Using Mechanistic Modeling Approaches to Support Bioequivalence Assessments for Oral Products.

This report summarizes the proceedings for Day 1 Session 3 of the 2-day public workshop entitled "Best Practices for Utilizing Modeling Approaches to Support Generic Product Development," a jointly sponsored workshop by the US Food and Drug Administration (FDA) and the Center for Research on Complex Generics (CRCG) in the year 2022. The aims of this workshop were to discuss how to modernize approaches for efficiently demonstrating bioequivalence (BE), to establish their role in modern paradigms of generic drug development, and to explore and develop best practices for the use of modeling and simulation approaches in regulatory submissions and approval. The theme of this session is mechanistic modeling approaches supporting BE assessments for oral drug products. As a summary, with more successful cases of PBPK absorption modeling being developed and shared, the general strategies/frameworks on using PBPK for oral products are being formed; this will help further evolvement of this area. In addition, the early communications between the industry and the agency through appropriate pathways (e.g., pre-abbreviated new drug applications (pre-ANDA) meetings) are encouraged, and this will speed up the successful development and utility of PBPK modeling for oral products.

Role of Physiologically Based Biopharmaceutics Modeling (PBBM) in Fed Bioequivalence Study Waivers: Regulatory Outlook, Case Studies and Future Perspectives.

Over the past few decades, physiologically based biopharmaceutics modeling (PBBM) has demonstrated its utility in both new drug and generic product development. Applications of PBBM for fed bioequivalence study waivers is an upcoming area. Recently Innovation & Quality (IQ) consortium demonstrated utility of PBBM to avoid repeat food effect studies for new drugs. In the similar lines, the current manuscript aims to discuss role of PBBM in generic fed bioequivalence study waivers. Generic industry practices related to PBBM model development to predict fed bioequivalence was portrayed with special emphasis on fed bio-predictive media. Media that can simulate fed bioequivalence study outcome were discussed from practical perspective. In-depth analysis, collating the data from 36 products was performed to understand predictability of PBBM for fed bioequivalence. Cases where PBBM was successful to predict fed bioequivalence was correlated with BCS class, formulation category and type of food effect. Further, two case studies were presented wherein fed bioequivalence study waiver obtained with PBBM approach. Lastly, future direction in terms of fed bioequivalence study waivers, regulatory perspectives and best practices for PBBM were portrayed. Overall, this article paves a way to utilize PBBM for generic fed bioequivalence study waivers.

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.

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.

Physiologically based pharmacokinetic modelling to predict drug-drug interactions for encorafenib. Part I. Model building, validation, and prospective predictions with enzyme inhibitors, inducers, and transporter inhibitors.

Encorafenib, a potent BRAF kinase inhibitor undergoes significant metabolism by CYP3A4 (83%) and CYP2C19 (16%) and also a substrate of P-glycoprotein (P-gp). Because of this, encorafenib possesses potential for enzyme-transporter related interactions. Clinically, its drug-drug interactions (DDIs) with CYP3A4 inhibitors (posaconazole, diltiazem) were reported and hence there is a necessity to study DDIs with multiple enzyme inhibitors, inducers, and P-gp inhibitors.USFDA recommended clinical CYP3A4, CYP2C19, P-gp inhibitors, CYP3A4 inducers were selected and prospective DDIs were simulated using physiologically based pharmacokinetic modelling (PBPK). Impact of dose (50 mg vs. 300 mg) and staggering of administrations (0-10 h) on the DDIs were predicted.PBPK models for encorafenib, perpetrators simulated PK parameters within twofold prediction error. Clinically reported DDIs with posaconazole and diltiazem were successfully predicted.CYP2C19 inhibitors did not result in significant DDI whereas strong CYP3A4 inhibitors resulted in DDI ratio up to 4.5. Combining CYP3A4, CYP2C19 inhibitors yielded DDI equivalent CYP3A4 alone. Strong CYP3A4 inducers yielded DDI ratio up to 0.3 and no impact of P-gp inhibitors on DDIs was observed. The DDIs were not impacted by dose and staggering of administration. Overall, this work indicated significance of PBPK modelling for evaluating clinical DDIs with enzymes, transporters and interplay.

Physiologically based pharmacokinetic modeling (PBPK) to predict drug-drug interactions for encorafenib. Part II. Prospective predictions in hepatic and renal impaired populations with clinical inhibitors and inducers.

