Validation of a Caco-2 microfluidic Chip model for predicting intestinal absorption of BCS Class I-IV drugs.

Oral delivery is considered the most patient preferred route of drug administration, however, the drug must be sufficiently soluble and permeable to successfully formulate an oral formulation. There have been advancements in the development of more predictive solubility and dissolution tools, but the tools that has been developed for permeability assays have not been validated as extensively as the gold-standard Caco-2 Transwell assay. Here, we evaluated Caco-2 intestinal permeability assay in Transwells and a commercially available microfluidic Chip using 19 representative Biopharmaceutics Classification System (BCS) Class I-IV compounds. For each selected compound, we performed a comprehensive viability test, quantified its apparent permeability (Papp), and established an in vitro in vivo correlation (IVIVC) to the human fraction absorbed (fa) in both culture conditions. Permeability differences were observed across the models as demonstrated by antipyrine (Transwell Papp: 38.5 ± 6.1 × 10-8 cm/s vs Chip Papp: 32.9 ± 11.3 × 10-8 cm/s) and nadolol (Transwell Papp: 0.6 ± 0.1 × 10-7 cm/s vs Chip Papp: 3 ± 1.2 × 10-7 cm/s). The in vitro in vivo correlation (IVIVC; Papp vs. fa) of the Transwell model (r2 = 0.59-0.83) was similar to the Chip model (r2 = 0.41-0.79), highlighting similar levels of predictivity. Comparing to historical data, our Chip Papp data was more closely aligned to native tissues assessed in Ussing chambers. This is the first study to comprehensively validate a commercial Gut-on-a-Chip model as a predictive tool for assessing oral absorption to further reduce our reliance on animal models.

Effect of Food Composition on the PK of Isoniazid Quantitatively Explained Using Physiologically Based Biopharmaceutics Modeling.

This work shows the utilization of a physiologically based biopharmaceutics model (PBBM) to mechanistically explain the impact of diverse food types on the pharmacokinetics (PK) of isoniazid (INH) and acetyl-isoniazid (Ac-INH). The model was established and validated using published PK profiles for INH along with a combination of measured and predicted values for the physico-chemical and biopharmaceutical propertied of INH and Ac-INH. A dedicated ontogeny model was developed for N-acetyltransferase 2 (NAT2) in human integrating Michaelis Menten parameters for this enzyme in the physiologically based pharmacokinetic (PBPK) model tissues and in the gut, to explain the pre-systemic and systemic metabolism of INH across different acetylator types. Additionally, a novel equation was proposed to calculate the luminal drug degradation related to the presence of reducing sugars, using individual sugar molar concentrations in the meal. By incorporating luminal degradation into the model, adjusting bile salt concentrations and gastric emptying according to food type and quantity, the PBBM was able to accurately predict the negative effect of carbohydrate-rich diets on the PK of INH.

Physiologically Based Biopharmaceutics Modeling (PBBM): Best Practices for Drug Product Quality, Regulatory and Industry Perspectives: 2023 Workshop Summary Report.

Physiologically based biopharmaceutics modeling (PBBM) is used to elevate drug product quality by providing a more accurate and holistic understanding of how drugs interact with the human body. These models are based on the integration of physiological, pharmacological, and pharmaceutical data to simulate and predict drug behavior in vivo. Effective utilization of PBBM requires a consistent approach to model development, verification, validation, and application. Currently, only one country has a draft guidance document for PBBM, whereas other major regulatory authorities have had limited experience with the review of PBBM. To address this gap, industry submitted confidential PBBM case studies to be reviewed by the regulatory agencies; software companies committed to training. PBBM cases were independently and collaboratively discussed by regulators, and academic colleagues participated in some of the discussions. Successful bioequivalence "safe space" industry case examples are also presented. Overall, six regulatory agencies were involved in the case study exercises, including ANVISA, FDA, Health Canada, MHRA, PMDA, and EMA (experts from Belgium, Germany, Norway, Portugal, Spain, and Sweden), and we believe this is the first time such a collaboration has taken place. The outcomes were presented at this workshop, together with a participant survey on the utility and experience with PBBM submissions, to discuss the best scientific practices for developing, validating, and applying PBBMs. The PBBM case studies enabled industry to receive constructive feedback from global regulators and highlighted clear direction for future PBBM submissions for regulatory consideration.

