Use of Physiologically Based Pharmacokinetic Models Coupled with Pharmacodynamic Models to Assess the Clinical Relevance of Current Bioequivalence Criteria for Generic Drug Products Containing Ibuprofen

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

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

Comparison of intravenous ibuprofen pharmacokinetics between Caucasian and Chinese populations using physiologically based pharmacokinetics modeling and simulation

BACKGROUND

Intravenous ibuprofen, a nonsteroidal anti-inflammatory drug, is widely used as an antipyretic and analgesic in adults and children. This study was designed to evaluate ethnic differences by comparing the pharmacokinetics of intravenous ibuprofen in Caucasian and Chinese populations using physiologically based pharmacokinetics (PBPK) modeling and simulation.

METHODS

A PBPK model for intravenous ibuprofen was developed in adults and children utilizing the Simcyp Simulator. The model was tested and verified against published literature and unpublished data obtained from the Caucasian adult population, Caucasian pediatric population and Chinese adult population.

RESULTS

The developed PBPK model could adequately pilot the pharmacokinetics of intravenous ibuprofen, and the major observed values were within the 90% prediction interval in both adults and children. Both folding errors of the maximum peak concentration (Cmax) and area under the concentration-time curve (AUC) were 1.5-fold less in the Caucasian and Chinese populations. In addition, no significant differences in weight-normalized Cmax and AUC were observed between the Caucasian and Chinese adult populations. Moreover, there were no obvious pharmacokinetic differences between the Caucasian and Chinese pediatric populations with intravenous infusion (10 minutes) of 10 mg/kg by age group.

CONCLUSION

This study indicates that the pharmacokinetic profile and the parameters of intravenous ibuprofen are analogous in Caucasian and Chinese populations, either adults or children. In addition, this study provides effective evidence that the dosing scheme of intravenous ibuprofen in Chinese children can remain the same as the regimen that the original company (Caldolor®) provided.

Acalabrutinib Maleate Tablets: The Physiologically Based Biopharmaceutics Model behind the Drug Product Dissolution Specification

Acalabrutinib maleate tablets correspond to an improved formulation compared to acalabrutinib capsules as they can be dosed with and without acid reducing agents and therefore benefit more cancer patients. The dissolution specification for the drug product was determined using all the information available on the drug safety, efficacy, and in vitro performance. In addition, a physiologically based biopharmaceutics model was developed for acalabrutinib maleate tablets on the back of a previously published model for acalabrutinib capsules to establish that the proposed drug product dissolution specification would ensure safe and effective products for all patients including those under acid reducing agent treatment. The model was built, validated, and used to predict the exposure of virtual batches where the dissolution was slower than that of the clinical target. A combination of exposure prediction and the use of a PK-PD model allowed it to be demonstrated that the proposed drug product dissolution specification was acceptable. This combination of models enabled a larger safe space than would have been granted by consideration of bioequivalence only.

Another Step Toward Qualification of Pediatric Physiologically Based Pharmacokinetic Models to Facilitate Inclusivity and Diversity in Pediatric Clinical Studies

Robust prediction of pharmacokinetics (PKs) in pediatric subjects of diverse ages, ethnicities, and morbidities is critical. Qualification of pediatric physiologically-based pharmacokinetic (P-PBPK) models is an essential step toward enabling precision dosing of these vulnerable groups. Twenty-two manuscripts involving P-PBPK predictions and corresponding observed PK data (e.g., area under the curve and clearance) for 22 small-molecule compounds metabolized by CYP (3A4, 1A2, and 2C9), UGT (1A9 and 2B7), FMO3, renal, non-renal, and complex routes were identified; ratios of mean predicted/observed (P/O) PK parameters were calculated. Seventy-eight of 115 mean predicted PK parameters were within 0.8 to 1.25-fold of observed data, 98 within 0.67 to 1.5-fold, 109 within 2-fold, and only 6 P/O ratios were outside of these bounds. A set of 12 CYP3A4-metabolized compounds and a set of 6 metabolized by other enzymes, CYP1A2 (1 compound), CYP2C9 (2 compounds), UGT1A9 (1 compound) and UGT2B7 (2 compounds) had 56 of 59 and 22 of 25 mean P/O ratios, respectively, that fell within the > 0.5 and < 2.0-fold boundaries. For compounds covering renal, non-renal, complex, and FM03 routes of elimination, 29 of 31 mean P/O ratios fell within the 0.67 to 1.5-fold bounds, including 4 of 5 P/O ratios from newborns. P-PBPK modeling and simulation is a strategic component of the complement of precision dosing methods and has a vital role to play in dose adjustment in vulnerable pediatric populations, such as those with disease or in different ethnic groups. Qualification of such models is an essential step toward acceptance of this methodology by regulators.

