Biopharmaceutics Risk Assessment-Connecting Critical Bioavailability Attributes with In Vitro, In Vivo Properties and Physiologically Based Biopharmaceutics Modeling to Enable Generic Regulatory Submissions

Physiologically Based Biopharmaceutics Modeling Coupled with Biopredictive Dissolution in Development of Bioequivalent Formulation for Mesalamine Enteric Coated Tablet: A Tough Nut to Crack

Mesalamine is a locally acting anti-inflammatory drug used to treat mild to moderate ulcerative colitis. Because of complex formulation principle and high in vivo variability, development of bioequivalent formulation for mesalamine is challenging. Further, fed state possess significant challenges for bioequivalence (BE) due to interplay of multiple factors. In the work, we have developed a novel biopredictive media for mesalamine enteric coated tablets and integrated into physiologically based biopharmaceutics model (PBBM) to predict in vivo fed behavior. USP III based gradient media was developed to mimic in vivo fed condition. The developed PBBM was initially validated with literature data and subsequently re-optimized with pilot BE study data. Further, virtual bioequivalence (VBE) was performed to evaluate model predictability for pilot BE data. Later, the model was applied for prospective BE predictions with increased subjects and parametric sensitivity analysis was performed to identify physiological factors that can impact in vivo performance. Further, the model was used to predict luminal and enterocyte concentrations in colon to demonstrate equivalent efficacy. Additionally, a novel dissolution/permeation tool (Dissoflux) was employed to compare permeability behavior of formulations. Overall, this work enabled BE prediction for complex mesalamine enteric coated tablets and helped to understand parameters that can impact in vivo performance.

A critical review on approaches to generate and validate virtual population for physiologically based pharmacokinetic models: Methodologies, case studies and way forward

PURPOSE

In silico modeling and simulation techniques such as physiologically based pharmacokinetic (PBPK) and physiologically based biopharmaceutics modeling (PBBM) have demonstrated various applications in drug discovery and development. Virtual bioequivalence leverages these computation tools to predict bioequivalence between reference and test formulations thereby demonstrating possibilities to reduce human studies. A pre-requisite for virtual bioequivalence is development of validated virtual population that depicts the same variability as that of observed in clinic. This development, validation and optimization of virtual population is a key attribute of virtual bioequivalence based on which conclusion of bioequivalence is made.

METHODS

Various strategies for optimization of virtual population based on appropriate considerations of physicochemical, physiological and disposition aspects are demonstrated with the help of six diverse case studies of immediate and modified release formulations. Once the virtual population is optimized to match in vivo variability, it can be used for various applications such as biowaivers, dissolution specification justification, f2 mismatch, establishing dissolution safe space, etc. In this review article, we attempted to describe various methodologies and approaches for optimization of virtual population using Gastroplus.

RESULTS

Strategies based on optimization of virtual population with emphasis on specific and sensitive parameters were portrayed. We have further elucidated considerations related to study design, in vivo variability, sample size for optimization of virtual population from Gastroplus perspective.

CONCLUSION

We believe that this review article provides a step-by-step process for virtual population optimization for interest of biopharmaceutics modeling scientists in order to ensure reliable and credible physiological models.

Machine learning driven bioequivalence risk assessment at an early stage of generic drug development

BACKGROUND

Bioequivalence risk assessment as an extension of quality risk management lacks examples of quantitative approaches to risk assessment at an early stage of generic drug development. The aim of our study was to develop a model-based approach for bioequivalence risk assessment that uses pharmacokinetic and physicochemical characteristics of drugs as predictors and would standardize the first step of risk assessment.

METHODS

The Sandoz in-house bioequivalence database of 128 bioequivalence studies with poorly soluble drugs (23.5% non-bioequivalent) was used to train and validate the model. Four different modeling approaches, random forest, XGBoost, logistic regression and naïve Bayes, were compared.

RESULTS

Among the best performing machine learning models, random forest was selected and optimized for the number of features, resulting in an accuracy of 84% on the test data set. The most important features for prediction were those related to solubility (dose number, acid dissociation constant), absorption and elimination rate, effective permeability, variability of pharmacokinetic endpoints, and absolute bioavailability. All features had a conceivable influence on the model predictions.

CONCLUSION

The model was used to develop a bioequivalence risk assessment approach to categorize drugs in early development into high, medium or low risk classes.