Encorafenib, a potent BRAF kinase inhibitor gets significantly metabolised by CYP3A4 (83%) and CYP2C19 (16%) and is a substrate for P-glycoprotein (P-gp). Due to significant metabolism by CYP3A4, encorafenib exposure can increase in hepatic and renal impairment and may lead to altered magnitude of drug-drug interactions (DDI). Hence, it is necessary to assess the exposures & DDI's in impaired population.Physiologically based pharmacokinetic modelling (PBPK) was utilised to determine the exposures of encorafenib in hepatic and renal impairment along with altered DDI's. Prospective DDI's were predicted with USFDA recommended clinical CYP3A4, CYP2C19, P-gp inhibitors and CYP3A4 inducers.PBPK models for encorafenib, perpetrators simulated PK parameters within 2-folds error. Encorafenib exposures significantly increased in hepatic as compared to renal impairment because of reduced CYP3A4 levels.Hepatic impairment caused changes in inhibition and induction DDI's, when compared to healthy population. Renal impairment did not cause significant changes in DDIs except for itraconazole. P-gp, CYP2C19 inhibitors did not result in altered DDI's. The DDI's were found to have insignificant correlation with relative exposure increase of perpetrators in case of impairment. Overall, this work signifies use of PBPK modelling for DDI's evaluations in hepatic and renal impairment populations.

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.

Power of integrating PBPK with PBBM (PBPK-BM): a single model predicting food effect, gender impact, drug-drug interactions and bioequivalence in fasting & fed conditions.

Over the past few years, PBPK and PBBM modelling have proven their significance in drug development. PBPK modelling is traditionally used to predict drug-drug interactions, exposures in special populations whereas PBBM modelling is a part of PBPK modelling that is used for a range of biopharmaceutics applications.Because of these differences in utilities, often PBPK and PBBM models are developed separately. When both models are combined, they serve multiple purposes through unified model. In the present case, an integrated PBPK-PBBM model for an IR product has been utilised for bioequivalence prediction in fasting & fed conditions, evaluating gender impact and food effect, prediction of drug-drug interactions.Model was built using physicochemical properties, enzymes and transporter kinetics, bio-predictive dissolution and has been validated with passing and failed pilot BE studies. The validated model predicted pivotal bioequivalence outcomes in fasting & fed conditions accurately, predicted gender impact and food effect in line with literature. Drug-drug interactions arising from transporter and metabolising enzymes were predicted accurately.Overall, this work demonstrates the utility of combining PBPK and PBBM model that can yield a single model which can be used for multiple purposes, regulatory justifications and can reduce regulatory review timelines.

Best Practices for Integration of Dissolution Data into Physiologically Based Biopharmaceutics Models (PBBM): A Biopharmaceutics Modeling Scientist Perspective.

Dissolution is considered as a critical input into physiologically based biopharmaceutics models (PBBM) as it governs in vivo exposure. Despite many workshops, initiatives by academia, industry, and regulatory, wider practices are followed for dissolution data input into PBBM models. Due to variety of options available for dissolution data input into PBBM models, it is important to understand pros, cons, and best practices while using specific dissolution model. This present article attempts to summarize current understanding of various dissolution models and data inputs in PBBM software's and aims to discuss practical challenges and ways to overcome such scenarios. Different approaches to incorporate dissolution data for immediate, modified, and delayed release formulations are discussed in detail. Common challenges faced during fitting of z-factor are discussed along with novel approach of dissolution data incorporation using P-PSD model. Ways to incorporate dissolution data for MR formulations using Weibull and IVIVR approaches were portrayed with examples. Strategies to incorporate dissolution data for DR formulations was depicted along with practical aspects. Approaches to generate virtual dissolution profiles, using Weibull function, DDDPlus, and time scaling for defining dissolution safe space, and strategies to generate virtual dissolution profiles for justifying single and multiple dissolution specifications were discussed. Finally, novel ways to integrate dissolution data for complex products such as liposomes, data from complex dissolution systems, importance of precipitation, and bio-predictive ability of QC media for evaluation of CBA's impact were discussed. Overall, this article aims to provide an easy guide for biopharmaceutics modeling scientist to integrate dissolution data effectively into PBBM models.

Predicting transporter mediated drug-drug interactions via static and dynamic physiologically based pharmacokinetic modeling: A comprehensive insight on where we are now and the way forward.

