Evidence map›Paper›PMID 40903672›Full record

ReviewThe AAPS journal2025

Commentary and Review on Prospective Prediction of Bioequivalence of Oral Dosage Forms using Compendial Dissolution Testing and PBPK Modeling.

Kazuko Sagawa, Priyanka Thipsay

Abstract readReview
PubMed Publisher
In one paragraph

Review in The AAPS journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Kazuko SagawaPharmaceutical Science, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, Connecticut, 06340, USA. kazuko.sagawa@pfizer.com.ORCID 0009-0006-1834-2537
Priyanka ThipsayPharmaceutical Science, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, Connecticut, 06340, USA.ORCID 0000-0003-4792-2574

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A virtual bioequivalence (VBE) approach utilizing physiologically based pharmacokinetic (PBPK) modeling presents a compelling alternative for pharmaceutical industries. This method can significantly reduce the time and cost associated with clinical bioequivalence (BE) trials while minimizing the risk of detecting a type II error (a false negative), as well as a type I error (a false positive). Additionally, it aligns with ethical considerations by obviating the need to expose healthy volunteers to investigational drugs. To secure a biowaiver through the VBE approach, it is essential to translate compendial in vitro dissolution data into pharmacokinetic (PK) parameters using PBPK modeling to evaluate BE. This article reflects three concepts: compendial dissolution test, PBPK modeling, and BE, reviewing their historical development and current research. It highlights the gaps and challenges and discusses potential future opportunities to strengthen clear linkage among three concepts. A deeper understanding of the mechanisms and mathematical translation of dosage form disintegration and API particle dissolution can enhance the prediction of dosage form performance in both in vivo and in vitro settings. Future advancement of PBPK modeling should incorporate these developments to improve confidence in correlating compendial dissolution data with quantitative risk assessments of BE outcomes.

Indexed as

Drug LiberationModels, BiologicalAdministration, OralDosage FormsHumansSolubilityTherapeutic EquivalencyDosage Formsbioequivalencecompendial dissolutionin vitro dissolutionPBPK modelvirtual BE

Identifiers

What OpenQuestion holds

Textmetadata
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.