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.

In Vitro-In Vivo Extrapolation by Physiologically Based Kinetic Modeling: Experience With Three Case Studies and Lessons Learned

Physiologically based kinetic (PBK) modeling has been increasingly used since the beginning of the 21st century to support dose selection to be used in preclinical and clinical safety studies in the pharmaceutical sector. For chemical safety assessment, the use of PBK has also found interest, however, to a smaller extent, although an internationally agreed document was published already in 2010 (IPCS/WHO), but at that time, PBK modeling was based mostly on in vivo data as the example in the IPCS/WHO document indicates. Recently, the OECD has published a guidance document which set standards on how to characterize, validate, and report PBK models for regulatory purposes. In the past few years, we gained experience on using in vitro data for performing quantitative in vitro–in vivo extrapolation (QIVIVE), in which biokinetic data play a crucial role to obtain a realistic estimation of human exposure. In addition, pharmaco-/toxicodynamic aspects have been introduced into the approach. Here, three examples with different drugs/chemicals are described, in which different approaches have been applied. The lessons we learned from the exercise are as follows: 1) in vitro conditions should be considered and compared to the in vivo situation, particularly for protein binding; 2) in vitro inhibition of metabolizing enzymes by the formed metabolites should be taken into consideration; and 3) it is important to extrapolate from the in vitro measured intracellular concentration and not from the nominal concentration to the tissue/organ concentration to come up with an appropriate QIVIVE for the relevant adverse effects.

Level A IVIVC for immediate release tablets confirms in vivo predictive dissolution testing for ibuprofen

A bioequivalence study comparing two fixed dose combination tablets containing 200 mg ibuprofen and 30 mg pseudoephedrine hydrochloride showed bioequivalence for pseudoephedrine AUC and C_max, but the reference product showed higher C_max than the test product in fasted conditions. The main difference between products was the presence of tribasic calcium phosphate in the reference tablet, resulting in an increased surface pH of the dissolving ibuprofen particles under gastric and intestinal conditions and, consequently, higher solubility of ibuprofen. A mechanistic model based on mass balance and ionization equilibria was used to calculate the pH of the particle surface under different buffer conditions. The discrepancies in surface pH between test and reference tablet were pronounced in 0.1 M and 0.01 M hydrochloric acid and in diluted maleate 7 mM pH 6.5 and phosphate 5 mM pH 6.7 buffers (but negligible in compendial phosphate buffer pH 6.8. Only those dissolution tests using pre-treatment in acidic conditions could be used to build a one-step in vitro-in vivo correlation (IVIVC). This work shows the potential of these discriminatory and in vivo predictive dissolution methods to obtain IVIVCs for BCS class IIa drugs and for extending BCS biowaivers to BCS class IIa drugs.

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.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Support Waivers of In Vivo Clinical Studies: Current Status, Challenges, and Opportunities

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has been extensively applied to quantitatively translate in vitro data, predict the in vivo performance, and ultimately support waivers of in vivo clinical studies. In the area of biopharmaceutics and within the context of model-informed drug discovery and development (MID3), there is a rapidly growing interest in applying verified and validated mechanistic PBPK models to waive in vivo clinical studies. However, the regulatory acceptance of PBPK analyses for biopharmaceutics and oral drug absorption applications, which is also referred to variously as "PBPK absorption modeling" [Zhang et al. CPT: Pharmacometrics Syst. Pharmacol. 2017, 6, 492], "physiologically based absorption modeling", or "physiologically based biopharmaceutics modeling" (PBBM), remains rather low [Kesisoglou et al. J. Pharm. Sci. 2016, 105, 2723] [Heimbach et al. AAPS J. 2019, 21, 29]. Despite considerable progress in the understanding of gastrointestinal (GI) physiology, in vitro biopharmaceutic and in silico tools, PBPK models for oral absorption often suffer from an incomplete understanding of the physiology, overparameterization, and insufficient model validation and/or platform verification, all of which can represent limitations to their translatability and predictive performance. The complex interactions of drug substances and (bioenabling) formulations with the highly dynamic and heterogeneous environment of the GI tract in different age, ethnic, and genetic groups as well as disease states have not been yet fully elucidated, and they deserve further research. Along with advancements in the understanding of GI physiology and refinement of current or development of fully mechanistic in silico tools, we strongly believe that harmonization, interdisciplinary interaction, and enhancement of the translational link between in vitro, in silico, and in vivo will determine the future of PBBM. This Perspective provides an overview of the current status of PBBM, reflects on challenges and knowledge gaps, and discusses future opportunities around PBPK/PD models for oral absorption of small and large molecules to waive in vivo clinical studies.