Modeling and Simulations in Latin-American Generic Markets: Perspectives from Chilean Local Industry, Regulatory Agency, and Academia

In the last 20 years, modeling and simulations (M&S) have gained increased attention in pharmaceutical sciences. International industry and world-reference agencies have used M&S to make cost-efficient decisions through the model-informed drug development (MIDD) framework. Modeling tools include biopredictive dissolution models, physiologically based pharmacokinetic models (PBPK), biopharmaceutic models (PBBM), and virtual bioequivalence, among many others. Regulatorily, health agencies are becoming more and more open to accept the use of M&S to support regulatory applications, including setting dissolution specifications, quality-by-design (QbD), postapproval changes (SUPAC), etc. Nonetheless, the potential of M&S has been only barely explored in Latin America (Latam) across different actors: industry, regulatory agencies, and even academia. In this manuscript, we discuss the challenges and opportunities for implementing M&S approaches in Latam. Perspectives of regional experts were shared in a workshop. Attendance (professionals from industry, regulator, academia, and clinicians) also shared their views via survey. The rational development of bioequivalent generics was considered the main opportunity for M&S in regional market, particularly the use of PBPK and PBBM. Nonetheless, a critical mass of modeling scientists is needed before Latin American industry and regulators can actually benefit from M&S. Collaborations (e.g., Academia-Industry and Academia-Regulatory) may be a path to develop applied research projects and train the future modelers. Reaching that critical mass, scientists from industry may apply modeling across generic drug development process and life cycle, while regulatory scientists may issue guidelines in local language to support regional industry. Only at that stage could the full potential of MIDD be reached in Latin American generic markets.

Bioequivalence requirements for orally inhaled and nasal drug products and use of novel physiologically based biopharmaceutics modeling approaches for assessing in vivo performance

Orally inhaled and nasal drug products (OINDPs) are complex due to the interplay between the device, formulation, and patient characteristics. Establishing bioequivalence (BE) of OINDPs with reference is highly complex and require in vitro, in vivo pharmacokinetic and comparative clinical endpoint studies that are challenging to conduct. In order to increase the rate of submission and approval of generics, regulatory agencies are encouraging the use of alternative in vitro and in silico methodologies to replace complex in vivo studies. The present review attempts to summarize current understanding of alternative BE approaches for OINDPs. In vitro characterization studies required for establishing BE for OINDPs considering USFDA and EMA guidance's are detailed. In silico models such as pulmonary compartmental absorption and transit (PCAT) with emphasis on model input parameters are portrayed. Further, two detailed case studies of inhalation nebulizer and nasal spray formulations are described where PCAT models are developed for predicting BE and local concentrations. Lastly, current understanding of such BE approaches from regulatory perspectives are discussed summarizing recent regulatory workshops and through collation of USFDA product specific guidance's for almost 70 drug products. Overall, this manuscript can act as ready-to-use guide to understand alternative approaches for establishing BE for OINDPs.

Justification of widened dissolution specifications of an extended-release product using physiologically based biopharmaceutics modeling

Drug products meeting the dissolution specifications is crucial in order to ensure consistent clinical performance. However, in certain cases, wider dissolution specifications may be required based on product behaviour. While the justification of such wider specifications may be challenging from a regulatory context, approaches such as physiological-based biopharmaceutics modeling (PBBM) can be utilised for this purpose.Product DRL is a fixed-dose combination product consisting of immediate release (IR) and extended-release (ER) portions. For the ER portion, the dissolution specifications consisted of four time points, and a proposal was made to relax the specification at the 2h time point (from 50-70% to 45-67%) to reduce the batch failures at the commercial scale.To support the wider specification, a PBBM was developed and extensively validated with literature & in-house studies. Virtual bioequivalence was performed using the pivotal clinical study data.Virtual dissolution profiles for proposed wider specifications were generated using three different approaches. The incorporation of lower and upper dissolution profiles into the model indicated the absence of impact on in vivo performance thereby justifying the specifications.Regulatory acceptance of proposed specifications with PBBM indicated the significance of using modeling approaches to reduce repeated testing thereby facilitating faster approvals.

Novel omeprazole delayed release orally disintegrating tablets for enhanced patient compliance: a case of model informed formulation development

The advanced in silico simulation tools, such as physiologically based biopharmaceutics models (PBBM) or physiologically based pharmacokinetic models (PBPK), play critical role in model informed formulation development. This approach has been successfully implemented in the present case for development of novel omeprazole delayed-release orally disintegrating tablets (ODT) formulation, aimed to enhance patient compliance.PBBM was developed using physicochemical, biopharmaceutical, and dissolution data. The dissolution studies for pilot formulations were conducted in biopredictive media in fasting (0.1 N HCl followed by pH 6.8) and fed (pH 5 followed by pH 6.8) conditions. The model was extensively validated in three stages: pilot fasted, pilot fed virtual bioequivalence and food effect assessments. Impressively, the model was able to predict both passed and failed batches appropriately.Based on insights from the pilot study, a higher scale pivotal formulation was optimised. Prospective predictions were made for pivotal formulations using validated model and bio results were found to be in line with model predictions in fasting condition.Overall, a rationale and patient compliant formulation was developed using innovative modelling approach and filed to regulatory agency. The novel omeprazole formulation enhanced patient compliance through ease of administration thereby circumventing challenges of conventional formulation.

