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- When to Extend Monitoring of Anti-drug Antibodies for High-risk
Biotherapeutics in Clinical Trials: an Opinion from the European
Immunogenicity Platform-
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Abstract: Abstract The determination of a tailored anti-drug antibody (ADA) testing strategy is based on the immunogenicity risk assessment to allow a correlation of ADAs with changes to pharmacokinetics, efficacy, and safety. The clinical impact of ADA formation refines the immunogenicity risk assessment and defines appropriate risk mitigation strategies. Health agencies request for high-risk biotherapeutics to extend ADA monitoring for patients that developed an ADA response to the drug until ADAs return to baseline levels. However, there is no common understanding in which cases an extension of ADA follow-up sampling beyond the end of study (EOS) defined in the clinical study protocol is required. Here, the Immunogenicity Strategy Working Group of the European Immunogenicity Platform (EIP) provides recommendations on requirements for an extension of ADA follow-up sampling in clinical studies where there is a high risk of serious consequences from ADAs. The importance of ADA evaluation during a treatment-free period is recognized but the decision whether to extend ADA monitoring at a predefined EOS should be based on evaluation of ADA data in the context of corresponding clinical signals. If the clinical data set shows that safety consequences are minor, mitigated, or resolved, further ADA monitoring may not be required despite potentially detectable ADAs above baseline. Extended ADA monitoring should be centered on individual patient benefit.
PubDate: 2022-05-12
- A General Biphasic Bodyweight Model for Scaling Basal Metabolic Rate,
Glomerular Filtration Rate, and Drug Clearance from Birth to Adulthood-
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Abstract: The objective of this study is to propose a unified, continuous, and bodyweight-only equation to quantify the changes of human basal metabolic rate (BMR), glomerular filtration rate (GFR), and drug clearance (CL) from infancy to adulthood. The BMR datasets were retrieved from a comprehensive historical database of male and female subjects (0.02 to 64 years). The CL datasets for 17 drugs and the GFR dataset were generated from published maturation and growth models with reported parameter values. A statistical approach was used to simulate the model-generated CL and GFR data for a hypothetical population with 26 age groups (from 0 to 20 years). A biphasic equation with two power-law functions of bodyweight was proposed and evaluated as a general model using nonlinear regression and dimensionless analysis. All datasets universally reveal biphasic curves with two distinct linear segments on log–log plots. The biphasic equation consists of two reciprocal allometric terms that asymptotically determine the overall curvature. The fitting results show a superlinear scaling phase (asymptotic exponent >1; ca. 1.5–3.5) and a sublinear scaling phase (asymptotic exponent <1; ca. 0.5–0.7), which are separated at the phase transition bodyweight ranging from 5 to 20 kg with a mean value of 10 kg (corresponding to 1 year of age). The dimensionless analysis generalizes and offers quantitative realization of the maturation and growth process. In conclusion, the proposed mixed-allometry equation is a generic model that quantitatively describes the phase transition in the human maturation process of diverse human functions. Graphical 
PubDate: 2022-05-10
- Biomarker Assay Validation by Mass Spectrometry
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Abstract: Abstract Decades of discussion and publication have gone into the guidance from the scientific community and the regulatory agencies on the use and validation of pharmacokinetic and toxicokinetic assays by chromatographic and ligand binding assays for the measurement of drugs and metabolites. These assay validations are well described in the FDA Guidance on Bioanalytical Methods Validation (BMV, 2018). While the BMV included biomarker assay validation, the focus was on understanding the challenges posed in validating biomarker assays and the importance of having reliable biomarker assays when used for regulatory submissions, rather than definition of the appropriate experiments to be performed. Different from PK bioanalysis, analysis of biomarkers can be challenging due to the presence of target analyte(s) in the control matrices used for calibrator and quality control sample preparation, and greater difficulty in procuring appropriate reference standards representative of the endogenous molecule. Several papers have been published offering recommendations for biomarker assay validation. The situational nature of biomarker applications necessitates fit-for-purpose (FFP) assay validation. A unifying theme for FFP analysis is that method validation requirements be consistent with the proposed context of use (COU) for any given biomarker. This communication provides specific recommendations for biomarker assay validation (BAV) by LC-MS, for both small and large molecule biomarkers. The consensus recommendations include creation of a validation plan that contains definition of the COU of the assay, use of the PK assay validation elements that support the COU, and definition of assay validation elements adapted to fit biomarker assays and the acceptance criteria for both.
