Virtual population pharmacokinetic using physiologically based pharmacokinetic model for evaluating bioequivalence of oral lacidipine formulations in dogs

Formulation Strategy of BCS-II Drugs by Coupling Mechanistic In-Vitro and Nonclinical In-Vivo Data with PBPK: Fundamentals of Absorption-Dissolution to Parameterization of Modelling and Simulation

BCS class II candidates pose challenges in drug development due to their low solubility and permeability. Researchers have explored various techniques; co-amorphous and solid dispersion are major approaches to enhance in-vitro drug solubility and dissolution. However, in-vivo oral bioavailability remains challenging. Physiologically based pharmacokinetic (PBPK) modeling with a detailed understanding of drug absorption, distribution, metabolism, and excretion (ADME) using a mechanistic approach is emerging. This review summarizes the fundamentals of the PBPK, dissolution-absorption models, parameterization of oral absorption for BCS class II drugs, and provides information about newly emerging artificial intelligence/machine learning (AI/ML) linked PBPK approaches with their advantages, disadvantages, challenges and areas of further exploration. Additionally, the fully integrated workflow for formulation design for investigational new drugs (INDs) and virtual bioequivalence for generic molecules falling under BCS-II are discussed.

Evaluating the bioequivalence of two pitavastatin calcium formulations based on IVIVC modeling and clinical study

In vitro-in vivo correlation (IVIVC) allows prediction of the in vivo performance of a pharmaceutical product based on its in vitro drug release profiles and can be used to reduce the number of bioequivalence (BE) studies during product development, and facilitate certain regulatory decisions. Here, we developed an IVIVC model for pitavastatin calcium, a basic Biopharmaceutics Classification System (BCS) II lipid-lowering drug, which was then used to predict the BE outcome of formulations manufactured at two manufacturers. In addition, virtual trials using the IVIVC model using pH 4.0 acetate buffer dissolution showed similarity in areas under the curves and maximum plasma concentration (Cmax ) for test and reference tablets under fasting condition. These predicted results were verified in definitive BE study. In conclusion, we demonstrated that for certain BCS II molecules, IVIVC modeling could be used as a priori to predict the BE outcome.

Enhancing Atorvastatin In Vivo Oral Bioavailability in the Presence of Inflammatory Bowel Disease and Irritable Bowel Syndrome Using Supercritical Fluid Technology Guided by wbPBPK Modeling in Rat and Human

Inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) are common disorders that can change the body's physiology and drugs pharmacokinetics. Solid dispersion (SD) preparation using supercritical fluid technology (SFT) has many advantages. Our study aimed to explore the effect of IBS and IBD on atorvastatin (ATV) pharmacokinetics, enhance ATV oral bioavailability (BCS II drug) using SFT, and analyze drug-disease-formulation interaction using a whole-body physiologically based pharmacokinetic (wbPBPK) model in rat and human. A novel ATV formulation was prepared using SFT and characterized in vitro and in vivo in healthy, IBS, and IBD rats. The resulting ATV plasma levels were analyzed using a combination of conventional and wbPBPK approaches. The novel formulation increased ATV solubility by 20-fold and resulted in a zero-order release of up to 95%. Both IBS and IBD increased ATV exposure after oral and intravenous administration by more than 30%. The novel SFT formulation increased ATV bioavailability by 28, 14, and 18% in control, IBD, and IBD rat groups and resulted in more consistent exposure as compared to raw ATV solution. Higher improvements in ATV bioavailability of more than 2-fold upon receiving the novel SFT formulation were predicted by the human wbPBPK model as compared to receiving the conventional tablets. Finally, the established wbPBPK model could describe ATV ADME in the presence of IBS and IBD after oral administration of raw ATV and using the novel SFT formula and can help scale the optimized ATV dosing regimens in the presence of IBS and IBD from rats to humans.

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.

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.

