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A Computational Drug Repositioning Method for Rare Diseases

Part of the Lecture Notes in Computer Science book series (LNCS,volume 13259)

Abstract

Rare diseases are a group of unusual pathologies in the world population, hence their name. They are considered the great neglected field of pharmaceutical research. To date, over 6,000 rare diseases have been identified and most of them lack treatment. The fact that they are so rare in the population does not encourage research efforts since their treatments are not in high demand. This work aims to analyze potential drug repositioning strategies that could be applied to these types of diseases. That is, discovering if existing drugs currently used for treating certain diseases can be employed to treat rare diseases. This process has been carried out using computational methods that compute similarities between rare diseases and other diseases, considering biological characteristics such as genes, proteins, and symptoms. The obtained potential drug repositioning hypotheses have been contrasted with related clinical trials found in scientific literature published to date.

Keywords

  • Rare diseases
  • Orphan diseases
  • Drug repositioning
  • Computational biology

Universidad Politécnica de Madrid.

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Notes

  1. 1.

    https://www.eurordis.org.

  2. 2.

    https://disnet.ctb.upm.es.

  3. 3.

    https://www.orpha.net.

  4. 4.

    https://medal.ctb.upm.es/internal/gitlab/b.otero/dr-for-rare-diseases.

  5. 5.

    https://www.nlm.nih.gov/research/umls/index.html.

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Correspondence to Alejandro Rodríguez-González .

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Otero-Carrasco, B., Prieto Santamaría, L., Ugarte Carro, E., Caraça-Valente Hernández, J.P., Rodríguez-González, A. (2022). A Computational Drug Repositioning Method for Rare Diseases. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence. IWINAC 2022. Lecture Notes in Computer Science, vol 13259. Springer, Cham. https://doi.org/10.1007/978-3-031-06527-9_55

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  • DOI: https://doi.org/10.1007/978-3-031-06527-9_55

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