PubDate: 2022-05-09
- Is Incurred Sample Reanalysis (ISR) Applicable in Biomarker Assays'
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PubDate: 2022-05-05
- Effect of the Size of Protein Therapeutics on Brain Pharmacokinetics
Following Systematic Administration-
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Abstract: Here, we have investigated the effect of size of protein therapeutics on brain pharmacokinetics (PK) following systemic administration in rats. All tested proteins were derived from trastuzumab that do not bind to any targets in rats. PK data generated with F(ab)2 (100 kDa), Fab (50 kDa), and scFv (27 kDa) fragments of trastuzumab, along with published PK data for FcRn non-binding and wild-type trastuzumab (150 kDa), were used to establish a relationship between the protein size and brain exposure. A large-pore microdialysis system was used to measure the PK of proteins in the plasma, the interstitial fluid (ISF) at the striatum (ST), and the cerebrospinal fluid (CSF) at the lateral ventricle (LV) and cisterna magna (CM). Concentrations of all the proteins in plasma, brain homogenate, ISF, and CSF were measured using ELISA. When evaluating the effect of protein size in the absence of FcRn binding, we found a bell-shaped relationship between the size and ISF/plasma AUC ratio, where 100 kDa F(ab)2 demonstrated the highest exposure. A similar bell-shaped relationship was observed for the brain homogenate/plasma AUC ratio, with a peak at 50 kDa. The CSF/plasma AUC ratio at LV increased monotonously with a decrease in the size of proteins. We observed that the exposure of protein therapeutics in different regions of the brain could be significantly different and there could be optimal sizes of protein therapeutics to accomplish maximum/selective exposure in selected brain regions following systemic administration. Graphical abstract 
PubDate: 2022-05-02
- A Fit-for-Purpose Method to Measure Circulating Levels of the mRNA
Component of a Liposomal-Formulated Individualized Neoantigen-Specific
Therapy for Cancer-
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Abstract: Autogene cevumeran is an individualized neoantigen-specific therapy (iNeST) under development for the treatment of various solid tumors. It consists of an RNA-Lipoplex (RNA-LPX) in which the encapsulated mRNA molecule encodes up to ten neoepitopes identified from each individual patient. In association with major histocompatibility complex (MHC) class I and MHC class II, these neoantigens can potentially stimulate and expand neoantigen-specific CD4+ and CD8+ T cells, leading to antitumor responses. As part of the pharmacokinetic (PK) property assessment of Autogene cevumeran in patients, both the lipid and mRNA content in circulation are measured. This work focused on our efforts to establish a sensitive and robust method for the measurement of mRNA levels of RNA-LPX in plasma. Due to the chemical characteristics of mRNA, extra precautions are required in order to effectively preserve mRNA integrity in human plasma during sample collection, handling and storage. To this end, a number of sample collection tubes and storage conditions were evaluated in order to inform the most optimal and operationally feasible conditions by which to preserve mRNA integrity during sample collection and upon freeze–thaw. PAXgene Blood ccfDNA tubes successfully prevented mRNA degradation and were subsequently selected for patient sample collection in the clinical trial. A branched DNA (bDNA)-based mRNA PK assay was developed to achieve the desired assay performance. Here, we discuss the evaluation of various sample collection and processing conditions as well as the optimization of the work flow during bDNA PK method development. Graphical 
PubDate: 2022-05-02
- A Critical Overview of the Biological Effects of Excipients (Part I):
Impact on Gastrointestinal Absorption-
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Abstract: Traditionally, excipients have been considered in drug development from the perspective of their influence on drug solubility, manufacturability, and ability to control in vitro and in vivo drug release. These effects have been largely evaluated through studies involving in vitro dissolution methods. However, there is a growing awareness that what had previously been considered biologically inert excipients can exert numerous in vivo effects. This includes the potential to change gastrointestinal (GI) transit time, enterocyte passive transcellular or paracellular permeability, active transport activity, or presystemic drug metabolism. In this critical overview of the biological effects of excipients (Part I), we provide a summary of select published studies that explore these various in vivo factors. We also include a table that points readers to published reviews that list a range of excipients known to have biological activity. A subsequent discussion on in vitro, in vivo, and in silico methods that can be used to explore these excipient effects is provided in a separate (Part 2) continuation of this critical overview. Graphical 