Using molecularly dissolved drug concentrations in PBBMs improves the prediction of oral absorption from supersaturating formulations.

Predicting the absorption of drugs from enabling formulations is still challenging due to the limited capabilities of standard physiologically based biopharmaceutics models (PBBMs) to capture complex absorption processes. Amongst others, it is often assumed that both, molecularly and apparently dissolved drug in the gastrointestinal lumen are prone to absorption. A recently introduced method for measuring concentrations of molecularly dissolved drug in a dynamic in vitro dissolution setup using microdialysis has opened new opportunities to test this hypothesis and refine mechanistic PBBM approaches. In the present study, we compared results of PBBMs that used either molecularly or apparently dissolved concentrations in the simulated gastrointestinal lumen as input parameters. The in vitro dissolution data from three supersaturating formulations of Posaconazole (PCZ) were used as model input. The modeling outcome was verified using PCZ concentration vs. time profiles measured in human intestinal aspirates and in the blood plasma. When using apparently dissolved drug concentrations (i.e., the sum of colloid-associated and molecularly dissolved drug) the simulated systemic plasma exposures were overpredicted, most pronouncedly with the ASD-based tablet. However, if the concentrations of molecularly dissolved drug were used as input values, the PBBM resulted in accurate prediction of systemic exposures for all three PCZ formulations. The present study impressively demonstrated the value of considering molecularly dissolved drug concentrations as input value for PBBMs of supersaturating drug formulations.

iBCS: 3. A Biopharmaceutics Classification System for Orally Inhaled Drug Products.

In this article, we specify for the first time a quantitative biopharmaceutics classification system for orally inhaled drugs. To date, orally inhaled drug product developers have lacked a biopharmaceutics classification system like the one developed to navigate the development of immediate release of oral medicines. Guideposts for respiratory drug discovery chemists and inhalation product formulators have been elusive and difficult to identify due to the complexity of pulmonary physiology, the intricacies of drug deposition and disposition in the lungs, and the influence of the inhalation delivery device used to deliver the drug as a respirable aerosol. The development of an inhalation biopharmaceutics classification system (iBCS) was an initiative supported by the Product Quality Research Institute (PQRI). The goal of the PQRI iBCS working group was to generate a qualitative biopharmaceutics classification system that can be utilized by inhalation scientists as a "rule of thumb" to identify desirable molecular properties and recognize and manage CMC product development risks based on physicochemical properties of the drug and the deposited lung dose. Herein, we define the iBCS classes quantitatively according to the dose number and permeability. The proposed iBCS was evaluated for its ability to categorize marketed inhaled drugs using data from the literature. The appropriateness of the classification of each drug was assessed based on published development, clinical and nonclinical data, and mechanistic physiologically based biopharmaceutics modeling. The inhaled drug product development challenges for each iBCS classification are discussed and illustrated for different classes of marketed inhaled drugs. Finally, it is recognized that discriminatory laboratory methods to characterize regional lung deposition, dissolution, and permeability will be key to fully realizing the benefits of an iBCS to streamline and derisk inhaled drug development.

Biowaiver Monograph for Immediate-Release Solid Oral Dosage Forms: Isavuconazonium Sulfate.

A Biopharmaceutics Classification System (BCS)-based biowaiver monograph is presented for isavuconazonium sulfate. A BCS-based biowaiver is a regulatory option to substitute appropriate in vitro data for in vivo bioequivalence studies. Isavuconazonium sulfate is the prodrug of isavuconazole, a broad-spectrum azole antifungal indicated for invasive fungal infections. While the prodrug can be classified as a BCS Class III drug with high solubility but low permeability, the parent drug can be classified as a BCS Class II drug with low solubility but high permeability. Interestingly, the in vivo behavior of both is additive and leads isavuconazonium sulfate to act like a BCS class I drug substance after oral administration. In this work, experimental solubility and dissolution data were evaluated and compared with available literature data to investigate whether it is feasible to approve immediate release solid oral dosage forms containing isavuconazonium sulfate according to official guidance from the FDA, EMA and/or ICH. The risks associated with waiving a prodrug according to the BCS-based biowaiver guidelines are reviewed and discussed, noting that current regulations are quite restrictive on this point. Further, results show high solubility but instability of isavuconazonium sulfate in aqueous media. Although experiments on the dissolution of the capsule contents confirmed 'very rapid' dissolution of the active pharmaceutical ingredient (API) isavuconazonium sulfate, its release from the commercial marketed capsule formulation Cresemba is limited by the choice of capsule shell material, providing an additional impediment to approval of generic versions via the BCS-Biowaiver approach.

