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

Integration of Biorelevant Pediatric Dissolution Methodology into PBPK Modeling to Predict In Vivo Performance and Bioequivalence of Generic Drugs in Pediatric Populations: a Carbamazepine Case Study

This study investigated the impact of gastro-intestinal fluid volume and bile salt (BS) concentration on the dissolution of carbamazepine (CBZ) immediate release (IR) 100 mg tablets and to integrate these in vitro biorelevant dissolution profiles into physiologically based pharmacokinetic modelling (PBPK) in pediatric and adult populations to determine the biopredictive dissolution profile. Dissolution profiles of CBZ IR tablets (100 mg) were generated in 50-900 mL biorelevant adult fasted state simulated gastric and intestinal fluid (Ad-FaSSGF and Ad-FaSSIF), also in three alternative compositions of biorelevant pediatric FaSSGF and FaSSIF medias at 200 mL. This study found that CBZ dissolution was poorly sensitive to changes in the composition of the biorelevant media, where dissimilar dissolution (F2 = 46.2) was only observed when the BS concentration was changed from 3000 to 89 μM (Ad-FaSSIF vs Ped-FaSSIF 50% 14 BS). PBPK modeling demonstrated the most predictive dissolution volume and media composition to forecast the PK was 500 mL of Ad-FaSSGF/Ad-FaSSIF media for adults and 200 mL Ped-FaSSGF/FaSSIF media for pediatrics. A virtual bioequivalence simulation was conducted by using Ad-FaSSGF and/or Ad-FaSSIF 500 mL or Ped-FaSSGF and/or Ped-FaSSIF 200 mL dissolution data for CBZ 100 mg (reference and generic test) IR product. The CBZ PBPK models showed bioequivalence of the product. This study demonstrates that the integration of biorelevant dissolution data can predict the PK profile of a poorly soluble drug in both populations. Further work using more pediatric drug products is needed to verify biorelevant dissolution data to predict the in vivo performance in pediatrics.

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1-4 by Virtual Bioequivalence Model

To evaluate the influence of solubility and permeability on the pharmacokinetic prediction performance of orally administered drugs using avirtual bioequivalence (VBE) model, a total of 23 orally administered drugs covering Biopharmaceutics Classification System (BCS) classes 1-4 were selected. A VBE model (i.e., a physiologically based pharmacokinetic model integrated with dissolution data) based on a B²O simulator was applied for pharmacokinetic (PK) prediction in a virtual population. Parameter sensitivity analysis was used for input parameter selection. The predictive performances of PK parameters (i.e., AUC_0-t, C_max, and T_max), PK profiles, and bioequivalence (BE) results were evaluated using the twofold error, average fold error (AFE), absolute average fold error (AAFE), and BE reassessment metrics. All models successfully simulated the mean PK profiles, with AAFE < 2 and AFE ranging from 0.58 to 1.66. As for the PK parameters, except for the time of peak concentration, T_max, of isosorbide mononitrate, other simulated PK parameters were all within a twofold error. The simulated PK behaviors were comparable to the observed ones, both for test (T) and reference (R) products, and the simulated T/R arithmetic mean ratios were all within 0.88-1.16 of the observed values. These four evaluation metrics were distributed equally among BCS class 1-4 drugs. The VBE model showed powerful performance to predict the PK behavior of orally administered drugs with various combinations of solubility and permeability, irrespective of the BCS category.

Modeling of In Vitro Dissolution Profiles of Carvedilol Immediate-Release Tablets in Different Dissolution Media

Quantitative evaluation of drug dissolution characteristics based on mathematical models is essential to understand and predict a particular drug release profile. In this study, model-dependent evaluation of the dissolution kinetics of reference and five test products (25-mg, immediate-release (IR) tablets) of an antihypertensive drug, carvedilol, was carried out using the DDSolver^® program. The effects of pH (pH 1.2, 4.5, and 6.8) and various media with/without 0.5% (w/v) anionic, cationic, and nonionic surfactants (sodium lauryl sulfate (SLS), hexadecyltrimethylammonium bromide (CTAB), and polysorbate 80) on the dissolution kinetics of the bioequivalent IR products of carvedilol were investigated. The Weibull-1 model was fitted successfully to the dissolution data of all products at pH 1.2 and pH 4.5, as well as in the pH 6.8 medium with CTAB according to the model goodness of fit (r² = 0.981-0.999, AIC = 14.5-42.6, MSC = 1.99-5.25). Model fitting produced good fits to Gompertz-1 for all products at pH 6.8 without a surfactant (r² = 0.975-0.998, AIC = 28.3-55, MSC = 2.53-5.82). For pH 6.8 media containing SLS or polysorbate 80, Logistic-2 was fitted successfully to the dissolution data of all products (r² = 0.974-0.999, AIC = 20.9-52.1, MSC = 1.90-5.69). Overall, the model-dependent analysis of in vitro dissolution data indicated in vitro equivalence of the reference and test products of carvedilol in each medium in terms of kinetic models, suggesting that it would have an important role in developing generic drug products of the BCS class II drug carvedilol.

Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives

Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for rationalizing drug interactions with their pharmacological targets. Despite the obvious utility and increasing impact of computational approaches, their development is not progressing at the same speed in different fields of pharmacology. Here, we review current in silico techniques used in cardiovascular diseases (CVDs), cardiological drug discovery, and assessment of cardiotoxicity. In silico techniques are paving the way to a new era in cardiovascular medicine, but their use somewhat lags behind that in other fields.

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.

In silico prediction of bioequivalence of Isosorbide Mononitrate tablets with different dissolution profiles using PBPK modeling and simulation

AIM

The waiver of bioequivalence (BE) studies is well accepted for Biopharmaceutics Classification System (BCS) class I drugs in form of immediate-release solid oral products. This study aimed to assess whether the rapid dissolution profiles (≥85% in 30 min) was crucial to guarantee bioequivalence of isosorbide mononitrate (ISMN) and then established a clinically relevant dissolution specification (CRDS) for screening BE or non-BE batches.

METHOD

A physiologically based pharmacokinetic (PBPK) model was constructed by integrating clinical and non-clinical data by B²O simulator. The model was verified by an actual clinical study (NMPA registration number: CTR20191360) with 28 healthy Chinese subjects. Then a virtual BE study was simulated to evaluate the bioequivalence of 7 virtual batches of ISMN tablets with different dissolution profiles, and the CRDS was established by integrating the results.

RESULT

The simulated PK behavior of ISMN was comparable to the observed. Even though the batches with slower dissolution were not equivalent to a rapid dissolution profile (≥85% in 30 min), it was demonstrated these batches would exhibit the similar in vivo performance. Meanwhile, the in vitro dissolution specification time point and the percentage of drug release (75% in 45 min) proved to have clinical relevance.

CONCLUSION

The virtual BE simulation by integrating in vitro dissolution profiles into the PBPK model provided a powerful tool for screening formulations, contributing to gaining time and reducing costs in BE evaluations.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing

Purpose: To review in vitro testing and simulation platforms that are in current use to predict in vivo performances of generic products as well as other situations to provide evidence for biowaiver and support drug formulations development. Methods: Pubmed and Google Scholar databases were used to review published literature over the past 10 years. The terms used were “simulation AND bioequivalence” and “modeling AND bioequivalence” in the title field of databases, followed by screening, and then reviewing. Results: A total of 22 research papers were reviewed. Computer simulation using software such as GastroPlus™, PK-Sim^® and SimCyp^® find applications in drug modeling. Considering the wide use of optimization for in silico predictions to fit observed data, a careful review of publications is required to validate the reliability of these platforms. For immediate release (IR) drug products belonging to the Biopharmaceutics Classification System (BCS) classes I and III, difference factor (ƒ₁) and similarity factor (ƒ₂) are calculated from the in vitro dissolution data of drug formulations to support biowaiver; however, this method can be more discriminatory and may not be useful for all dissolution profiles. Conclusions: Computer simulation platforms need to improve their mechanistic physiologically based pharmacokinetic (PBPK) modeling, and if prospectively validated within a small percentage of error from the observed clinical data, they can be valuable tools in bioequivalence (BE) testing and formulation development.

Power of the Dissolution Test in Distinguishing a Change in Dosage Form Critical Quality Attributes

For a dissolution method to be considered relevant to in vivo performance, the dissolution data profiles should show discrimination or meaningful change when there is a change in critical material attributes (CMAs) and critical product properties (CPPs). The dissolution test has been shown repeatedly to have the power to distinguish between significant changes in active pharmaceutical ingredient (API), formulation, and process that relate to the release mechanism of the in vivo performance. Examples will be discussed in the literature where the effects of formulation, drug substance, and manufacturing variables have been measured by dissolution testing. There will be a suggested plan on how to develop and challenge a discriminating method that may be utilized for regulatory purposes. A brief review of other challenges and considerations regarding discriminatory dissolution testing is presented.