PubDate: 2022-05-02
- Application of Modeling and Simulation to Identify a Shortened Study
Duration and Novel Bioequivalence Metric for a Long-Acting Intrauterine
System-
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Abstract: An intrauterine system (IUS) can be implanted in the uterus and deliver drug directly at the site of pharmacological action. Mirena was the first FDA-approved levonorgestrel (LNG) releasing IUS without an approved generic form. Its 5-year application duration presents challenges for bioequivalence (BE) assessment using the conventional in vivo studies with pharmacokinetic and/or comparative clinical endpoints. Conventionally, along with other conditions, BE could be established if the 90% confidence interval (CI) of the ratio of geometric means of residual LNG at the end of 5 years is within the BE limits of 80.00% and 125.00%. Modeling and simulation were conducted to identify a shortened BE study duration and its corresponding BE acceptance limit that can be used as a surrogate for the conventional limit for a 5-year study. Simulation results suggest that having the 90% CI of the residual LNG 12 months post insertion within 95.00–105.26% would ensure that residual LNG amount at 5 years to be within 80.00–125.00%. This modeling and simulation practice leads to the current BE recommendation: if a test IUS is made of the same material in the same concentration and has the same physical dimensions as the Mirena, its BE could be established by showing (1) comparative physicochemical and mechanical properties; (2) comparative in vitro drug release behavior for 5 years; and (3) performance in a comparative short-term in vivo study and BE based on 90% confidence interval of test and reference ratio of residual LNG to be within 95.00–105.26% at month 12. Graphical 
PubDate: 2022-05-02
- A Critical Overview of the Biological Effects of Excipients (Part II):
Scientific Considerations and Tools for Oral Product Development-
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Abstract: It is now recognized that a number of excipients previously considered to be “inert” have the capacity to alter drug oral bioavailability through a range of in vivo effects. The various mechanisms through which an excipient can affect in vivo gastrointestinal physiology and drug absorption characteristics were explored in “A Critical Overview of The Biological Effects of Excipients (Part I): Impact on Gastrointestinal Absorption.” The next critical issue that needs to be discussed is how these biological effects are evaluated. Therefore, in Part 2 of this critical overview, the in vitro, in vivo, and in silico methods for evaluating excipient effects are considered. Examples are provided to illustrate how such studies employing these various procedures have been used to promote formulation understanding and optimization. Finally, a discussion of how the Center for Drug Evaluation and Research applies these tools to support biowaivers is provided. Graphical 
PubDate: 2022-05-02
- Does Food Affect the Pharmacokinetics of Non-orally Delivered Drugs' A
Review of Currently Available Evidence-
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Abstract: The food effects for orally administered drugs have been widely investigated and reviewed. In contrast, our knowledge of food effects for non-orally administered drugs is scarce. In this review paper, we did a literature survey to collect clinical food effect data for non-orally administered drugs. Our survey retrieved 18 drugs, including thirteen intravenously (IV), two subcutaneously (SC), one intradermally (ID), one pulmonary, and one rectally administered drug. The food effect data show that food intake can increase the absorption of SC and ID administered peptides and proteins with MW < 30 kDa by 30–50%. On the other hand, food intake can increase the elimination of IV and inhaled drugs with moderate and high hepatic extraction and reduce drug exposure by up to 35%. The food effect knowledge can be used to mitigate potential efficacy and safety risks of non-orally administered drugs. Graphical abstract 
PubDate: 2022-04-29
- Tumor Growth Inhibition-Overall Survival (TGI-OS) Model for Subgroup
Analysis Based on Post-Randomization Factors: Application for Anti-drug
Antibody (ADA) Subgroup Analysis of Atezolizumab in the IMpower150 Study-