Assessing the impact of cystic fibrosis on the antipyretic response of ibuprofen in children: Physiologically-based modeling as a candle in the dark

AIM

The goal of this study is to present the utility of quantitative modelling for extrapolation of drug safety and efficacy to underrepresented populations in controlled clinical trials. To illustrate this, the stepwise development of an integrated disease/pharmacokinetics/pharmacodynamics model of antipyretic efficacy of ibuprofen in children with cystic fibrosis (CF) is presented along with therapy optimization suggestions.

METHOD

Published clinical trials, in vitro data, and drug physiochemical properties were used to develop an ibuprofen-mediated antipyresis model for febrile children also having CF. Workflow included first developing a mechanistic absorption model using in vitro-in vivo extrapolation followed by physiologically-based pharmacokinetic (PBPK) modelling. The verified PBPK model was then scaled to paediatric patients with CF. Once verified, the PBPK model was linked to an indirect response model of antipyresis for simulation of the overall antipyretic efficacy of ibuprofen in CF children.

RESULTS

Model simulations showed therapeutic inequivalence between healthy children and paediatric patients with CF; C_max and AUC decreased by 39% (32-46%) and 44% (36-52%), respectively, in patients. Further, and in agreement with literature reports, predicted pharmacodynamics time courses suggest a slower onset and faster offset of action in patients compared to healthy children, 30 and 60 minutes, respectively. Exploratory simulations suggest an increase in dosing frequency for CF children as a better therapeutic strategy.

CONCLUSION

Model-informed approaches to leveraging knowledge obtained throughout the life cycle of drug development may play a key role in extrapolating drug efficacy and safety to underrepresented populations.

Application of the relationship between pharmacokinetics and pharmacodynamics in drug development and therapeutic equivalence: a PEARRL review

Objectives

The objective of this review was to provide an overview of pharmacokinetic/pharmacodynamic (PK/PD) models, focusing on drug-specific PK/PD models and highlighting their value added in drug development and regulatory decision-making.

Key findings

Many PK/PD models, with varying degrees of complexity and physiological understanding have been developed to evaluate the safety and efficacy of drug products. In special populations (e.g. paediatrics), in cases where there is genetic polymorphism and in other instances where therapeutic outcomes are not well described solely by PK metrics, the implementation of PK/PD models is crucial to assure the desired clinical outcome. Since dissociation between the pharmacokinetic and pharmacodynamic profiles is often observed, it is proposed that physiologically based pharmacokinetic and PK/PD models be given more weight by regulatory authorities when assessing the therapeutic equivalence of drug products.

Summary

Modelling and simulation approaches already play an important role in drug development. While slowly moving away from ‘one-size fits all’ PK methodologies to assess therapeutic outcomes, further work is required to increase confidence in PK/PD models in translatability and prediction of various clinical scenarios to encourage more widespread implementation in regulatory decision-making.

Dissolution Methods to Increasing Discriminatory Power of In Vitro Dissolution Testing for Ibuprofen Free Acid and Its Salts

The predictive capacity of in vitro dissolution tests using the Biopharmaceutics Classification System (BCS)-based experimental setup to anticipate in vivo bioequivalence outcomes for BCS class 2 weak acids has been questioned. In this work, the effect of buffer concentration media was investigated as a possible approach to ensuring the discriminative capacity of the in vitro dissolution methods. The case example used to test this approach was ibuprofen, formulated as either the free acid or in various salt forms. By matching the concentration of buffers commonly used to prepare media which aim to simulate the intestinal conditions with that of bicarbonate buffer, which is the predominant buffer species in vivo, to arrive at the same surface pH (pH₀), the discriminative power of the in vitro dissolution tests was improved. To simulate the in vivo results even better, a pretreatment at acidic pH was added to the dissolution test simulating the gastric conditions to create a 2-stage test. With the 2-stage test, it was possible to account for differences in disintegration in a more physiologically relevant way and thus to better reflect the in vivo performance of the various formulations.

Can dosage form-dependent food effects be predicted using biorelevant dissolution tests? Case example extended release nifedipine

AIMS

Food intake is known to have various effects on gastrointestinal luminal conditions in terms of transit times, hydrodynamic forces and/or luminal fluid composition and can therefore affect the dissolution behavior of solid oral dosage forms. The aim of this study was to investigate and detect the dosage form-dependent food effect that has been observed for two extended-release formulations of nifedipine using in vitro dissolution tests.

METHODS

Two monolithic extended release formulations, the osmotic pump Adalat® XL 60mg and matrix-type Adalat® Eins 30mg formulation, were investigated with biorelevant dissolution methods using the USP apparatus III and IV under both simulated prandial states, and their corresponding quality control dissolution method. In vitro data were compared to published and unpublished in vivo data using deconvolution-based in vitro - in vivo correlation (IVIVC) approaches.