Neural Network Models for Predicting Solubility and Metabolism Class of Drugs in the Biopharmaceutics Drug Disposition Classification System (BDDCS).

BACKGROUND AND OBJECTIVE: The biopharmaceutics drug disposition classification system (BDDCS) categorizes drugs into four classes on the basis of their solubility and metabolism. This framework allows for the study of the pharmacokinetics of transporters and enzymatic metabolization on biopharmaceuticals, as well as drug-drug interactions in the body. The objective of the present study was to develop computational models by neural network models and structural parameters and physicochemical properties to estimate the class of a drug in the BDDCS system. METHODS: In this study, deep learning methods were utilized to explore the potential of artificial and convolutional neural networks (ANNs and CNNs) in predicting the BDDCS class of 721 substances. The structural parameters and physicochemical properties [Abraham solvation parameters, octanol-water partition (log P) and over the pH range 1-7.5 (log D), number of rotatable bonds, hydrogen bond acceptor numbers, as well as hydrogen bond donor count] are calculated with various software. These compounds were then split into a training set consisting of 602 molecules and a test set of 119 compounds to validate the models. RESULTS: The results of this study showed that neural network models using applied parameters of the drug, i.e., log D and Abraham solvation parameters, are able to predict the class of solubility and metabolism in the BDDCS system with good accuracy. CONCLUSIONS: Neural network models are well equipped to deal with the relations between the structural parameters and physicochemical properties of drugs and BDDCS classes. In addition, log D is a more suitable parameter compared with log P in predicting BDDCS.

Evaluation of mucosal immune profile associated with Zileuton nanocrystal-formulated BCS-II drug upon oral administration in Sprague Dawley rats.

Nanocrystal drug formulation involves several critical manufacturing procedures that result in complex structures to improve drug solubility, dissolution, bioavailability, and consequently the efficacy of poorly soluble Biopharmaceutics Classification System (BCS) II and IV drugs. Nanocrystal formulation of an already approved oral drug may need additional immunotoxic assessment due to changes in the physical properties of the active pharmaceutical ingredient (API). In this study, we selected Zileuton, an FDA-approved drug that belongs to BCS-II for nanocrystal formulation. To evaluate the efficacy and mucosal immune profile of the nanocrystal drug, 10-week-old rats were dosed using capsules containing either API alone or nanocrystal formulated Zileuton (NDZ), or with a physical mixture (PM) using flexible oral gavage syringes. Control groups consisted of untreated, or placebo treated animals. Test formulations were administrated to rats at a dose of 30 mg/kg body weight (bw) once a day for 15 days. The rats treated with NDZ or PM had approximately 4.0 times lower (7.5 mg/kg bw) API when compared to the micron sized API treated rats. At the end of treatment, mucosal (intestinal tissue) and circulating cytokines were measured. The immunological response revealed that NDZ decreased several proinflammatory cytokines in the ileal mucosa (Interleukin-18, Tumor necrosis Factor-α and RANTES [regulated upon activation, normal T cell expressed and secreted]). A similar pattern in the cytokine profile was also observed for the micron sized API and PM treated rats. The cytokine production revealed that there was a significant increase in the production of IL-1ß and IL-10 in the females in all experimental groups. Additionally, NDZ showed an immunosuppressive effect on proinflammatory cytokines both locally and systemically, which was similar to the response in micron sized API treated rats. These findings indicate that NDZ significantly decreased several proinflammatory cytokines and it displays less immunotoxicity, probably due to the nanocrystal formulation. Thus, the nanocrystal formulation is more suitable for oral drug delivery, as it exhibited better efficacy, safety, and reduced toxicity.