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Abstract: Longitudinal changes of tumor size or tumor-associated biomarkers have been receiving growing attention as early markers of treatment benefits. Tumor growth inhibition-overall survival (TGI-OS) models represent mathematical frameworks used to establish a link from tumor size trajectory to survival outcome with the aim of predicting survival benefit with tumor data from a small number of subjects with a short follow-up time. In the present study, we applied the TGI-OS model to assess treatment benefit in the IMpower150 study for patients who exhibited development of anti-drug antibodies (ADA). Direct comparison between subgroups of the active arm [ADA positive (ADA +) and negative (ADA −) groups] to the entire control group is not appropriate, due to potential imbalances of baseline prognostic factors between ADA + and ADA − patients. Thus, the TGI-OS modeling framework was employed to adjust for differences in prognostic factors between the ADA subgroups to more accurately estimate the treatment benefits. After adjustment, the TGI-OS model predicted comparable hazard ratios (HRs) of OS between ADA + and ADA − subgroups, suggesting that the development of ADA does not have a clinically significant impact on the treatment benefit of atezolizumab. Graphical abstract 
PubDate: 2022-04-28
- International Regulatory Collaboration on the Analysis of Nitrosamines in
Metformin-Containing Medicines-
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Abstract: Recalls of some batches of metformin have occurred due to the detection of N-nitrosodimethylamine (NDMA) in amounts above the acceptable intake (AI) of 96 ng per day. Prior to the recalls, an international regulatory laboratory network had been monitoring drugs for nitrosamine impurities with each laboratory independently developing and validating multiple analytical procedures to detect and measure nitrosamines in metformin drugs used in their jurisdictions. Here, we provide an overview of the analysis of metformin active pharmaceutical ingredients (APIs) and drug products with 1090 samples (875 finished dosage forms (FDFs) and 215 API samples) tested beginning in November of 2019 through July of 2020. Samples were obtained internationally by a variety of approaches, including purchased, received from firms via information requests or selected by regional regulatory authorities (either at wholesalers or during GMP inspections). Only one nitrosamine (NDMA) was detected and was only present in some batches of metformin products. For API samples, 213 out of 215 lots tested had no measurable level of NDMA. For FDF samples tested, the number of batches with NDMA above the AI amount for patient safety was 17.8% (156/875). Based on these data, although the presence of NDMA was of concern, 82.2% of the samples of metformin drug products tested met quality and safety standards for patients. Regulatory agencies continue to collaborate extensively and work with marketing authorization holders to understand root causes of nitrosamine formation and agree on corrective actions to mitigate the presence of NDMA in future metformin batches. Graphical abstract 
PubDate: 2022-04-21
- Machine Learning Prediction of Clinical Trial Operational Efficiency
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Abstract: Clinical trials are the gatekeepers and bottlenecks of progress in medicine. In recent years, they have become increasingly complex and expensive, driven by a growing number of stakeholders requiring more endpoints, more diverse patient populations, and a stringent regulatory environment. Trial designers have historically relied on investigator expertise and legacy norms established within sponsor companies to improve operational efficiency while achieving study goals. As such, data-driven forecasts of operational metrics can be a useful resource for trial design and planning. We develop a machine learning model to predict clinical trial operational efficiency using a novel dataset from Roche containing over 2,000 clinical trials across 20 years and multiple disease areas. The data includes important operational metrics related to patient recruitment and trial duration, as well as a variety of trial features such as the number of procedures, eligibility criteria, and endpoints. Our results demonstrate that operational efficiency can be predicted robustly using trial features, which can provide useful insights to trial designers on the potential impact of their decisions on patient recruitment success and trial duration. Graphical 
PubDate: 2022-04-21
- Correction: Best Practices in qPCR and dPCR Validation in Regulated
Bioanalytical Laboratories-
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PubDate: 2022-04-19
- DISSOLUTION PROFILE SIMILARITY ANALYSES—STATISTICAL PRINCIPLES,
METHODS AND CONSIDERATIONS-
