNEDDS. The dynamic light-scattering technique was used to confirm the formation of nanoemulsion based on the globule size, in addition to the turbidity measurements. In vivo bioavailability studies were carried out on male Wistar rats. The pharmacokinetic parameters upon oral administration were calculated using the GastroPlus software. The optimized SNEDDS had a mean globule size of 165 nm with minimal turbidity in an aqueous medium. Bioavailability of PTX increased 1.5-folds (AUC = 1013.30 ng h/mL) as SNEDDS than the pure drug with an AUC of 673.10 ng h/mL. In conclusion, SNEDDS was seen to enhance the bioavailability of PTX and can be explored to effectively control the incidents of intermittent claudication.

Entering the era of computationally driven drug development

Historically, failure rates in drug development are high; increased sophistication and investment throughout the process has shifted the reasons for attrition, but the overall success rates have remained stubbornly and consistently low. Only 8% of new entities entering clinical testing gain regulatory approval, indicating that significant obstacles still exist for efficient therapeutic development. The continued high failure rate can be partially attributed to the inability to link drug exposure with the magnitude of observed safety and efficacy-related pharmacodynamic (PD) responses; frequently, this is a result of nonclinical models exhibiting poor prediction of human outcomes across a wide range of disease conditions, resulting in faulty evaluation of drug toxicology and efficacy. However, the increasing quality and standardization of experimental methods in preclinical stages of testing has created valuable data sets within companies that can be leveraged to further improve the efficiency and accuracy of preclinical prediction for both pharmacokinetics (PK) and PD. Models of Quantitative structure-activity relationships (QSAR), physiologically based pharmacokinetics (PBPK), and PK/PD relationships have also improved efficiency. Founded on a core understanding of biochemistry and physiological interactions of xenobiotics, these in silico methods have the potential to increase the probability of compound success in clinical trials. Integration of traditional computational methods with machine-learning approaches and existing internal pharma databases stands to make a fundamental impact on the speed and accuracy of predictions during the process of drug development and approval.

The Biopharmaceutics Classification System (BCS) and the Biopharmaceutics Drug Disposition Classification System (BDDCS): Beyond guidelines

The recent impact of the Biopharmaceutics Classification System (BCS) and the Biopharmaceutics Drug Disposition Classification System (BDDCS) on relevant scientific advancements is discussed. The major advances associated with the BCS concern the extensive work on dissolution of poorly absorbed BCS class II drugs in nutritional liquids (e.g. milk, peanut oil) and biorelevant media for the accurate prediction of the rate and the extent of oral absorption. The use of physiologically based pharmacokinetic (PBPK) modeling as predictive tool for bioavailability is also presented. Since recent dissolution studies demonstrate that the two mechanisms (diffusion- and reaction-limited dissolution) take place simultaneously, the neglected reaction-limited dissolution models are discussed, regarding the biopharmaceutical classification of drugs. Solubility- and dissolution-enhancing formulation strategies based on the supersaturation principle to enhance the extent of drug absorption, along with the applications of the BDDCS to the understanding of disposition phenomena are reviewed. Finally, recent classification systems relevant either to the BCS or the BDDCS are presented. These include: i) a model independent approach based on %metabolism and the fulfilment (or not) of the current regulatory dissolution criteria, ii) the so called ΑΒΓ system, a continuous version of the BCS, and iii) the so-called Extended Clearance Classification System (ECCS). ECCS uses clearance concepts (physicochemical properties and membrane permeability) to classify compounds and differentiates from BDDCS by bypassing the measure of solubility (based on the assumption that since it inter-correlates with lipophilicity, it is not directly relevant to clearance mechanisms or elimination).