Applications of Modeling and Simulation Approaches in Support of Drug Product Development of Oral Dosage Forms and Locally Acting Drug Products: a Symposium Summary.

The number of modeling and simulation applications, including physiologically based pharmacokinetic (PBPK) models, physiologically based biopharmaceutics modeling (PBBM), and empirical models, has been constantly increasing along with the regulatory acceptance of these methodologies. While aiming at minimizing unnecessary human testing, these methodologies are used today to support the development and approval of novel drug products and generics. Modeling approaches are leveraged today for assessing drug-drug interaction, informing dose adjustments in renally or hepatically impaired patients, perform dose selection in pediatrics and pregnant women and diseased populations, and conduct biopharmaceutics-related assessments such as establish clinically relevant specifications for drug products and achieve quality assurance throughout the product life cycle. In the generics space, PBPK analyses are utilized toward virtual bioequivalence assessments within the scope of alternative bioequivalence approaches, product-specific guidance development, and food effect assessments among others. Case studies highlighting the evolving and expanding role of modeling and simulation approaches within the biopharmaceutics space were presented at the symposium titled "Model Informed Drug Development (MIDD): Role in Dose Selection, Vulnerable Populations, and Biowaivers - Chemical Entities" and Prologue "PBPK/PBBM to inform the Bioequivalence Safe Space, Food Effects, and pH-mediated DDIs" at the American Association of Pharmaceutical Scientists (AAPS) PharmSci 360 Annual Meeting in Boston, MA, on October 16-19, 2022, and are summarized here.

Approaches to Account for Colon Absorption in Physiologically Based Biopharmaceutics Modeling of Extended-Release Drug Products.

The rate and extent of colon absorption are important determinants of the in vivo performance of extended-release (ER) drug products. The ability to appropriately predict this at different stages of development using mechanistic physiologically based biopharmaceutic modeling (PBBM) is highly desirable. This investigation aimed to evaluate the prediction performance of three different approaches to account for colon absorption in predictions of the in vivo performance of ER drug product variants with different in vitro release profiles. This was done by mechanistic predictions of the absorption and plasma exposure of the ER drug products using GastroPlus and GI-Sim for five drugs with different degrees of colon absorption limitations in humans. Colon absorption was accounted for in the predictions using three different approaches: (1) by an a priori approach using the default colon models, (2) by fitting the colon absorption scaling factors to the observed plasma concentration-time profiles after direct administration to the colon in humans, or (3) from the ER drug product variant with the slowest in vitro release profile. The prediction performance was evaluated based on the percentage prediction error and the average absolute prediction error (AAPE). Two levels of acceptance criteria corresponding to highly accurate (AAPE ≤ 20%) and accurate (AAPE 20-50%) predictions were defined prior to the evaluation. For the a priori approach, the relative bioavailability (Frel), AUC0-t, and Cmax of the ER drug product variants for the low to medium colon absorption limitation risk drugs was accurately predicted with an AAPE range of 11-53 and 8-59% for GastroPlus and GI-Sim, respectively. However, the prediction performance was poor for the high colon absorption limitation risk drugs. Moreover, accounting for the human regional colon absorption data in the models did not improve the prediction performance. In contrast, using the colon absorption scaling factors derived from the slowest ER variant significantly improved the prediction performance regardless of colon absorption limitation, with a majority of the predictions meeting the high accuracy criteria. For the slowest ER approach, the AAPE ranges were 5-24 and 5-32% for GastroPlus and GI-Sim, respectively, excluding the low permeability drug. In conclusion, the a priori PBBM can be used during candidate selection and early product design to predict the in vivo performance of ER drug products for low to medium colon absorption limitation risk drugs with sufficient accuracy. The results also indicate a limited value in performing human regional absorption studies in which the drug is administered to the colon as a bolus to support PBBM development for ER drug products. Instead, by performing an early streamlined relative bioavailability study with the slowest relevant ER in vitro release profile, a highly accurate PBBM suitable for ER predictions for commercial and regulatory applications can be developed, except for permeability-limited drugs.

SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters.

PURPOSE: To construct a detailed mechanistic and physiologically based biopharmaceutics model capable of predicting 1) device-formulation-tissue interaction during the injection process and 2) binding, degradation, local distribution, diffusion, and drug absorption, following subcutaneous injection. This paper is part of a series and focusses on the first aspect. METHODS: A mathematical model, SubQ-Sim, was developed incorporating the details of the various substructures within the subcutaneous environment together with the calculation of dynamic drug disposition towards the lymph ducts and venous capillaries. Literature was searched to derive key model parameters in healthy and diseased subjects. External factors such as body temperature, exercise, body position, food or stress provide a means to calculate the impact of "life events" on the pharmacokinetics of subcutaneously administered drugs. RESULTS: The model predicts the tissue backpressure time profile during the injection as a function of injection rate, volume injected, solution viscosity, and interstitial fluid viscosity. The shape of the depot and the concentrations of the formulation and proteins in the depot are described. The model enables prediction of formulation backflow following premature needle removal and the resulting formulation losses. Finally, the effect of disease (type 2 diabetes) or the presence of recombinant human hyaluronidase in the formulation on the injection pressure, are explored. CONCLUSIONS: This novel model can successfully predict tissue back pressure, depot dimensions, drug and protein concentration and formulation losses due to incorrect injection, which are all important starting conditions for predicting drug absorption from a subcutaneous dose. The next article will describe the absorption model and validation against clinical data.

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.

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

Quality risk assessment following ICH Q9 principles is an important activity to ensure optimal clinical efficacy and safety of a drug product. Typically, risk assessment is focused on product performance wherein critical material attributes, formulation variables, and process parameters are evaluated from a manufacturing perspective. Extending ICH Q9 principles to biopharmaceutics risk assessment to identify factors that can impact in vivo performance is an upcoming area. This is evident by recent regulatory trends wherein a new term critical bioavailability attributes (CBA) has been coined to identify such factors. Although significant work has been performed for biopharmaceutics risk assessment for new molecules, there is a need for harmonized biopharmaceutics risk assessment workflow for generic submissions. In this manuscript, we attempted to provide a framework for performing biopharmaceutics risk assessment for generic regulatory submissions. A detailed workflow for performing biopharmaceutics risk assessment includes identification of initial CBA (iCBA), their confirmatory evaluation followed by definition of the control strategy. Tools for biopharmaceutics risk assessment, i.e., bio-discriminatory dissolution method and physiologically based biopharmaceutics modeling (PBBM) were discussed from a practical perspective. Furthermore, a case study for CBA evaluation using PBBM modeling for an extended-release product for regulatory submission has been described using the proposed workflow. Finally, future directions of integrating CBA evaluation, biopharmaceutics risk assessment to the FDA Knowledge Aided Structured Assessment (KASA) initiative, the necessity of risk assessment templates, and knowledge sharing between industry and academia are discussed. Overall, the work described in this manuscript can facilitate and provide guidance for biopharmaceutics risk assessment for generic submissions.

Drug Permeability - Best Practices for Biopharmaceutics Classification System (BCS)-Based Biowaivers: A workshop Summary Report.

The workshop "Drug Permeability - Best Practices for Biopharmaceutics Classification System (BCS) Based Biowaivers" was held virtually on December 6, 2021, organized by the University of Maryland Center of Excellence in Regulatory Science and Innovation (M-CERSI), and the Food and Drug Administration (FDA). The workshop focused on the industrial, academic, and regulatory experiences in generating and evaluating permeability data, with the aim to further facilitate implementation of the BCS and efficient development of high-quality drug products globally. As the first international permeability workshop since the BCS based biowaivers was finalized as the ICH M9 guideline, the workshop included lectures, panel discussions, and breakout sessions. Lecture and panel discussion topics covered case studies at IND, NDA, and ANDA stages, typical deficiencies relating to permeability assessment supporting BCS biowaiver, types of evidence that are available to demonstrate high permeability, method suitability of a permeability assay, impact of excipients, importance of global acceptance of permeability methods, opportunities to expand the use of biowaivers (e.g. non-Caco-2 cell lines, totality-of-evidence approach to demonstrate high permeability) and future of permeability testing. Breakout sessions focused on 1) in vitro and in silico intestinal permeability methods; 2) potential excipient effects on permeability and; 3) use of label and literature data to designate permeability class.

