Evidence map›Paper›PMID 40007990›Full record

ArticleJRSM open2025

The UK's Early Access to Medicines Scheme 10 years on: an evaluation using publicly available data.

Pandora Pound, Rebecca Ram, Kathy Archibald

Abstract read
In one paragraph

Article in JRSM open, 2025. 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

3 authors.

Pandora PoundSafer Medicines Trust, Kingsbridge, TQ7 9AX, UK.ORCID https://orcid.org/0000-0001-6885-6401
Rebecca RamSafer Medicines Trust, Kingsbridge, TQ7 9AX, UK.ORCID https://orcid.org/0000-0001-9269-3841
Kathy ArchibaldSafer Medicines Trust, Kingsbridge, TQ7 9AX, UK.ORCID https://orcid.org/0009-0002-0650-5985

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To investigate the drugs and indications that have passed through the UK's Early Access to Medicines Scheme (EAMS) to date, the type of evidence the regulator considers when accepting a drug into the EAMS, and potential risks to patients. Design: Analysis of publicly available data: MHRA Public Assessment Reports; Electronic Medicines Compendium database; interactive Drug Analysis Profiles database; Eudravigilance database. Setting: United Kingdom. Participants: The 51 'scientific opinions' available on the MHRA website in June 2024. Main Outcome Measures: Public Assessment Reports, pharmacovigilance data. Results: After exclusions, there were 48 EAMS submissions, consisting of 48 indications and 32 drugs. 60% of indications were for cancer. Only 7% of EAMS submissions were based on double-blind, placebo-controlled randomised trials. The average sample size of studies conducted for the EAMS was 654. Most studies used surrogate (76%) and/or survival (57%) outcomes. Only 17% used subjective outcomes. For 17% of the indications, no ongoing studies were being conducted. Animal studies were conducted preclinically for all drugs and 35% also conducted in vitro studies. 47% of the drugs had elevated rates of suspected adverse reaction reports according to pharmacovigilance data. Conclusions: We recommend that the EAMS drugs with elevated reporting rates are reviewed, that future studies of EAMS drugs use patient-centred outcomes, that preclinical studies make greater use of human biology-based approaches, that post-approval trials are conducted, and that future reviews of the EAMS centre the experience of patients.

Indexed as

accelerated accessadverse drug reactionscancerdrug safetypharmacovigilance

Identifiers

PMID40007990
PMCPMC11848878

What OpenQuestion holds

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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.