Evaluating gender effect in the generic bioequivalence studies by physiologically based pharmacokinetic modeling - A case study of dextromethorphan modified release tablets.

The United States Food and Drug Administration guidelines for the bioequivalence (BE) testing of the generic drug products suggests that there should be an equal proportion of male and female population in the BE study. Despite this requirement, many generic drug companies do not maintain the suggested proportion of female population in their studies. Several socio-economic and cultural factors lead to lower participation of the females in the BE studies. More recently, the regulatory agencies across the globe are requesting the generic drug companies to demonstrate the performance of their drug products in the under-represented sex via additional studies. In this work, we describe the case of Dextromethorphan modified release tablets where the gender effect on the product performance was evaluated by physiologically based pharmacokinetic (PBPK) modeling approach. We have compared the drug product's performance by population simulations considering four different scenarios. The data from all-male population (from in house Pharmacokinetic [PK] BE studies) was considered as a reference and other scenarios were compared against the all-male population data. In the first scenario, we made a comparison between all-male (100% male) vs all-female (100% female) population. Second scenario was as per agency's requirements-equal proportion of male and female in the BE study. As an extreme scenario, 100% male vs 30:70 male:female was considered (higher females than males in the BE studies). Finally, as a more realistic scenario, 100% male versus 70:30 male:female was considered (lower females than males in the BE studies). Population PK followed by virtual BE was employed to demonstrate the similarity/differences in the drug product performance between the sexes. This approach can be potentially utilized to seek BE study waivers thus saving cost and accelerating the entry of the generic products to the market.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

FREQUENCY AND OUTCOME OF NECROTIZING ENTEROCOLITIS IN PRETERM NEONATES.

BACKGROUND: Necrotizing enterocolitis (NEC) is the commonest gastrointestinal emergency in neonates. It is associated with high mortality and morbidity. Present study was conducted to determine the frequency of necrotizing enterocolitis in preterm neonates along with their outcome during stay in hospital. METHODS: This was descriptive case series carried out in Neonatal Intensive Care Unit (NICU) of Paediatrics department, POF Hospital Wah Cantt from August 2010 to February 2011. All the preterm neonates admitted in NICU POF Hospital were included in the study. Patients were clerked on a pre-designed pro forma. RESULTS: A total of 196 neonates were enrolled and 28 (14%) were diagnosed with NEC. Outcome analysis of these 28 patients with NEC revealed that 16 patients (57.14%) were discharged while 11 (39.28%) expired and one (3.5%) was referred. CONCLUSION: There is a high incidence in preterm-low birth weight babies presenting in our set-up, with high mortality rates.

COMPLICATIONS AND SAFETY OF POST PERCUTANEOUS RENAL BIOPSY IN PAEDIATRIC PATIENTS.

BACKGROUND: Renal biopsy is gold standard in diagnosis of various renal diseases. Though it is safe yet it requires adequate patient evaluation, preparation and monitoring after the procedure. METHODS: This descriptive case series was conducted in the Paediatric Nephrology Department, The Children's Hospital Lahore over a period of one year. Children aged less than 16 years were included who were suffering from renal diseases requiring renal biopsy for diagnosis. After renal biopsy patients were monitored for complications and were discharged after short stay of eight hours who got no complication during the observation period. RESULTS: Out of total 145 patients, 97 (66.1%) were males and 48 (33.9%) were females. The age range was from 0.7 years to 16 years. The duration of stay after renal biopsy was up to eight hours in 131 (90.34%) patients, while 14 (9.66%) stayed longer. Post-biopsy stay of 24 hours was observed in 8 patients and 48 hours in 5 patients. Only 1 patient stayed for 96 hours. Patients with gross haernaturia were 6 (4.1%) who were checked for perinephric hematoma formation by ultrasonography. Only one patient required blood transfusion along with fresh frozen plasma. The most common histopathological diagnosis was Mesangioproliferative with 67 (46.2%) cases, followed by Glomerulonephritis in 35 (24.1%) patients having Membranoproliferative Glomerulonephritis (MPGN) while Systemic Lupus Erythematous (SLE) nephritis was reported in 15 (10.35%) patients. CONCLUSION: Patients can be discharged after short stay post renal biopsy procedure provided done after proper screening of patients. As it not only reduces patient stay but also is cost effective.

HISTOPATHOLOGICAL PATTERNS IN PAEDIATRIC IDIOPATHIC STEROID RESISTANT NEPHROTIC SYNDROME.