The greater utilization and acceptance of physiologically-based pharmacokinetic (PBPK) modeling to evaluate the potential metabolic drug-drug interactions is evident by the plethora of literature, guidance's, and regulatory dossiers available in the literature. In contrast, it is not widely used to predict transporter-mediated DDI (tDDI). This is attributed to the unavailability of accurate transporter tissue expression levels, the absence of accurate in vitro to in vivo extrapolations (IVIVE), enzyme-transporter interplay, and a lack of specific probe substrates. Additionally, poor understanding of the inhibition/induction mechanisms coupled with the inability to determine unbound concentrations at the interaction site made tDDI assessment challenging. Despite these challenges, continuous improvements in IVIVE approaches enabled accurate tDDI predictions. Furthermore, the necessity of extrapolating tDDI's to special (pediatrics, pregnant, geriatrics) and diseased (renal, hepatic impaired) populations is gaining impetus and is encouraged by regulatory authorities. This review aims to visit the current state-of-the-art and summarizes contemporary knowledge on tDDI predictions. The current understanding and ability of static and dynamic PBPK models to predict tDDI are portrayed in detail. Peer-reviewed transporter abundance data in special and diseased populations from recent publications were compiled, enabling direct input into modeling tools for accurate tDDI predictions. A compilation of regulatory guidance's for tDDI's assessment and success stories from regulatory submissions are presented. Future perspectives and challenges of predicting tDDI in terms of in vitro system considerations, endogenous biomarkers, the use of empirical scaling factors, enzyme-transporter interplay, and acceptance criteria for model validation to meet the regulatory expectations were discussed.

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.

Utility of Physiologically Based Biopharmaceutics Modeling (PBBM) in Regulatory Perspective: Application to Supersede f2, Enabling Biowaivers & Creation of Dissolution Safe Space.

Product DRL is a generic IR tablet formulation with BCS Class-III API, available in two strengths: 50mg & 100mg. The reference and test formulations have salt-A & salt-B of API but both products were bioequivalent based on the in vivo bioequivalence study conducted for higher strength 100mg. While leveraging the generic product to different market, the reference product from other market showed slower release than generic formulation resulting in f2<50 in pH 6.8 for both 50mg and 100mg, because of which waiver for BE study couldn't be granted. To support f2 mismatch at 100mg, 50mg and to facilitate biowaiver of 50mg, a Gastroplus® PBBM model was developed & validated. Virtual bioequivalence trials were performed using the slower dissolution profile of other market reference. It was demonstrated that despite slower dissolution, bioequivalence was achieved for test product against other market reference for 50mg & 100mg strengths. Additionally, dissolution safe space was created using virtual dissolution profiles, which indicated that when >85% released up to 60 min there is no impact on bioequivalence. Overall, for molecules with permeability controlled absorption (i.e. BCS-III), very rapid dissolution criteria can be relaxed by defining dissolution safe space thereby enabling more waivers in future.

Simplified Model-Dependent and Model-Independent Approaches for Dissolution Profile Comparison for Oral Products: Regulatory Perspective for Generic Product Development.

Dissolution profile comparison among different formulations plays a critical role during new drug as well as generic product development. In the generic product development, dissolution profile comparison is a mandate for biowaivers (BCS-based, for lower strengths and IVIVC-based biowaivers) and also from quality control perspective. Even though traditionally similarity factor or f2 is used as a metric for dissolution profile comparison, it comes with multiple limitations and requirements (e.g., number of time points and variability). To overcome this, regulatory agencies suggested model-independent (e.g., MSD) and model-dependent (e.g., zero order, Weibull) dissolution profile comparison methods. Although most of regulatory guidance documents mention about such approaches, their usage in reality is limited probably due to lack of clear, detailed, and step-wise procedure. In this context, the present article describes simplistic yet detailed procedures of dissolution profile comparison with case studies covering generic product development scenario's from a regulatory perspective. Detailed review of regulatory guidances from various agencies was made along with examples of such approaches in regulatory submissions. Data from three formulations-Formulations A, B, and C-were utilized to perform dissolution profile comparison using MSD, zero-order, and Weibull release profile-based comparisons. Dissolution profile comparisons were made using all of these three approaches complying with regulatory requirements. These examples demonstrated value and utility of these approaches and the simplified and detailed procedure explained in this manuscript can be adapted for generic product applications.

Establishing the Bioequivalence Safe Space for Immediate-Release Oral Dosage Forms using Physiologically Based Biopharmaceutics Modeling (PBBM): Case Studies.

