Evidence map›Paper›PMID 42249247›Full record

ArticleThe AAPS journal2026

Quantitative Estimation of Clinical Intrasubject Variability of a Pharmacokinetic Parameter.

Hao-Jui Hsu, Katrina Casteel, Samuel Yang, Vivek Purohit, Vu Le, Kazuko Sagawa

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Article in The AAPS journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Hao-Jui HsuDrug Product Design and Supply, Pharmaceutical Sciences Small Molecule, Pfizer Groton, 445 Eastern Point Road, Groton, CT, 06340, USA.ORCID http://orcid.org/0000-0001-5256-7269
Katrina CasteelDrug Product Design and Supply, Pharmaceutical Sciences Small Molecule, Pfizer Groton, 445 Eastern Point Road, Groton, CT, 06340, USA.ORCID http://orcid.org/0009-0004-2890-6960
Samuel YangDrug Product Design and Supply, Pharmaceutical Sciences Small Molecule, Pfizer Groton, 445 Eastern Point Road, Groton, CT, 06340, USA.ORCID http://orcid.org/0009-0008-8671-6005
Vivek PurohitTranslational Clinical Sciences, Pfizer Groton, Groton, Connecticut, USA.ORCID http://orcid.org/0000-0002-9019-0789
Vu LeGlobal Biometrics and Data Management, Pfizer, New York, New York, USA.ORCID http://orcid.org/0009-0009-6249-0045
Kazuko SagawaDrug Product Design and Supply, Pharmaceutical Sciences Small Molecule, Pfizer Groton, 445 Eastern Point Road, Groton, CT, 06340, USA. kazuko.sagawa@pfizer.com.ORCID http://orcid.org/0009-0006-1834-2537

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The virtual bioequivalence (VBE) approach, which employs physiologically based pharmacokinetic (PBPK) modeling in lieu of clinical bioequivalence (BE) studies, provides a valuable alternative for the pharmaceutical industry. The VBE has the potential to substantially reduce both the time and costs associated with traditional clinical BE studies. Furthermore, this approach supports ethical principles by eliminating the need to expose healthy volunteers to investigational compounds without medical benefit. Intrasubject variability (intrasubject coefficient of variation, ICV) is a main factor for balanced cross-over design BE studies in calculating the confidence intervals for the geometric mean ratio of AUC and C

Indexed as

Models, BiologicalPharmacokineticsAdministration, OralArea Under CurveBiological AvailabilityCross-Over StudiesHalf-LifeHumansPermeabilityPharmaceutical PreparationsSolubilityTherapeutic EquivalencyPharmaceutical Preparationsabsorptionbioequivalenceclinical trialsintrasubject coefficient of variationPBPKwithin subject variability

Identifiers

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Registered trials

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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.