RESULTS

Quality control dissolution methods tended to overestimate the dissolution rate due to the excessive solubilizing capabilities of the sodium dodecyl sulfate (SDS)-containing dissolution media. Using Level II biorelevant media the dosage form dependent food effect for nifedipine was described well when studied with the USP apparatus III, whereas the USP apparatus IV failed to detect the positive food effect for the matrix-type dosage form.

CONCLUSIONS

It was demonstrated that biorelevant methods can serve as a useful tool during formulation development as they were able to qualitatively reflect the in vivo data.

In vitro assays in natural products research - a matter of concentration and relevance to in vivo administration using resveratrol, α-mangostin/γ-mangostin and xanthohumol as examples

Herbal or botanical dietary supplements are an ever increasingly popular category of products in the United States and around the world. In vitro data can provide meaningful insight into the potential target and mechanism of action for a proposed active compound but may also be misused to promote a supplement to consumers with unverified health claims. In vitro data need to be considered alongside pharmacokinetic and pharmacodynamic data in preclinical animal and clinical human trials. While considerable activity of compounds and extracts in vitro may lead to further testing in vivo, in many instances, concentrations tested in cell lines or isolated targets are not achievable at the target site in vivo. Thus, whether the in vitro data are relevant to humans after oral administration is questionable. This review will discuss this discrepancy using in vitro and in vivo data of resveratrol, xanthones (α-mangostin and γ-mangostin) and xanthohumol.

Recent Advances in Development and Application of Physiologically-Based Pharmacokinetic (PBPK) Models: a Transition from Academic Curiosity to Regulatory Acceptance

There is a renewed surge of interest in applications of physiologically-based pharmacokinetic (PBPK) models by the pharmaceutical industry and regulatory agencies. Developing PBPK models within a systems pharmacology context allows separation of the parameters pertaining to the animal or human body (the system) from that of the drug and the study design which is essential to develop generic drug-independent models used to extrapolate PK/PD properties in various healthy and patient populations. This has expanded the classical paradigm to a ‘predict-learn-confirm-apply’ concept. Recently, a number of drug labels are informed by simulation results generated using PBPK models. These cases show that either the simulations are used in lieu of conducting clinical studies or have informed the drug label that otherwise would have been silent in some specific situations. It will not be surprising to see applications of these models in implementing precision dosing at the point of care in the near future.

A paradigm shift in pharmacokinetic-pharmacodynamic (PKPD) modeling: rule of thumb for estimating free drug level in tissue compared with plasma to guide drug design

A basic assumption in pharmacokinetics-pharmacodynamics research is that the free drug concentration is similar in plasma and tissue, and, hence, in vitro plasma data can be used to estimate the in vivo condition in tissue. However, in a companion manuscript, it has been demonstrated that this assumption is violated for the ionized drugs. Nonetheless, these observations focus on in vitro static environments and do not challenge data with an in vivo dynamic system. Therefore, an extension from an in vitro to an in vivo system becomes the necessary next step. The objective of this study was to perform theoretical simulations of the free drug concentration in tissue and plasma by using a physiologically based pharmacokinetics (PBPK) model reproducing the in vivo conditions in human. Therefore, the effects of drug ionization, lipophilicity, and clearance have been taken into account in a dynamic system. This modeling exercise was performed as a proof of concept to demonstrate that free drug concentration in tissue and plasma may also differ in a dynamic system for passively permeable drugs that are ionized at the physiological pH. The PBPK model simulations indicated that free drug concentrations in tissue cells and plasma significantly differ for the ionized drugs because of the pH gradient effect between cells and interstitial space. Hence, a rule of thumb for potentially performing more accurate PBPK/PD modeling is suggested, which states that the free drug concentration in tissue and plasma will differ for the ionizable drugs in contrast to the neutral drugs. In addition to the pH gradient effect for the ionizable drugs, lipophilicity and clearance effects will increase or decrease the free drug concentration in tissue and plasma for each class of drugs; thus, higher will be the drug lipophilicity and clearance, lower would be the free drug concentration in plasma, and, hence, in tissue, in a dynamic in vivo system. Therefore, only considering the value of free fraction in plasma derived from a static in vitro environment might be biased to guide drug design (the old paradigm), and, hence, it is recommended to use a PBPK model to reproduce more accurately the in vivo condition in tissue (the new paradigm). This newly developed approach can be used to predict free drug concentration in diverse tissue compartments for small molecules in toxicology and pharmacology studies, which can be leveraged to optimize the pharmacokinetics drivers of tissue distribution based upon physicochemical and physiological input parameters in an attempt to optimize free drug level in tissue. Overall, this present study provides guidance on the application of plasma and tissue concentration information in PBPK/PD research in preclinical and clinical studies, which is in accordance with the recent literature.