Predictive Potential of BCS and Pharmacokinetic Parameters on Study Outcome: Analysis of 198 In Vivo Bioequivalence Studies.

BACKGROUND AND OBJECTIVES: Understanding predictive potential of parameters to perform early bioequivalence (BE) risk assessment is crucial for good planning and risk mitigation during product development. The objective of the present study was to evaluate predictive potential of various biopharmaceutical and pharmacokinetic parameters on the outcome of BE study. METHODS: Retrospective analysis was performed on 198 Sandoz (Lek Pharmaceuticals d.d., A Sandoz Company, Verovskova 57, 1526 Ljubljana, Slovenia) sponsored BE studies [52 active pharmaceutical ingredients (API)] where characteristics of BE study and APIs were collected for immediate-release products and their predictive potential on the study outcome was assessed using univariate statistical analysis. RESULTS: Biopharmaceutics Classification System (BCS) was confirmed to be highly predictive of BE success. BE studies with poorly soluble APIs were riskier (23% non-BE) than with highly soluble APIs (0.1% non-BE). APIs with either lower bioavailability (BA), presence of first-pass metabolism, and/or being substrate for P-glycoprotein substrate (P-gP) were associated with higher non-BE occurrence. In silico permeability and time at peak plasma concentrations (Tmax) were shown as potentially relevant features for predicting BE outcome. In addition, our analysis showed significantly higher occurrence of non-BE results for poorly soluble APIs with disposition described by multicompartment model. The conclusions for poorly soluble APIs were the same on a subset of fasting BE studies; for a subset of fed studies there were no significant differences between factors in BE and non-BE groups. CONCLUSION: Understanding the association of parameters and BE outcome is important for further development of early BE risk assessment tools where focus should be first in finding additional parameters to differentiate BE risk within a group of poorly soluble APIs.

Integrating Forward and Reverse Translation in PBPK Modeling to Predict Food Effect on Oral Absorption of Weakly Basic Drugs.

INTRODUCTION: Ketoconazole and posaconazole are two weakly basic broad-spectrum antifungals classified as Biopharmaceutics Classification System class II drugs, indicating that they are highly permeable, but exhibit poor solubility. As a result, oral bioavailability and clinical efficacy can be impacted by the formulation performance in the gastrointestinal system. In this work, we have leveraged in vitro biopharmaceutics and clinical data available in the literature to build physiologically based pharmacokinetic (PBPK) models for ketoconazole and posaconazole, to determine the suitability of forward in vitro-in vivo translation for characterization of in vivo drug precipitation, and to predict food effect. METHODS: A stepwise modeling approach was utilized to derive key parameters related to absorption, such as drug solubility, dissolution, and precipitation kinetics from in vitro data. These parameters were then integrated into PBPK models for the simulation of ketoconazole and posaconazole plasma concentrations in the fasted and fed states. RESULTS: Forward in vitro-in vivo translation of intestinal precipitation kinetics for both model drugs resulted in poor predictions of PK profiles. Therefore, a reverse translation approach was applied, based on limited fitting of precipitation-related parameters to clinical data. Subsequent simulations for ketoconazole and posaconazole demonstrated that fasted and fed state PK profiles for both drugs were adequately recapitulated. CONCLUSION: The two examples presented in this paper show how middle-out modeling approaches can be used to predict the magnitude and direction of food effects provided the model is verified on fasted state PK data.

Biowaiver Monograph for Immediate-Release Solid Oral Dosage Forms: Levocetirizine Dihydrochloride.

