Evidence map›Paper›PMID 42502229›Full record

ArticleCPT: pharmacometrics & systems pharmacology2026

DDIapp-A Web-Based Application for Static Drug-Drug Interaction Assessment.

Hirotaka Watase, Sylvie Klieber, Yorgos M Psarellis, Nikhil Pillai, Panteleimon D Mavroudis, Saroj Dhakal

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 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.

Hirotaka WataseQuantitative Pharmacology Projects D-Japan, Translational Medicine Unit, R&D, Sanofi K.K., Tokyo, Japan.ORCID https://orcid.org/0009-0006-5517-6208
Sylvie KlieberLaboratory Sciences, Translational Medicine Unit, R&D, Sanofi, Vitry-Sur-Seine, France.
Yorgos M PsarellisQuantitative Pharmacology - Pharmacometrics, Computational and AI Strategy R&D, Sanofi, Cambridge, Massachusetts, USA.ORCID https://orcid.org/0000-0003-2540-0505
Nikhil PillaiQuantitative Pharmacology - Pharmacometrics, Computational and AI Strategy R&D, Sanofi, Cambridge, Massachusetts, USA.
Panteleimon D MavroudisQuantitative Pharmacology - Pharmacometrics, Computational and AI Strategy R&D, Sanofi, Cambridge, Massachusetts, USA.ORCID https://orcid.org/0000-0002-0512-4147
Saroj DhakalQuantitative Pharmacology - Pharmacometrics, Computational and AI Strategy R&D, Sanofi, Cambridge, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work we describe the development of a web-based application for static drug-drug interaction (DDI) risk assessment in accordance with the International Council for Harmonization (ICH) M12 guidance. The app was built using the Shiny for Python framework and it employs a modular mathematical modeling structure that incorporates models for the assessment of enzyme inhibition, enzyme induction, and transporter inhibition at intestinal, hepatic, and renal levels. In addition, a "net effect" model estimates the combined impact of inhibition and induction on victim drug exposure, expressed as the area under the curve ratio (AUCR). Matrix-specific approaches for estimating unbound fractions in microsomes and hepatocytes (f

Indexed as

Drug InteractionsSoftwareHepatocytesHumansInternetModels, BiologicalRisk Assessmentdrug–drug interaction (DDI)enzyme inductionenzyme inhibitionnet effectshiny applicationtransporter inhibition

Identifiers

PMID42502229
PMCPMC13401703

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.