Accelerated Repurposing and Drug Development of Pulmonary Hypertension Therapies for COVID-19 Treatment Using an AI-Integrated Biosimulation Platform

The COVID-19 pandemic has reached over 100 million worldwide. Due to the multi-targeted nature of the virus, it is clear that drugs providing anti-COVID-19 effects need to be developed at an accelerated rate, and a combinatorial approach may stand to be more successful than a single drug therapy. Among several targets and pathways that are under investigation, the renin-angiotensin system (RAS) and specifically angiotensin-converting enzyme (ACE), and Ca²⁺-mediated SARS-CoV-2 cellular entry and replication are noteworthy. A combination of ACE inhibitors and calcium channel blockers (CCBs), a critical line of therapy for pulmonary hypertension, has shown therapeutic relevance in COVID-19 when investigated independently. To that end, we conducted in silico modeling using BIOiSIM, an AI-integrated mechanistic modeling platform by utilizing known preclinical in vitro and in vivo datasets to accurately simulate systemic therapy disposition and site-of-action penetration of the CCBs and ACEi compounds to tissues implicated in COVID-19 pathogenesis.

An integrated computational methodology with data-driven machine learning, molecular modeling and PBPK modeling to accelerate solid dispersion formulation design

Drugs in solid dispersion (SD) take advantage of fast and extended dissolution, thus attains a higher bioavailability than the crystal form. However, current development of SD relies on a random large-scale formulation screening method with low efficiency. Current research aims to integrate various computational tools, including machine learning (ML), molecular dynamic (MD) simulation and physiologically based pharmacokinetic (PBPK) modeling, to accelerate the development of SD formulations. Firstly, based on a dataset consisting of 674 dissolution profiles of SD, the random forest algorithm was used to construct a classification model to distinguish two types of dissolution profiles: "spring-and-parachute" and "maintain supersaturation", and a regression model to predict the time-dependent dissolution profiles. Both of the two prediction models showed good prediction performance. Moreover, feature importance was performed to help understand the key information that contributes to the model. After that, the vemurafenib (VEM) SD formulation in previous report was used as an example to validate the models. MD simulation was used to investigate the dissolution behavior of two SD formulations with two polymers (HPMCAS and Eudragit) at the molecular level. The results showed that the HPMCAS-based formulation resulted in faster dissolution than the Eudragit formulation, which agreed with the reported experimental results. Finally, a PBPK model was constructed to accurately predict the human pharmacokinetic profile of the VEM-HPMCAS SD formulation. In conclusion, combined computational tools have been developed to in silico predict formulation composition, in vitro release and in vivo absorption behavior of SD formulations. The integrated computational methodology will significantly facilitate pharmaceutical formulation development than the traditional trial-and-error approach in the laboratory.

Co-amorphous solid dispersion systems of lacidipine-spironolactone with improved dissolution rate and enhanced physical stability

Co-amorphous solid dispersion (C-ASD) systems have attracted great attention to improve the solubility of poorly soluble drugs, but the selection of an appropriate stabilizer to stabilize amorphous forms is still a huge challenge. Herein, C-ASD system of two clinical combined used drugs (lacidipine (LCDP) and spironolactone (SPL)) as stabilizers to each other, was prepared by solvent evaporation method. The effects of variation in molar ratio of LCDP and SPL (3:1, 1:1, 1:3, 1:6, and 1:9) on the drug release characteristics were explored. Polarized light microscopy (PLM), powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were employed to evaluate the solid states. Prepared C-ASDs were further studied for their stability under the high humidity (RH 92.5%). Further analysis of C-ASDs via Fourier-transform infrared spectroscopy (FTIR) and Raman spectroscopy confirmed that hydrogen bond interactions between the two drugs played a significant role in maintaining the stability of the C-ASDs systems. Moreover, molecular dynamic (MD) simulations provided a clear insight into the stability mechanism at the molecular level. This study demonstrated the novel drug-drug C-ASDs systems is a promising formulation strategy for improved dissolution rate and enhanced physical stability of poorly soluble drugs.