BACKGROUND: Steroid-resistant nephrotic syndrome (SRNS) is a common problem but difficult to treat for pediatric nephrologists. Due to paucity of studies done in few centres in southern Pakistan regarding the histopathological aspects in paediatric patients with SRNS, this study was conducted to determine the histopathological spectrum in children with SRNS at our centre. METHODS: This descriptive study has been conducted at the Nephrology department, The Children's Hospital Lahore from February 2014 to January 2015. Based upon history, physical examination and laboratory results, all patients diagnosed as idiopathic SRNS were included in the study and renal biopsy was done to determine the underlying pathology. Histopathology reports were retrieved and data analysis done using SPSS-20.0. RESULTS: There were a total of 96 patients, 64 (66.7%) males and 32 (33.3%) females. The age range was from 0.80 to 15 years with mean age of presentation being 6.34+3.75 years. The most common histo-pathological pattern was mesangio-proliferative Glomerulonephritis found in 79 (82.3%) cases followed by Focal segmental glomerulosclerosis (FSGS) in 9 (9.4%) patients while Minimal change disease (MCD) was seen in 5 (5.2%) subjects. CONCLUSION: Mesangioproliferative glomerulonephritis is the most common histological pattern seen in children presenting with idiopathic SRNS at our centre followed by FSGS and MCD.

P7170, a novel inhibitor of mTORC1/mTORC2 and Activin receptor-like Kinase 1 (ALK1) inhibits the growth of non small cell lung cancer.

BACKGROUND: Lung cancer is the major cause of cancer-related deaths and many cases of Non Small Cell Lung Cancer (NSCLC), a common type of lung cancer, have frequent genetic/oncogenic activation of EGFR, KRAS, PIK3CA, BRAF, and others that drive tumor growth. Some patients though initially respond, but later develop resistance to erlotinib/gefitinib with no option except for cytotoxic therapy. Therefore, development of novel targeted therapeutics is imperative to provide improved survival benefit for NSCLC patients. The mTOR cell survival pathway is activated in naïve, or in response to targeted therapies in NSCLC. METHODS: We have discovered P7170, a small molecule inhibitor of mTORC1/mTORC2/ALK1 and investigated its antitumor efficacy using various in vitro and in vivo models of human NSCLC. RESULTS: P7170 inhibited the phosphorylation of AKT, S6 and 4EBP1 (substrates for mTORC2 and mTORC1) levels by 80-100% and growth of NSCLC cells. P7170 inhibited anchorage-independent colony formation of NSCLC patient tumor-derived cells subsistent of disease sub-types. The compound also induced apoptosis in NSCLC cell lines. P7170 at a well-tolerated daily dose of 20 mg/kg significantly inhibited the growth of NSCLC xenografts independent of different mutations (EGFR, KRAS, or PIK3CA) or sensitivity to erlotinib. Pharmacokinetic-pharmacodynamic (PK-PD) analysis showed sub-micro molar tumor concentrations along with mTORC1/C2 inhibition. CONCLUSIONS: Our results provide evidence of antitumor activity of P7170 in the erlotinib -sensitive and -insensitive models of NSCLC.

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.

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.

Experience Learned and Perspectives on Using Model-Integrated Evidence in the Regulatory Context for Generic Drug Products-a Meeting Report.

This report summarizes relevant insights and discussions from a 2022 FDA public workshop titled Best Practices for Utilizing Modeling Approaches to Support Generic Product Development which illustrated how model-integrated evidence has been used and can be leveraged further to inform generic drug product development and regulatory decisions during the assessment of generic drug applications submitted to the FDA. The workshop attendees discussed that model-integrated evidence (MIE) approaches for generics are being applied in the space of long-acting injectable (LAI) products to develop shorter and more cost-effective alternative study designs for LAI products. Modeling and simulation approaches are utilized to support virtual BE assessments at the site of action for locally acting drug products and to assess the impact of food on BE assessments for oral dosage forms. The factors contributing to the success of the model-informed drug development program under PDUFA VI were discussed. The generic drug industry shared that decisions on formulation candidate/formulation variant selection, on pilot in vivo bioavailability studies, and on alternative study designs for BE assessment are informed by modeling and simulation approaches. There was agreement that interactions between the regulatory agencies and the industry are desirable because they improve the industry's understanding of scientific and other regulatory considerations on implementing modeling and simulation approaches in drug development and regulatory submissions.