A Semi-Mechanistic Physiologically Based Biopharmaceutics Model to Describe Complex and Saturable Absorption of Metformin: Justification of Dissolution Specifications for Extended Release Formulation

Physiologically based pharmacokinetic (PBPK) or physiologically based biopharmaceutics models (PBBM) demonstrated plethora of applications in both new drugs and generic product development. Justification of dissolution specifications and establishment of dissolution safe space is an important application of such modeling approaches. In case of molecules exhibiting saturable absorption behavior, justification of dissolution specifications requires development of a model that incorporates effects of transporters is critical to simulate in vivo scenario. In the present case, we have developed a semi-mechanistic PBBM to describe the non-linearity of BCS class III molecule metformin for justification of dissolution specifications of extended release formulation at strengths 500 mg and 1000 mg. Semi-mechanistic PBBM was built using physicochemical properties, dissolution and non-linearity was accounted through incorporation of multiple transporter kinetics at absorption level. The model was extensively validated using literature reported intravenous, oral (immediate & extended release) formulations and further validated using in-house bioequivalence data in fasting and fed conditions. Virtual dissolution profiles at lower and upper specifications were generated to justify the dissolution specifications. The model predicted literature as well as in-house clinical study data with acceptable prediction errors. Further, virtual bioequivalence trials predicted the bioequivalence outcome that matched with clinical study data. The model predicted bioequivalence when lower and upper specifications were compared against pivotal test formulations thereby justifying dissolution specifications. Overall, complex and saturable absorption pathway of metformin was successfully simulated and this work resulted in regulatory acceptance of dissolution specifications which has ability to reduce multiple dissolution testing.

Advancing Virtual Bioequivalence for Orally Administered Drug Products: Methodology, Real-World Applications and Future Outlook

Bioequivalence studies are pivotal in generic drug development wherein therapeutic equivalence is provided with an innovator product. However, bioequivalence studies represent significant complexities due to the interplay of multiple factors related to drug, formulation, physiology, and pharmacokinetics. Approaches such as physiologically based biopharmaceutics modeling (PBBM) can enable virtual bioequivalence (VBE) assessment through appropriately developed and validated models. Such models are now being extensively used for bioequivalence risk assessment, internal decision-making, and the evaluation of drug and formulation factors related to bioequivalence. Depiction of the above-mentioned factors through the incorporation of variability and development of a virtual population for bioequivalence assessment is of paramount importance in utilizing such models. In this manuscript, we have portrayed our current understanding of VBE. A detailed explanation was provided with respect to study designs, in vivo variability, and the impact of physiological, drug, and formulation factors on the development of the population for VBE. Furthermore, strategies are suggested to incorporate variability in GastroPlus with an emphasis on intra-subject and inter-occasion variability. Two industrial case studies pertaining to immediate and modified release formulation were portrayed wherein VBE was utilized for decision-making and regulatory justification. Finally, regulatory understanding in the area of VBE, along with future perspectives, was detailed.

Playing Hide-and-Seek with Tyrosine Kinase Inhibitors: Can We Overcome Administration Challenges?

Tyrosine kinase inhibitors (TKIs) have demonstrated significant efficacy against various types of cancers through molecular targeting mechanisms. Over the past 22 years, more than 100 TKIs have been approved for the treatment of various types of cancer indicating the significant progress achieved in this research area. Despite having significant efficacy and ability to target multiple pathways, TKIs administration is associated with challenges. There are reported inconsistencies between observed food effect and labeling administration, challenges of concomitant administration with acid-reducing agents (ARA), pill burden and dosing frequency. In this context, the objective of present review is to visit administration challenges of TKIs and effective ways to tackle them. We have gathered data of 94 TKIs approved in between 2000 and 2022 with respect to food effect, ARA impact, administration schemes (food and PPI restrictions), number of pills per day and administration frequency. Further, trend analysis has been performed to identify inconsistencies in the labeling with respect to observed food effect, molecules exhibiting ARA impact, in order to identify solutions to remove these restrictions through novel formulation approaches. Additionally, opportunities to reduce number of pills per day and dosing frequency for better patient compliance were suggested using innovative formulation interventions. Finally, utility of physiologically based pharmacokinetic modeling (PBPK) for rationale formulation development was discussed with literature reported examples. Overall, this review can act as a ready-to-use-guide for the formulation, biopharmaceutics scientists and medical oncologists to identify opportunities for innovation for TKIs.

