Evidence map›Paper›PMID 36141396›Full record

ArticleHealthcare (Basel, Switzerland)2022

Repositioning Drugs for Rare Diseases Based on Biological Features and Computational Approaches.

Belén Otero-Carrasco, Lucía Prieto Santamaría, Esther Ugarte Carro, Juan Pedro Caraça-Valente Hernández, Alejandro Rodríguez-González

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. 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

5 authors.

Belén Otero-CarrascoCentro de Tecnología Biomédica, Universidad Politécnica de Madrid, Boadilla del Monte, 28660 Madrid, Spain.ORCID 0000-0001-7315-2257
Lucía Prieto SantamaríaCentro de Tecnología Biomédica, Universidad Politécnica de Madrid, Boadilla del Monte, 28660 Madrid, Spain.ORCID 0000-0003-1545-3515
Esther Ugarte CarroCentro de Tecnología Biomédica, Universidad Politécnica de Madrid, Boadilla del Monte, 28660 Madrid, Spain.ORCID 0000-0003-1450-7518
Juan Pedro Caraça-Valente HernándezETS Ingenieros Informáticos, Universidad Politécnica de Madrid, Boadilla del Monte, 28660 Madrid, Spain.ORCID 0000-0002-8681-0682
Alejandro Rodríguez-GonzálezCentro de Tecnología Biomédica, Universidad Politécnica de Madrid, Boadilla del Monte, 28660 Madrid, Spain.ORCID 0000-0001-8801-4762

Funding

Ministerio de Ciencia e Innovación ID2021-122659OB-I00Ministerio de Ciencia e Innovación (Ayudas FPI) FPI PRE2019-090912Ministerio de Ciencia, Innovación y Universidades RTI2018-795 094576-A-I00Programa de fomento de la investigación y la innovación (Doctorados Industriales) de la Comunidad de Madrid IND2019/TIC-17159
6 · The paper itself

Abstract

Rare diseases are a group of uncommon diseases in the world population. To date, about 7000 rare diseases have been documented. However, most of them do not have a known treatment. As a result of the relatively low demand for their treatments caused by their scarce prevalence, the pharmaceutical industry has not sufficiently encouraged the research to develop drugs to treat them. This work aims to analyse potential drug-repositioning strategies for this kind of disease. Drug repositioning seeks to find new uses for existing drugs. In this context, it seeks to discover if rare diseases could be treated with medicines previously indicated to heal other diseases. Our approaches tackle the problem by employing computational methods that calculate similarities between rare and non-rare diseases, considering biological features such as genes, proteins, and symptoms. Drug candidates for repositioning will be checked against clinical trials found in the scientific literature. In this study, 13 different rare diseases have been selected for which potential drugs could be repositioned. By verifying these drugs in the scientific literature, successful cases were found for 75% of the rare diseases studied. The genetic associations and phenotypical features of the rare diseases were examined. In addition, the verified drugs were classified according to the anatomical therapeutic chemical (ATC) code to highlight the types with a higher predisposition to be repositioned. These promising results open the door for further research in this field of study.

Indexed as

biomedical informaticsDISNET knowledge basedrug repositioningrare diseases

Identifiers

PMID36141396
PMCPMC9498751

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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.