Evidence map›Paper›PMID 40990143›Full record

ArticleCPT: pharmacometrics & systems pharmacology2025

An Open-Source Framework for Virtual Bioequivalence Modeling and Clinical Trial Design.

Abdullah Hamadeh, Moriah Pellowe, Pierre Chelle, Cindy Hoi Ting Yeung, Julian Otalvaro, Walter Yamada, Jay Bartroff, Alona Kryshchenko, André Dallmann, Juri Solodenko and 4 more

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Best Practices in Physiologically Based Pharmacokinetic (PBPK) Modeling.CPT: pharmacometrics & systems pharmacology · 2026
    Review
  2. Open Systems Pharmacology Community Conference (OSP-CC) Proceedings 2025.CPT: pharmacometrics & systems pharmacology · 2026
    Article
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

14 authors.

Abdullah HamadehSchool of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada.ORCID 0000-0002-9419-1797
Moriah PelloweSchool of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada.ORCID 0000-0002-0014-5379
Pierre ChelleSchool of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada.ORCID 0000-0002-0167-4774
Cindy Hoi Ting YeungCollege of Pharmacy, Dalhousie University, Halifax, Nova Scotia, Canada.ORCID 0000-0002-2334-6376
Julian OtalvaroUniversity of Southern California, Los Angeles, California, USA.ORCID 0000-0001-5202-1645
Walter YamadaChildren's Hospital Los Angeles, Hollywood, California, USA.ORCID 0000-0003-3512-9202
Jay BartroffDepartment of Statistics & Data Sciences, University of Texas at Austin, Austin, Texas, USA.ORCID 0009-0004-6443-8391
Alona KryshchenkoCalifornia State University Channel Islands, Camarillo, California, USA.ORCID 0000-0002-5049-0293
André DallmannBayer HealthCare SAS, on Behalf of: Model-Informed Drug Development, Research & Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany.ORCID 0000-0003-1108-5719
Juri SolodenkoBayer AG, Leverkusen, Germany.ORCID 0000-0001-6922-588X
Jörg LippertBayer AG, Leverkusen, Germany.ORCID 0000-0002-0683-2874
Eleftheria TsakalozouDivision of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.ORCID 0000-0003-1993-8528
Michael NeelyUniversity of Southern California, Los Angeles, California, USA.ORCID 0000-0002-1675-8276
Andrea EdgintonSchool of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada.ORCID 0000-0002-9014-1653

Funding

FDA HHSU.S. Department of Health and Human Services
6 · The paper itself

Abstract

To establish bioequivalence (BE) of a generic test formulation with respect to a reference listed drug, it is necessary to demonstrate a comparable rate and extent to which active ingredients reach the site of action. To decrease unnecessary human testing and simulate scenarios involving specific populations or challenges with recruitment or study design, industry and regulators are increasingly considering in silico virtual bioequivalence (VBE) approaches. This tutorial introduces the VBEToolbox R package: a toolbox within the Open Systems Pharmacology framework to streamline and standardize computational VBE workflows. The package integrates in vitro and in vivo data to train pharmacokinetic models through inference of inter-individual variability from clinical data and establishment of in vitro to in vivo extrapolations. A nonparametric approach is adopted to account for uncertainties from parameter non-identifiability. The trained model is then applied to determine the study size with statistical power needed to demonstrate BE virtually. The use of the VBE tool is illustrated with two case studies. The first evaluates the VBE of petrolatum and ethylene glycol dermal formulations of testosterone by integrating in vitro skin permeation tests, vehicle/skin partitioning data, testosterone solubility data, and in vivo absorption data in a mechanistic in vitro/in vivo dermal absorption model. The second assesses the VBE of two oral bupropion formulations by integrating in vitro dissolution data in a physiologically based pharmacokinetic model. These case studies highlight essential considerations for model development, training, and extrapolation toward application for VBE assessment.

Indexed as

Clinical Trials as TopicDrugs, GenericModels, BiologicalComputer SimulationHumansResearch DesignSkin AbsorptionTestosteroneTherapeutic EquivalencyDrugs, GenericTestosterone

Identifiers

PMID40990143
PMCPMC12706426

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.