Evidence map›Paper›PMID 42905252›Full record

ReviewClinical pharmacokinetics2026

A Patient-Centered Approach for Drug-Drug Interaction (DDI) Assessment: Integrating Nested Clinical DDI Studies to Verify Translatability of Healthy Volunteer DDI Data, Minimize Stand-Alone Trials, and Enrich Drug Labeling.

Cheuk Fung Chan, Young Sun Scaringella, Fenglei Huang

Abstract readReview
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In one paragraph

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

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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

3 authors.

Cheuk Fung ChanClinical Pharmacology and Non-Clinical Safety Sciences, Boehringer Ingelheim Pharmaceuticals, Inc., 900 Ridgebury Rd, Ridgefield, CT, 06877, USA.
Young Sun ScaringellaClinical Pharmacology and Non-Clinical Safety Sciences, Boehringer Ingelheim Pharmaceuticals, Inc., 900 Ridgebury Rd, Ridgefield, CT, 06877, USA.
Fenglei HuangClinical Pharmacology and Non-Clinical Safety Sciences, Boehringer Ingelheim Pharmaceuticals, Inc., 900 Ridgebury Rd, Ridgefield, CT, 06877, USA. fenglei.huang@boehringer-ingelheim.com.ORCID http://orcid.org/0000-0002-0642-9401

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pharmaceutical industry often adopts a stepwise approach, assuming that drug-drug interaction (DDI) results obtained in healthy volunteers (HVs) are translatable to patients. This strategy typically begins with evaluating DDIs in HVs using probe drugs, followed by assessing interactions with potential concomitant medications, often supported by physiologically based pharmacokinetic modeling. Findings from HV studies are subsequently extrapolated to patient populations to inform drug labeling. However, this approach has limitations: (i) DDI results obtained from HV studies may not always be able be to translate to patients due to disease-related physiological changes; (ii) ethical and cost concerns arise when administering investigational drugs to HVs in clinical setting; and (iii) physiologically based pharmacokinetic modeling may be insufficient in predicting DDIs across diverse clinical scenarios. One way to address these challenges is the nested DDI study, where DDI assessments are perceptively embedded within phase II or III clinical trials. [1]. We reviewed US Food and Drugs Administration approvals over recent decades and found that nested/patient-based DDI evaluations were considered sufficient by Food and Drug Administration to support DDI labeling for 86% of new chemical entities and 92% of biologics. This design helps verify HV-to-patient translatability, reduces HV exposure, lowers operational costs, and strengthens labeling. Importantly, nested DDI studies can confirm known interactions, uncover new DDIs, and address gaps in physiologically based pharmacokinetic predictions. In conclusion, prospectively integrating nested DDI studies into development programs supports efficient risk assessment, enhances patient safety, and improves clinical relevance. Regulators and drug developers should consider nested designs as a standard component of DDI evaluation.

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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.