For oral drug products, in vitro dissolution is the most used surrogate of in vivo dissolution and absorption. In the context of drug product quality, safe space is defined as the boundaries of in vitro dissolution, and relevant quality attributes, within which drug product variants are expected to be bioequivalent to each other. It would be highly desirable if the safe space could be established via a direct link between available in vitro data and in vivo pharmacokinetics. In response to the challenges with establishing in vitro-in vivo correlations (IVIVC) with traditional modeling approaches, physiologically based biopharmaceutics modeling (PBBM) has been gaining increased attention. In this manuscript we report five case studies on using PBBM to establish a safe space for BCS Class 2 and 4 across different companies, including applications in an industrial setting for both internal decision making or regulatory applications. The case studies provide an opportunity to reflect on practical vs. ideal datasets for safe space development, the methodologies for incorporating dissolution data in the model and the criteria used for model validation and application. PBBM and safe space, still represent an evolving field and more examples are needed to drive development of best practices.

Development, validation and application of physiologically based biopharmaceutics model to justify the change in dissolution specifications for DRL ABC extended release tablets.

OBJECTIVE: The generic drug product DRL ABC is an Extended Release (ER) Tablet manufactured by Dr. Reddy's Laboratories Limited and have multi point dissolution as part of release specification. A proposal is being made to revise the dissolution specification and the aim of present work was to evaluate if this would still provide bioequivalent product. METHODS: PBBM was developed for DRL ABC using literature reported pharmacokinetic (PK) data. The intravenous PK data and in vitro metabolic rate constants were utilized for developing PBPK model first, followed by that in conjugation with mechanistic ACATTM model, a PBBM is developed for per-oral immediate release formulations. The validated model was applied to predict clinical bioequivalence (BE) study data for the Reference (Innovator ER Tablet) and Test product. For Reference and Test product, in vivo dissolution profiles were mechanistically deconvoluted from plasma concentration (Cp)-time profiles. Further, mechanistic in vitro-in vivo relationship (IVIVR) applied to in vitro release profiles of two hypothetical Test product batches (one with single point low dissolution profile (SPLP) and other with overall low dissolution profile (LP)) in order to calculate their in vivo releases and population simulation was performed with 40 virtual subjects. RESULTS: Results from the cross-over virtual trials showed BE between the Reference and various Test product batches (SPLP and LP), with maximum Cp (Cmax) and area under the Cp-time curve (AUC0-inf) well within 80-125% range. CONCLUSION: PBBM in conjugation with IVIVR and virtual BE was successfully applied for justifying changes in dissolution specification of DRL ABC.

In vitro and In silico biopharmaceutic regulatory guidelines for generic bioequivalence for oral products: Comparison among various regulatory agencies.

Generic drug development is a complex process that involves development of formulation similar to reference product. Because of the complexity associated with generic drug development, many regulatory agencies have come up with various guidelines. Out of many guidelines, the biopharmaceutics classification system that was introduced in 1995 based on aqueous solubility and permeability helped many pharmaceutical scientists across the globe to utilize the tool for formulation development, waiver of in vivo studies. Later on in vitro guidelines based on dissolution and in vitro in vivo correlation were introduced by many regulatory agencies with an intent to reduce number of in vivo human testing thereby facilitating shorter development time and faster approvals and launch. Most recently, understanding the importance in silico approaches such as physiologically based pharmacokinetic modelling, regulatory agencies such as United States Food and Drug Administration (USFDA) and European Middle East and Africa (EMA) came up with modelling guidance documents. Even though consensus exists between guidance documents from various regulatory agencies, still there are many minor to major differences exists between these guidance documents that needs to be considered while submitting a generic drug application. This review aims to compare all the in vitro and in silico guidance documents from major regulatory agencies with emphasis on latest trends and technologies combined with regulatory acceptability with an intention to harmonize regulations. Guidance documents from major regulatory agencies such as USFDA, EMA, World Health Organization, International Council for Harmonization and other emerging markets were compared. Similarities &differences among these guidance documents are critically reviewed to provide the reader a detailed overview of these guidance documents at one place.

Prediction of ARA/PPI Drug-Drug Interactions at the Drug Discovery and Development Interface.

Advances in understanding of human disease have prompted the U.S. Food and Drug Administration to classify certain molecules as "break-through therapies," providing an accelerated review that may potentially enhance the quality of patient lives. With this designation come compressed timelines to develop drug products, which are not only suitable for clinic trials but can also be approved and brought to the market rapidly. Early risk identification for decreased oral absorption due to drug-drug interactions with proton pump inhibitors (PPIs) or acid-reducing agents (ARAs) is paramount to an effective drug product development strategy. An early ARA/PPI drug-drug interaction (DDI) risk identification strategy has been developed using physiologically based absorption modeling that readily integrates ADMET predictor generated in silico estimates or measured in vitro solubility, permeability, and ionization constants. Observed or predicted pH-solubility profile data along with pKas and drug dosing parameters were used to calculate a fraction of drug absorbed ratio in absence and presence of ARAs/PPIs. An integrated physiologically based pharmacokinetic absorption model using GastroPlus™ with pKa values fitted to measured pH-solubility profile data along with measured permeability data correctly identified the observed ARA/PPI DDI for 78% (16/22) of the clinical studies. Formulation strategies for compounds with an anticipated pH-mediated DDI risk are presented.