On the unphysical hypotheses in pharmacokinetics and oral drug absorption: Time to utilize instantaneous rate coefficients instead of rate constants

This work aims to explore the unphysical assumptions associated with i) the homogeneity of the well mixed compartments of pharmacokinetics and ii) the diffusion limited model of drug dissolution. To this end, we i) tested the homogeneity hypothesis using Monte Carlo simulations for a reaction and a diffusional process that take place in Euclidean and fractal media, ii) re-considered the flip-flop kinetics assuming that the absorption rate for a one-compartment model is governed by an instantaneous rate coefficient instead of a rate constant, and, iii) re-considered the extent of drug absorption as a function of dose using an in vivo reaction limited model of drug dissolution with integer and non-integer stoichiometry values. We found that drug diffusional processes and reactions are slowed down in heterogeneous media and the environmental heterogeneity leads to increased fluctuations of the measurable quantities. Highly variable experimental literature data with measurements in intrathecal space and gastrointestinal fluids were explained accordingly. Next, by applying power law and Weibull input functions to a one-compartment model of disposition we show that the shape of concentration-time curves is highly dependent on the time exponent of the input functions. Realistic examples based on PK data of three compounds known to exhibit flip-flop kinetics are analyzed. The need to use time dependent coefficients instead of rate constants in PBPK modeling and virtual bioequivalence is underlined. Finally, the shape of the fraction absorbed as a function of dose plots, using an in vivo reaction limited model of drug dissolution were found to be dependent on the stoichiometry value and the solubility of drug. Ascending and descending limbs were observed for the higher stoichiometries (2.0 and 1.5) with the low solubility drug. In contrast, for the more soluble drug, a continuous increase of fraction absorbed as a function of dose is observed when the higher stoichiometries are used (2.0 and 1.5). For both drugs, the fraction absorbed for the lower values of stoichiometry (0.7 and 1.0) exhibit a non-dependency on dose profile. Our results give an insight into the complex picture of in vivo drug dissolution since diffusion-limited and reaction-limited processes seem to operate under in vivo conditions concurrently.

Integration of in vitro biorelevant dissolution and in silico PBPK model of carvedilol to predict bioequivalence of oral drug products

Bioequivalence implementation in developing countries where a high proportion of similar drug products are being marketed has found several obstacles, impeding regulatory agencies to move forward with this policy. Biopharmaceutical quality of these products, several of which are massively prescribed, remains unknown. In this context, an in vitro-in silico-in vivo approach is proposed as a mean to screen product performance and target specific formulations for bioequivalence assessment. By coupling in vitro biorelevant dissolution testing in USP-4 Apparatus (flow-through cell) with physiologically-based pharmacokinetic (PBPK) modeling in PK-Sim® software (Bayer, Germany), the performance of seven similar products of carvedilol tablets containing 25 mg available in the Uruguayan market were compared with the brand-name drug Dilatrend®. In silico simulations for Dilatrend® were compared with published results of bioequivalence studies performed in fasting conditions allowing model development through a learning and confirming process. Single-dose pharmacokinetic profiles were then simulated for the brand-name drug and two similar drug products selected according to in vitro observations, in a virtual Caucasian population of 1000 subjects (50% male, aged between 18 and 50 years with standard body-weights). Population bioequivalence ratios were estimated revealing that in vitro differences in drug release would have a major impact in carvedilol maximum plasma concentration, leading to a non-bioequivalence outcome. Predictions support the need to perform in vivo bioequivalence for these products of extensive use. Application of the in vitro-in silico-in vivo approach stands as an interesting alternative to tackle and reduce drug product variability in biopharmaceutical quality.

Predictive Performance of Physiologically Based Pharmacokinetic Models for the Effect of Food on Oral Drug Absorption: Current Status

A comprehensive search in literature and published US Food and Drug Administration reviews was conducted to assess whether physiologically based pharmacokinetic (PBPK) modeling could be prospectively used to predict clinical food effect on oral drug absorption. Among the 48 resulted food effect predictions, ∼50% were predicted within 1.25‐fold of observed, and 75% within 2‐fold. Dissolution rate and precipitation time were commonly optimized parameters when PBPK modeling was not able to capture the food effect. The current work presents a knowledgebase for documenting PBPK experience to predict food effect.