Conventional vs Mechanistic IVIVC: A Comparative Study in Establishing Dissolution Safe Space for Extended Release Formulations

The use of in vitro-in vivo correlation (IVIVC) for extended release oral dosage forms is an important technique that can avoid potential clinical studies. IVIVC has been a topic of discussion over the past two decades since the inception of USFDA guidance. It has been routinely used for biowaivers, establishment of dissolution safe space and clinically relevant dissolution specifications, for supporting site transfers, scale-up and post approval changes. Although conventional or mathematical IVIVC is routinely used, other approach such as mechanistic IVIVC can be of attractive choice as it integrates all the physiological aspects. In the present study, we have performed comparative evaluation of mechanistic and conventional IVIVC for establishment of dissolution safe space using divalproex sodium and tofacitinib extended release formulations as case examples. Conventional IVIVC was established using Phoenix and mechanistic IVIVC was set up using Gastroplus physiologically based biopharmaceutics model (PBBM). Virtual dissolution profiles with varying release rates were constructed around target dissolution profile using Weibull function. After internal and external validation, the virtual dissolution profiles were integrated into mechanistic and conventional IVIVC and safe space was established by absolute error and T/R ratio's methods. The results suggest that mechanistic IVIVC yielded wider safe space as compared to conventional IVIVC. The results suggest that a mechanistic approach of establishing IVIVC may be a flexible approach as it integrates physiological aspects. These findings suggest that mechanistic IVIVC has wider potential as compared to conventional IVIVC to gain wider dissolution safe space and thus can avoid potential clinical studies.

Dissolution Profiles Comparison Using Conventional and Bias Corrected and Accelerated f2 Bootstrap Approaches with Different Software's: Impact of Variability, Sample Size and Number of Bootstraps

Dissolution profiles comparison is an important element in order to support biowaivers, scale-up and post approval changes and site transfers. Highly variable dissolution can possess significant challenges for comparison and f2 bootstrap approach can be utilized in such cases. However, availability of different types of f2 and confidence intervals (CI) methods indicates necessity to understand each type of calculation thoroughly. Among all approaches, bias corrected and accelerated (BCa) can be an attractive choice as it corrects the bias and skewness of the distribution. In this manuscript, we have performed comparison of highly variable dissolution data using various software's by adopting percentile and BCa CI approaches. Diverse data with different variability's, number of samples and bootstraps were evaluated with JMP, DDSolver, R-software, SAS and PhEq. While all software's yielded similar observed f2 values, differences in lower percentile CI was observed. BCa with R-software and JMP provided superior lower percentile as compared to other computations. Expected f2 recommended by EMA has resulted as stringent criteria as compared to estimated f2. No impact of number of bootstraps on similarity analysis was observed whereas number of samples increased chance of acceptance. Variability has impacted similarity outcome with estimated f2 but chance of acceptance enhanced with BCa approach. Further, freely available R-software can be of attractive choice due to computation of various types of f2, percentile and BCa intervals. Overall, this work can enable regulatory submissions to enhance probability of similarity through appropriate selection of number of samples, technique based on variability of dissolution data.

Novel application of PBBM to justify impact of faster dissolution on safety and pharmacokinetics - a case study and utility in regulatory justifications

Physiologically based biopharmaceutics modelling (PBBM) was recognised as potential approach for biopharmaceutics applications. However, PBBM to justify safety is an unexplored area.In this manuscript, we elucidated PBBM application for safety justification. Product DRL is a generic extended release tablet containing an anti-epileptic narrow therapeutic index (NTI) drug. During dossier review, regulatory agency requested to evaluate the impact of faster dissolution profiles observed during stability on safety aspects. In order to justify, PBBMbased strategy was adapted.Model was validated and population simulations were performed for reference and test formulations and the predictions matched with clinical outcome. The model was found to be sensitive to dissolution changes and hence applied for the prediction of stability batches exhibiting faster dissolution profiles, virtually generated profiles at lower and upper specifications. The maximum predicted plasma levels were well below the reported safety levels, thereby demonstrating safety of the product.Overall, a novel application of PBBM to justify safety was demonstrated. Similar justifications using PBBM and linking with safety can be adopted where safety can be impacted due to aggravated dissolution profiles. Such justifications have potential to avoid clinical safety studies and helps in faster approval of drug product.