Evidence map›Paper›PMID 42693649›Full record

ArticleCPT: pharmacometrics & systems pharmacology2026

Pharmaceutical Industry Perspectives on Exposure-Response Confounding in Large Molecule Therapeutics: Results From an IQ Consortium Survey.

Engie Salama, Manisha Lamba, Sihem Ait-Oudhia, Ellen Wang, Dorothee Semiond, Zhang Li, Tao Long, Satyendra Suryawanshi, Leticia Arrington, Wei Gao and 4 more

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

14 authors.

Engie SalamaClinical Pharmacology & Pharmacometrics, Xencor, Pasadena, California, USA.ORCID https://orcid.org/0000-0002-7009-3666
Manisha LambaPharmacometrics & Systems Pharmacology, Pfizer, Pearl River, New York, USA.ORCID https://orcid.org/0009-0001-1480-0792
Sihem Ait-OudhiaQuantitative Pharmacology and Pharmacometrics, Merck & Co, Inc., Rahway, New Jersey, USA.ORCID https://orcid.org/0000-0002-9794-8601
Ellen WangTranslational Clinical Sciences, Internal Medicine Clinical Pharmacology, Pfizer, New York, New York, USA.
Dorothee SemiondSanofi R&D, Cambridge, Massachusetts, USA.
Zhang LiQuantitative Clinical Pharmacology, Daiichi Sankyo, Basking Ridge, New Jersey, USA.
Tao LongTakeda Development Center Americas, Inc. (TDCA), Cambridge, Massachusetts, USA.ORCID https://orcid.org/0000-0002-0676-391X
Satyendra SuryawanshiBristol Myers Squibb, Princeton, New Jersey, USA.
Leticia ArringtonAmgen Inc., Thousand Oaks, California, USA.ORCID https://orcid.org/0000-0001-7272-1657
Wei GaoModerna Therapeutics, Inc., Cambridge, Massachusetts, USA.
Xiaowen GuanRegeneron Pharmaceuticals, Tarrytown, New York, USA.ORCID https://orcid.org/0000-0002-2286-0920
Hugh GiovinazzoBeOne Medicines, Ltd, San Carlos, California, USA.ORCID https://orcid.org/0009-0001-2538-7024
Dale MilesClinical Pharmacology, Genentech, South San Francisco, California, USA.ORCID https://orcid.org/0000-0002-6351-0441
David C TurnerClinical Pharmacology, Genentech, South San Francisco, California, USA.ORCID https://orcid.org/0000-0001-9242-6188

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exposure-response (ER) analyses assessing the efficacy of large molecule therapeutics are often susceptible to confounding, where associations between drug exposure and patient disease severity can obscure true ER signals and complicate dose selection. To better understand the pharmaceutical industry perspectives on this challenge, the IQ consortium conducted a comprehensive survey targeting clinical pharmacologists, pharmacometricians, and statisticians. The survey, completed by 125 individuals from 23 pharmaceutical companies, aimed to assess awareness, perceived prevalence, mitigation strategies, and the overall role of ER analyses in the context of confounding. Results revealed strong industry awareness, with 88.0% of respondents acknowledging the relevance of ER confounding. However, uncertainty regarding its pervasiveness persists, particularly in non-oncology settings (31.2% unsure). A consensus emerged on the value of dose-ranging study designs as an effective mitigation strategy (81.6% agreement). In contrast, the use of advanced statistical methods for causal inference is inconsistent (45.6% usage), and confidence in their reliability is mixed, with 32.8% of respondents expressing uncertainty and most others rating them only moderate or somewhat reliable. While the majority agreed that confounded ER analyses should be interpreted with caution (79.2%), opinions diverged regarding their value in decision-making when dose-ranging data is insufficient. This uncertainty, coupled with a recognized need for additional alignment with health authorities, led to a call for best-practice guidance (92.8% view as valuable). Overall, the survey findings highlight a need for an industry-wide common approach and the development of clear frameworks to manage and interpret ER confounding for large molecule therapeutics.

Indexed as

Drug IndustryConfounding Factors, EpidemiologicDose-Response Relationship, DrugHumansSurveys and Questionnairesconfoundingexposure‐response (ER) analysisIQ consortium surveylarge molecule therapeuticspharmaceutical industry

Identifiers

PMID42693649
PMCPMC13542575

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.