Prediction of a Therapeutic Dose for Buagafuran, a Potent Anxiolytic Agent by Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling Starting from Pharmacokinetics in Rats and Human

Physiologically based pharmacokinetic (PBPK)/pharmacodynamic (PD) models can contribute to animal-to-human extrapolation and therapeutic dose predictions. Buagafuran is a novel anxiolytic agent and phase I clinical trials of buagafuran have been completed. In this paper, a potentially effective dose for buagafuran of 30 mg t.i.d. in human was estimated based on the human brain concentration predicted by a PBPK/PD modeling. The software GastroPlus^TM was used to build the PBPK/PD model for buagafuran in rat which related the brain tissue concentrations of buagafuran and the times of animals entering the open arms in the pharmacological model of elevated plus-maze. Buagafuran concentrations in human plasma were fitted and brain tissue concentrations were predicted by using a human PBPK model in which the predicted plasma profiles were in good agreement with observations. The results provided supportive data for the rational use of buagafuran in clinic.

Integrating In Vitro, Modeling, and In Vivo Approaches to Investigate Warfarin Bioequivalence

We demonstrate the use of modeling and simulation to investigate bioequivalence (BE) concerns raised about generic warfarin products. To test the hypothesis that the loss of isopropyl alcohol and slow dissolution in acidic pH has significant impact on the pharmacokinetics of warfarin sodium tablets, we conducted physiologically based pharmacokinetic absorption modeling and simulation using formulation factors or in vitro dissolution profiles as input parameters. Sensitivity analyses indicated that warfarin pharmacokinetics was not sensitive to solubility, particle size, density, or dissolution rate in pH 4.5, but was affected by dissolution rate in pH 6.8 and potency. Virtual BE studies suggested that stressed warfarin sodium tablets with slow dissolution rate in pH 4.5 but having similar dissolution rate in pH 6.8 would be bioequivalent to the unstressed warfarin sodium tablets. A four‐way, crossover, single‐dose BE study in healthy subjects was conducted to test the same hypothesis and confirmed the simulation conclusion.

Mechanistic Oral Absorption Modeling and Simulation for Formulation Development and Bioequivalence Evaluation: Report of an FDA Public Workshop

On May 19, 2016, the US Food and Drug Administration (FDA) hosted a public workshop, entitled “Mechanistic Oral Absorption Modeling and Simulation for Formulation Development and Bioequivalence Evaluation.”1 The topic of mechanistic oral absorption modeling, which is one of the major applications of physiologically based pharmacokinetic (PBPK) modeling and simulation, focuses on predicting oral absorption by mechanistically integrating gastrointestinal transit, dissolution, and permeation processes, incorporating systems, active pharmaceutical ingredient (API), and the drug product information, into a systemic mathematical whole‐body framework.2

Physiologically Based Pharmacokinetic and Absorption Modeling for Osmotic Pump Products

Physiologically based pharmacokinetic (PBPK) and absorption modeling approaches were employed for oral extended-release (ER) drug products based on an osmotic drug delivery system (osmotic pumps). The purpose was to systemically evaluate the in vivo relevance of in vitro dissolution for this type of formulation. As expected, in vitro dissolution appeared to be generally predictive of in vivo PK profiles, because of the unique feature of this delivery system that the in vitro and in vivo release of osmotic pump drug products is less susceptible to surrounding environment in the gastrointestinal (GI) tract such as pH, hydrodynamic, and food effects. The present study considered BCS (Biopharmaceutics Classification System) class 1, 2, and 3 drug products with half-lives ranging from 2 to greater than 24 h. In some cases, the colonic absorption models needed to be adjusted to account for absorption in the colon. C _max (maximum plasma concentration) and AUCt (area under the concentration curve) of the studied drug products were sensitive to changes in colon permeability and segmental GI transit times in a drug product-dependent manner. While improvement of the methodology is still warranted for more precise prediction (e.g., colonic absorption and dynamic movement in the GI tract), the results from the present study further emphasized the advantage of using PBPK modeling in addressing product-specific questions arising from regulatory review and drug development.

