Evidence map›Paper›PMID 42257440›Full record

ArticleClinical pharmacology and therapeutics2026

How Drug-Drug Interaction Studies Inform Drug Labeling: A Survey of US Food and Drug Administration-Approved New Molecular Entities from 1998 to 2022.

Tyler Shugg, Ashley N Springer, Yemi Gafari, Jason Xu, Patrick Marroum, Zeruesenay Desta, Nicholas R Powell, Islam R Younis

Abstract read
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Article in Clinical pharmacology and therapeutics, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Tyler ShuggDivision of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0000-0002-5784-3565
Ashley N SpringerDivision of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0009-0000-7911-2758
Yemi GafariDivision of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Jason XuThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Patrick MarroumClinical Pharmacology and Pharmacometrics, AbbVie Inc., North Chicago, Illinois, USA.
Zeruesenay DestaDivision of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0009-0001-1513-1295
Nicholas R PowellDivision of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0000-0003-4572-0733
Islam R YounisQuantitative Pharmacology and Pharmacometrics, Merck and Co., Inc., Rahway, New Jersey, USA.ORCID 0000-0001-9000-0431

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-drug interactions (DDIs) are a major cause of adverse drug events and drug inefficacy. To mitigate their clinical burden, it is essential for drug labeling to provide actionable DDI recommendations to clinicians. This investigation analyzed DDI information included in US Food and Drug Administration (FDA) labeling over the past two decades, focusing on DDI management recommendations and the information sources that served as their basis. Data elements were extracted from drug labels and clinical pharmacology reviews for new molecular entities (NMEs) approved by the FDA between 1998 and 2022. Drug labels for 76.2% of NMEs contained ≥1 DDI recommendation, yielding a total of 8,992 unique DDI pairs. Actionable management strategies were recommended for 48.5% of DDI pairs. The most common sources informing DDI recommendations were predictions based on disposition pathways (43.5%) and clinical pharmacokinetic (PK) DDI studies (36.7%). Antivirals (39.2), psychiatry (24.2), and reproduction (23.1) were the therapeutic areas with the most average recommendations per approval, while oncology (71.9%), nephrology (71.4%), and medical imaging (63.6%) were the therapeutic areas with the highest percentages of actionable recommendations. The underlying mechanisms for 75.2% of DDI recommendations involved drug-metabolizing enzymes or drug transporters, with the most common being CYP3A inducers/inhibitors (38.8% of interactions), CYP3A substrates (24.4%), and CYP2C19 inducers/inhibitors (15.8%). The extent of drug exposure changes in PK DDI studies was positively associated with actionable labeling recommendations (P < 0.001). In conclusion, our findings identify considerations to enhance the efficiency and completeness of studying DDIs and communicating DDI management recommendations in drug labeling.

Indexed as

Drug ApprovalDrug LabelingUnited States Food and Drug AdministrationDrug InteractionsDrug-Related Side Effects and Adverse ReactionsHumansSurveys and QuestionnairesUnited States

Identifiers

PMID42257440
PMCPMC13339565

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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.