Evidence map›Paper›PMID 34553275›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2021

A Bayesian population physiologically based pharmacokinetic absorption modeling approach to support generic drug development: application to bupropion hydrochloride oral dosage forms.

Nan-Hung Hsieh, Frédéric Y Bois, Eleftheria Tsakalozou, Zhanglin Ni, Miyoung Yoon, Wanjie Sun, Martin Klein, Brad Reisfeld, Weihsueh A Chiu

Abstract read
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Nan-Hung Hsieh *Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843, USA.
Frédéric Y Bois *Simcyp Division, Certara UK Limited, Sheffield, UK.
Eleftheria TsakalozouDivision of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Zhanglin NiDivision of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Miyoung YoonDivision of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Wanjie SunOffice of Biostatistics, Division of Biometrics VIII, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Martin KleinOffice of Biostatistics, Division of Biometrics VIII, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Brad ReisfeldChemical and Biological Engineering and School of Biomedical Engineering, Colorado State University, Fort Collins, CO, USA.
Weihsueh A ChiuDepartment of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843, USA. wchiu@tamu.edu.ORCID 0000-0002-7575-2368

Funding

Single cell, multi-parametric high throughput platform to classify endocrine disruptor potential of mixturesP42ES027704 · NIEHS · TEXAS A&M UNIVERSITY · PI Thomas Joseph McDonald · 2017 to 2026
$21.2M
Texas A&M Center for Environmental Health Research (TiCER)P30ES029067 · NIEHS · TEXAS A&M UNIVERSITY · PI Weston W Porter · 2019 to 2026
$13.0M
Enhancing the reliability, efficiency, and usability of Bayesian population PBPK modelingU01FD005838 · FDA · COLORADO STATE UNIVERSITY · PI REISFELD, BRAD · 2016 to 2017
$500k
FDA HHS U01 FD005838NIEHS NIH HHS P30 ES029067NIEHS NIH HHS P42 ES027704
6 · The paper itself

Abstract

We propose a Bayesian population modeling and virtual bioequivalence assessment approach to establishing dissolution specifications for oral dosage forms. A generalizable semi-physiologically based pharmacokinetic absorption model with six gut segments and liver, connected to a two-compartment model of systemic disposition for bupropion hydrochloride oral dosage forms was developed. Prior information on model parameters for gut physiology, bupropion physicochemical properties, and drug product properties were obtained from the literature. The release of bupropion hydrochloride from immediate-, sustained- and extended-release oral dosage forms was described by a Weibull function. In vitro dissolution data were used to assign priors to the in vivo release properties of the three bupropion formulations. We applied global sensitivity analysis to identify the influential parameters for plasma bupropion concentrations and calibrated them. To quantify inter- and intra-individual variability, plasma concentration profiles in healthy volunteers that received the three dosage forms, each at two doses, were used. The calibrated model was in good agreement with both in vitro dissolution and in vivo exposure data. Markov Chain Monte Carlo samples from the joint posterior parameter distribution were used to simulate virtual crossover clinical trials for each formulation with distinct drug dissolution profiles. For each trial, an allowable range of dissolution parameters ("safe space") in which bioequivalence can be anticipated was established. These findings can be used to assure consistent product performance throughout the drug product life-cycle and to support manufacturing changes. Our framework provides a comprehensive approach to support decision-making in drug product development.

Indexed as

BupropionDrugs, GenericAdministration, OralBayes TheoremBiological AvailabilityHumansModels, BiologicalTabletsTherapeutic EquivalencyBupropionDrugs, GenericTabletsBayesian inferenceBioequivalenceBupropion hydrochlorideGeneric drugPhysiologically based pharmacokinetic modelPopulation pharmacokinetics

Identifiers

PMID34553275
PMCPMC8604781

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.