Evidence map›Paper›PMID 38515987›Full record

ArticleFrontiers in medicine2024

Patient listening on social media for patient-focused drug development: a synthesis of considerations from patients, industry and regulators.

Philipp Cimiano, Ben Collins, Maria Carmela De Vuono, Thierry Escudier, Jürgen Gottowik, Matthias Hartung, Mathias Leddin, Bikalpa Neupane, Raul Rodriguez-Esteban, Ana Lucia Schmidt and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
10.0field-weighted citation impact, top 1% of its field
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

15 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Informational needs in vulvar cancer and precursor conditions: a social listening study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Social Listening as a Tool to Understand Nutrition-Related Information Needs: A Case Study in Inflammatory Bowel Disease.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
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

13 authors at 5 institutions in 4 countries.

Philipp CimianoSemalytix GmbH, Bielefeld, Germany.
Ben CollinsBoehringer Ingelheim International GmbH, Ingelheim, Germany.
Maria Carmela De VuonoChiesi Farmaceutici SpA, Parma, Italy.
Thierry EscudierPistoia Alliance, Wakefield, MA, United States.
Jürgen GottowikRoche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Matthias HartungSemalytix GmbH, Bielefeld, Germany.
Mathias LeddinRoche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Bikalpa NeupaneTakeda Pharmaceuticals Co., Ltd., Cambridge, MA, United States.
Raul Rodriguez-EstebanRoche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Ana Lucia SchmidtRoche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Cornelius Starke-KnäuselSemalytix GmbH, Bielefeld, Germany.
Maarten VoorhaarBoehringer Ingelheim International GmbH, Ingelheim, Germany.
Krzysztof WieckowskiSageFiber, Ustron, Poland.
Roche (Switzerland) · CHBoehringer Ingelheim (Germany) · DEBielefeld University · DEChiesi (Italy) · ITTakeda (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients, life science industry and regulatory authorities are united in their goal to reduce the disease burden of patients by closing remaining unmet needs. Patients have, however, not always been systematically and consistently involved in the drug development process. Recognizing this gap, regulatory bodies worldwide have initiated patient-focused drug development (PFDD) initiatives to foster a more systematic involvement of patients in the drug development process and to ensure that outcomes measured in clinical trials are truly relevant to patients and represent significant improvements to their quality of life. As a source of real-world evidence (RWE), social media has been consistently shown to capture the first-hand, spontaneous and unfiltered disease and treatment experience of patients and is acknowledged as a valid method for generating patient experience data by the Food and Drug Administration (FDA). While social media listening (SML) methods are increasingly applied to many diseases and use cases, a significant piece of uncertainty remains on how evidence derived from social media can be used in the drug development process and how it can impact regulatory decision making, including legal and ethical aspects. In this policy paper, we review the perspectives of three key stakeholder groups on the role of SML in drug development, namely patients, life science companies and regulators. We also carry out a systematic review of current practices and use cases for SML and, in particular, highlight benefits and drawbacks for the use of SML as a way to identify unmet needs of patients. While we find that the stakeholders are strongly aligned regarding the potential of social media for PFDD, we identify key areas in which regulatory guidance is needed to reduce uncertainty regarding the impact of SML as a source of patient experience data that has impact on regulatory decision making.

Indexed as

patient experience datapatient-focused drug developmentreal-world evidenceregulatory decision makingsocial media listening

Identifiers

PMID38515987
PMCPMC10955474
OpenAlexW4392554236

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.