Pharmacokinetic aspects and in vitro-in vivo correlation potential for lipid-based formulations.

Lipid-based formulations have been an attractive choice among novel drug delivery systems for enhancing the solubility and bioavailability of poorly soluble drugs due to their ability to keep the drug in solubilized state in the gastrointestinal tract. These formulations offer multiple advantages such as reduction in food effect and inter-individual variability, ease of preparation, and the possibility of manufacturing using common excipients available in the market. Despite these advantages, very few products are available in the present market, perhaps due to limited knowledge in the in vitro tests (for prediction of in vivo fate) and lack of understanding of the mechanisms behind pharmacokinetic and biopharmaceutical aspects of lipid formulations after oral administration. The current review aims to provide a detailed understanding of the in vivo processing steps involved after oral administration of lipid formulations, their pharmacokinetic aspects and in vitro in vivo correlation (IVIVC) perspectives. Various pharmacokinetic and biopharmaceutical aspects such as formulation dispersion and lipid digestion, bioavailability enhancement mechanisms, impact of excipients on efflux transporters, and lymphatic transport are discussed with examples. In addition, various IVIVC approaches towards predicting in vivo data from in vitro dispersion/precipitation, in vitro lipolysis and ex vivo permeation studies are also discussed in detail with help of case studies.

Validation of an HPLC method for determination of imatinib mesylate in rat serum and its application in a pharmacokinetic study.

A simple, selective, and sensitive liquid chromatographic method has been developed and validated for quantitative determination of Imatinib mesylate in rat serum. Efficient chromatographic separation has been performed on a Zorbax Extend (5 microm, 4.6 x 250 mm) double end-capped C(18) column using a mobile phase consisting of methanol and aqueous triethyl amine (pH 10.5; 1%, v/v) (60:40, v/v) in an isocratic mode at a flow rate of 1 mL/min. Simple and effective liquid-liquid extraction technique has resulted in consistent and high recoveries (90.32-95.86%) at all concentrations studied. The method has demonstrated linearity from 25 to 1600 ng/mL with a regression coefficient of 0.9995. Accuracy of the method is acceptable with intra-batch %bias between -2.34 to 3.42 and inter-batch %bias between -2.17 to 3.45. The method has demonstrated high sensitivity with lower limit of quantification of 25 ng/mL and excellent stability of Imatinib mesylate in serum. The method is found to be rapid, reliable, and suitable for in vivo pharmacokinetic study.

Application of rotatable central composite design in the preparation and optimization of poly(lactic-co-glycolic acid) nanoparticles for controlled delivery of paclitaxel.

CONTEXT: Polymeric carrier systems of paclitaxel (PCT) offer advantages over only available formulation Taxol® in terms of enhancing therapeutic efficacy and eliminating adverse effects. OBJECTIVE: The objective of the present study was to prepare poly (lactic-co-glycolic acid) nanoparticles containing PCT using emulsion solvent evaporation technique. METHODS: Critical factors involved in the processing method were identified and optimized by scientific, efficient rotatable central composite design aiming at low mean particle size and high entrapment efficiency. Twenty different experiments were designed and each formulation was evaluated for mean particle size and entrapment efficiency. The optimized formulation was evaluated for in vitro drug release, and absorption characteristics were studied using in situ rat intestinal permeability study. RESULTS: Amount of polymer and duration of ultrasonication were found to have significant effect on mean particle size and entrapment efficiency. First-order interactions of amount of miglyol with amount of polymer were significant in case of mean particle size, whereas second-order interactions of polymer were significant in mean particle size and entrapment efficiency. The developed quadratic model showed high correlation (R(2) > 0.85) between predicted response and studied factors. The optimized formulation had low mean particle size (231.68 nm) and high entrapment efficiency (95.18%) with 4.88% drug content. The optimized formulation showed controlled release of PCT for more than 72 hours. In situ absorption study showed faster and enhanced extent of absorption of PCT from nanoparticles compared to pure drug. CONCLUSION: The poly (lactic-co-glycolic acid) nanoparticles containing PCT may be of clinical importance in enhancing its oral bioavailability.