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Abstract: The pharmaceutical industry and regulatory agencies rely on dissolution similarity testing to make critical product decisions as part of drug product life cycle management. Accordingly, the application of mathematical approaches to evaluate dissolution profile similarity is described in regulatory guidance with the emphasis given to the similarity factor f2 with little discussion of alternative methods. In an effort to highlight current practices to assess dissolution profile similarity and to strive toward global harmonization, a workshop entitled “In Vitro Dissolution Similarity Assessment in Support of Drug Product Quality: What, How, When” was held on May 21–22, 2019 at the University of Maryland, Baltimore. This manuscript provides in-depth discussion of the mathematical principles of the model-independent statistical methods for dissolution profile similarity analyses presented in the workshop. Deeper understanding of the testing objective and statistical properties of the available statistical methods is essential to identify methods which are appropriate for application in practice. A decision tree is provided to aid in the selection of an appropriate statistical method based on the underlying characteristics of the drug product. Finally, the design of dissolution profile studies is addressed regarding analytical and statistical recommendations to sufficiently power the study. This includes a detailed discussion on evaluation of dissolution profile data for which several batches per reference and/or test product are available. Graphical abstract 
PubDate: 2022-04-06
- An Investigation of Instability in Dried Blood Spot Samples for
Pharmacokinetic Sampling in Phase 3 Trials of Verubecestat-
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Abstract: In-clinic dried blood spot (DBS) pharmacokinetic (PK) sampling was incorporated into two phase 3 studies of verubecestat for Alzheimer’s disease (EPOCH [NCT01739348] and APECS [NCT01953601]), as a potential alternative to plasma PK sampling for improved logistical feasibility and decreased blood volume burden. However, an interim PK analysis revealed verubecestat concentrations in DBS samples declined with time to assay in both trials. An investigation revealed wide variation in implementation practices for DBS sample handling procedures resulting in insufficient desiccation which caused verubecestat instability. High-resolution mass spectrometry evaluations of stressed and aged verubecestat DBS samples revealed the presence of two hydrolysis degradants. To minimize instability, new DBS handling procedures were implemented that provided additional desiccant and minimized the time to analysis. Both verubecestat hydrolysis products were previously discovered and synthesized during active pharmaceutical ingredient stability characterization. A liquid chromatography-mass spectrometry assay to quantitate the dominant verubecestat degradant in DBS samples was developed and validated. The application of this method to stressed and aged verubecestat DBS samples confirmed that degradant concentrations accounted for the observed decreases in the verubecestat concentration. Furthermore, after increasing desiccant amounts, degradant concentrations accounted for approximately 7% of the verubecestat concentration in DBS clinical samples, indicating that issues with sample handling were minimized with new storage and shipping conditions. This case study illustrates the challenges with employing new sampling techniques in large, global trials, and the importance of anticipating and mitigating implementation risks. Graphical abstract 
PubDate: 2022-04-06
- A Model-Based Approach to Bridging Plasma and Dried Blood Spot
Concentration Data for Phase 3 Verubecestat Trials-
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Abstract: In-clinic venous dried blood spot (DBS) pharmacokinetic (PK) sampling was incorporated into two phase 3 studies of verubecestat for Alzheimer’s disease (EPOCH [NCT01739348] and APECS [NCT01953601]), as a potential alternative to plasma PK sampling. Initially, plasma and DBS PK samples were collected concurrently to better understand the DBS–plasma verubecestat concentration relationship, with the intention of discontinuing DBS or plasma sampling following interim analysis. Following initial analyses and comparison of results with prespecified selection criteria, plasma PK sampling was discontinued; however, a stability issue resulting in generally lower DBS verubecestat concentrations with longer collection-to-assay times was subsequently discovered (associated with non-compliance in DBS sample handling), prompting reintroduction of plasma sampling. To enable inclusion of DBS data in population