Levocetirizine, a histamine H1-receptor antagonist, is prescribed to treat uncomplicated skin rashes associated with chronic idiopathic urticaria as well as the symptoms of both seasonal and continual allergic rhinitis. In this monograph, the practicality of using Biopharmaceutics Classification System (BCS) based methodologies as a substitute for pharmacokinetic studies in human volunteers to appraise the bioequivalence of immediate-release (IR) oral, solid dosage forms containing levocetirizine dihydrochloride was investigated, using data from the literature and in-house testing. Levocetirizine's solubility and permeability properties, as well as its dissolution from commercial products, its therapeutic uses, therapeutic index, pharmacokinetics and pharmacodynamic traits, were reviewed in accordance with the BCS, along with any reports in the literature about failure to meet bioequivalence (BE) requirements, bioavailability issues, drug-excipient interactions as well as other relevant information. The data presented in this monograph unequivocally point to classification of levocetirizine in BCS Class 1. For products that are somewhat supra-equivalent or somewhat sub-equivalent, clinical risks are expected to be insignificant in light of levocetirizine's wide therapeutic index and unlikelihood of severe adverse effects. After careful consideration of all the information available, it was concluded that the BCS-based biowaiver can be implemented for products which contain levocetirizine dihydrochloride, provided (a) the test product comprises excipients that are typically found in IR oral, solid drug products that have been approved by a country belonging to or associated with ICH and are used in quantities that are typical for such products, (b) data supporting the BCS-based biowaiver are gathered using ICH-recommended methods, and (c) all in vitro dissolution requirements specified in the ICH guidance are met by both the test and comparator products (in this case, the comparator is the innovator product).

Biowaiver Monograph for Immediate-Release Dosage Forms: Levamisole Hydrochloride.

This work describes the potential applicability of the BCS-based Biowaiver to oral solid dosage forms containing Levamisole hydrochloride, an anthelmintic drug on the WHO List of Essential Medicines. Solubility and permeability data of levamisole hydrochloride were searched in the literature and/or measured experimentally. Levamisole hydrochloride is a highly soluble drug, but there is no clear evidence of high permeability in humans, indicating that it should provisionally be assigned to BCS class III. The biowaiver procedure would thus be applicable for solid oral dosage forms containing levamisole hydrochloride as the only active ingredient. Due to the lack of data in the literature regarding excipient effects on the bioequivalence of products containing levamisole, it is currently recommended that the products comply with the ICH and WHO guidelines: the test formulation should have the same qualitative composition as the comparator, contain very similar quantities of those excipients, and be very rapidly dissolving at pH 1.2, 4.5, and 6.8. However, for certain well-studied excipients, there appears to be opportunity for additional regulatory relief in future versions of the ICH BCS Guidance M9, such as not requiring that the quantities of these common excipients in the test and comparator be the same.

Physiologically Based Pharmacokinetics Modeling in Biopharmaceutics: Case Studies for Establishing the Bioequivalence Safe Space for Innovator and Generic Drugs.

For successful oral drug development, defining a bioequivalence (BE) safe space is critical for the identification of newer bioequivalent formulations or for setting of clinically relevant in vitro specifications to ensure drug product quality. By definition, the safe space delineates the dissolution profile boundaries or other drug product quality attributes, within which the drug product variants are anticipated to be bioequivalent. Defining a BE safe space with physiologically based biopharmaceutics model (PBBM) allows the establishment of mechanistic in vitro and in vivo relationships (IVIVR) to better understand absorption mechanism and critical bioavailability attributes (CBA). Detailed case studies on how to use PBBM to establish a BE safe space for both innovator and generic drugs are described. New case studies and literature examples demonstrate BE safe space applications such as how to set in vitro dissolution/particle size distribution (PSD) specifications, widen dissolution specification to supersede f2 tests, or application toward a scale-up and post-approval changes (SUPAC) biowaiver. A workflow for detailed PBBM set-up and common clinical study data requirements to establish the safe space and knowledge space are discussed. Approaches to model in vitro dissolution profiles i.e. the diffusion layer model (DLM), Takano and Johnson models or the fitted PSD and Weibull function are described with a decision tree. The conduct of parameter sensitivity analyses on kinetic dissolution parameters for safe space and virtual bioequivalence (VBE) modeling for innovator and generic drugs are shared. The necessity for biopredictive dissolution method development and challenges with PBBM development and acceptance criteria are described.

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., AUC0-t, Cmax, and Tmax), 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, Tmax, 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.