Characterising Drug Release from Immediate-Release Formulations of a Poorly Soluble Compound, Basmisanil, Through Absorption Modelling and Dissolution Testing

The study aimed to characterise the mechanism of release and absorption of Basmisanil, a biopharmaceutics classification system (BCS) class 2 compound, from immediate-release formulations via mechanistic absorption modelling, dissolution testing, and Raman imaging. An oral absorption model was developed in GastroPlus® and verified with single-dose pharmacokinetic data in humans. The properties and drug release behaviour of different oral Basmisanil formulations were characterised via biorelevant dissolution and Raman imaging studies. Finally, an in vitro-in vivo correlation (IVIVC) model was developed using conventional and mechanistic deconvolution methods for comparison. The GastroPlus model accurately simulated oral Basmisanil exposure from tablets and granules formulations containing micronized drug. Absorption of oral doses below 200 mg was mostly dissolution rate-limited and thus particularly sensitive to formulation properties. Indeed, reduced exposure was observed for a 120-mg film-coated tablet and the slower dissolution rate measured in biorelevant media was attributed to differences in drug load. This hypothesis was confirmed when Raman imaging showed that the percolation threshold was exceeded in this formulation. This biorelevant dissolution method clearly differentiated between the formulations and was used to develop a robust IVIVC model. The study demonstrates the applicability and impact of mechanistic absorption modelling and biopharmaceutical in vitro tools for rational drug development.

Design and evaluation of an extended-release matrix tablet formulation; the combination of hypromellose acetate succinate and hydroxypropylcellulose

The purpose of this study was to develop an extended-release (ER) matrix tablet that shows robust dissolution properties able to account for the variability of pH and mechanical stress in the GI tract using a combination of enteric polymer and hydrophilic polymer. Hypromellose acetate succinate (HPMCAS) and hydroxypropylcellulose (HPC) were selected as ER polymers for the ER matrix tablet (HPMCAS/HPC ER matrix tablet). Oxycodone hydrochloride was employed as a model drug. Dissolution properties of the HPMCAS/HPC ER matrix tablets were evaluated and were not affected by the pH of the test medium or paddle rotating speed. In a USP apparatus 3 (bio-relevant dissolution method), dissolution profiles of the HPMCAS/HPC ER matrix tablets containing oxycodone hydrochloride were similar to that of the reference product (OxyContin). Moreover, in vivo performance after oral administration of the HPMCAS/HPC ER matrix tablets to humans was simulated by GastroPlus based on dissolution profiles from the USP apparatus 3. The plasma concentration-time profile simulated was similar to that of the reference product. These results suggest that the combination of HPMCAS and HPC shows a robust dissolution profile against pH and paddle rotating speed and indicates the appropriate extended-release profile in humans.

Scientific and Regulatory Considerations in Solid Oral Modified Release Drug Product Development

This review presents scientific and regulatory considerations for the development of solid oral modified release (MR) drug products. It includes a rationale for patient-focused development based on Quality-by-Design (QbD) principles. Product and process understanding of MR products includes identification and risk-based evaluation of critical material attributes (CMAs), critical process parameters (CPPs), and their impact on critical quality attributes (CQAs) that affect the clinical performance. The use of various biopharmaceutics tools that link the CQAs to a predictable and reproducible clinical performance for patient benefit is emphasized. Product and process understanding lead to a more comprehensive control strategy that can maintain product quality through the shelf life and the lifecycle of the drug product. The overall goal is to develop MR products that consistently meet the clinical objectives while mitigating the risks to patients by reducing the probability and increasing the detectability of CQA failures.

Physiologically Based Absorption Modeling to Design Extended-Release Clinical Products for an Ester Prodrug

Absorption modeling has demonstrated its great value in modern drug product development due to its utility in understanding and predicting in vivo performance. In this case, we integrated physiologically based modeling in the development processes to effectively design extended-release (ER) clinical products for an ester prodrug LY545694. By simulating the trial results of immediate-release products, we delineated complex pharmacokinetics due to prodrug conversion and established an absorption model to describe the clinical observations. This model suggested the prodrug has optimal biopharmaceutical properties to warrant developing an ER product. Subsequently, we incorporated release profiles of prototype ER tablets into the absorption model to simulate the in vivo performance of these products observed in an exploratory trial. The models suggested that the absorption of these ER tablets was lower than the IR products because the extended release from the formulations prevented the drug from taking advantage of the optimal absorption window. Using these models, we formed a strategy to optimize the ER product to minimize the impact of the absorption window limitation. Accurate prediction of the performance of these optimized products by modeling was confirmed in a third clinical trial.