PK analyses, a conversion algorithm for calculating plasma-equivalent concentrations (accounting for DBS sample instability) was developed using paired (time-matched) plasma and DBS data from the EPOCH study. Verubecestat population PK models developed from pooled phase 1/1b and EPOCH data using either (1) plasma-only data or (2) plasma and plasma-equivalent concentrations (calculated from non-paired DBS samples) yielded similar results. The algorithm robustness was demonstrated using DBS data from paired samples from the APECS study and comparison between plasma and plasma-equivalent concentrations. The population PK model was updated with APECS data (both plasma and, if no plasma sample available, plasma equivalents). The results demonstrated similar PK in the two phase 3 populations and exposures consistent with expectations from phase 1 data. This case study illustrates challenges with employing new sampling techniques in large, global trials and describes lessons learned. Graphical abstract 
PubDate: 2022-04-06
- The AAPS Journal Theme Issue: Rising Stars in Drug Delivery and Novel
Carriers-
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PubDate: 2022-04-05
- Current Approaches for Dissolution Similarity Assessment, Requirements,
and Global Expectations-
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Abstract: This report summarizes podium presentations and breakout sessions from the second day of the 2019 M-CERSI workshop on In Vitro Dissolution Similarity Assessment in Support of Drug Product Quality: What, How, and When? Presenters from the U.S. Food and Drug Administration (FDA), Health Canada (HC), European Medicines Agency (EMA), Brazilian Health Surveillance Agency (ANVISA), and the pharmaceutical industry shared experiences/concerns with dissolution profile similarity assessment supporting minor/moderate Chemistry, Manufacturing and Control (CMC) changes. Members from regulatory agencies explained that dissolution profile similarity testing is only part of the overall assessment of the acceptability of the proposed changes; decisions are usually made based on aggregate weight of evidence. Scientific shortcomings of f2 were highlighted but no proposal on how to replace it was made. Controlling dissolution timepoint variability and application of pairwise batch-to-batch comparisons (PBC) of dissolution profiles caused considerable debate. Several industry participants suggested increased sample sizes to raise confidence in decision-making and to avoid PBC. They proposed identification of a single mathematical method with predefined acceptance criteria and suggested that dissolution timepoint selection should follow EMA and HC guidance. A majority of meeting attendees favored applying clinically relevant dissolution specifications (CRDS) and dissolution safe space to determine the impact of minor/moderate CMC changes as opposed to dissolution profile similarity assessment via statistical methods. Day 2 of the workshop highlighted the need and opportunities for global harmonization including variability, timepoint selection, role of CRDS, and statistical methods to address the ambiguity globally operating pharmaceutical companies are currently facing. Graphical 
PubDate: 2022-03-29
- An IQ Consortium Perspective on Connecting Dissolution Methods to In Vivo
Performance: Analysis of an Industrial Database and Case Studies to
Propose a Workflow-
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Abstract: Abstract Assessment of bioperformance to inform formulation selection and development decisions is an important aspect of drug development. There is high demand in the pharmaceutical industry to develop an efficient and streamlined approach for better understanding and predicting drug product performance to support acceleration of clinical timelines. This manuscript presents an effort from the IQ Formulation Bioperformance Prediction Working Group composed of members from 12 pharmaceutical companies under the IQ Consortium to develop a database around the topic of formulation bioperformance prediction and report findings from the database analysis. Six case studies described in the manuscript demonstrate how bioperformance models were used to predict in vivo performance and to provide guidance addressing questions encountered during oral solid dosage form development. The case studies also described findings of a correlation between in vitro dissolution and in vivo performance and how dissolution data can be incorporated into physiologically based biopharmaceutical modeling. Finally, a workflow for how in vitro dissolution data can be utilized to predict clinical bioperformance of oral solid dosage forms is proposed.
PubDate: 2022-03-29
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