Evidence map›Paper›PMID 39651589›Full record

ArticleInternational journal of technology assessment in health care2024

New or repurposed: a novel classification system for the horizon scanning of innovative medicines.

Ross Fairbairn, Sola Akinbolade, Diarmuid Coughlan, Dapo Ogunbayo, Nick Meader, Dawn Craig

Abstract read
In one paragraph

Article in International journal of technology assessment in health care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Ross FairbairnNational Institute for Health and Care Research (NIHR) Innovation Observatory, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK.ORCID https://orcid.org/0000-0001-9017-5282
Sola AkinboladeNational Institute for Health and Care Research (NIHR) Innovation Observatory, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK.ORCID https://orcid.org/0000-0003-0464-6426
Diarmuid CoughlanPopulation Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK.ORCID https://orcid.org/0000-0002-5348-3750
Dapo OgunbayoNational Institute for Health and Care Research (NIHR) Innovation Observatory, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK.ORCID https://orcid.org/0000-0003-3189-4169
Nick MeaderNational Institute for Health and Care Research (NIHR) Innovation Observatory, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK.ORCID https://orcid.org/0000-0001-9332-6605
Dawn CraigNational Institute for Health and Care Research (NIHR) Innovation Observatory, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK.ORCID https://orcid.org/0000-0002-5808-0096

Funding

National Institute for Health and Care Research HSRIC-2016-10009/Innovation Observatory
6 · The paper itself

Abstract

objectivesIt is vital that horizon scanning organizations can capture and disseminate intelligence on new and repurposed medicines in clinical development. To our knowledge, there are no standardized classification systems to capture this intelligence. This study aims to create a novel classification system to allow new and repurposed medicines horizon scanning intelligence to be disseminated to healthcare organizations.

methodsA multidisciplinary working group undertook literature searching and an iterative, three-stage piloting process to build consensus on a classification system. Supplementary data collection was carried out to facilitate the implementation and validation of the system on the National Institute of Health and Care Research (NIHR) Innovation Observatory (IO)'s horizon scanning database, the Medicines Innovation Database (MInD).

resultsOur piloting process highlighted important issues such as the patency and regulatory approval status of individual medicines and how combination therapies interact with these characteristics. We created a classification system with six values (New Technology, Repurposed Technology (Off-patent/Generic), Repurposed Technology (On-patent/Branded), Repurposed Technology (Never commercialised), New + Repurposed Technology (Combinations-only), Repurposed Technology (Combinations-only)) that account for these characteristics to provide novel horizon scanning insights. We validated our system through application to over 20,000 technology records on the MInD.

conclusionsOur system provides the opportunity to deliver concise yet informative intelligence to healthcare organizations and those studying the clinical development landscape of medicines. Inbuilt flexibility and the use of publicly available data sources ensure that it can be utilized by all, regardless of location or resource availability.

Indexed as

Drug RepositioningTechnology Assessment, BiomedicalHumansclassificationdatabasedrug approvalpharmaceutical preparations

Identifiers

PMID39651589
PMCPMC11703622

What OpenQuestion holds

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LicenceCC BY
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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.