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Potential of Artificial Intelligence to Accelerate Drug Development for Rare Diseases.
Napolitano, Giulio; Has, Canan; Schwerk, Anne; Yuan, Jui-Hung; Ullrich, Carsten.
Afiliação
  • Napolitano G; Centogene GmbH, Alboinstraße 36-42, 12103, Berlin, Germany. gnapolitano01@qub.ac.uk.
  • Has C; Centogene GmbH, Alboinstraße 36-42, 12103, Berlin, Germany.
  • Schwerk A; Beriln Institute of Health Center for Regenerative Therapies (BCRT), Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • Yuan JH; Beriln Institute of Health Center for Regenerative Therapies (BCRT), Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • Ullrich C; Beriln Institute of Health Center for Regenerative Therapies (BCRT), Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Pharmaceut Med ; 38(2): 79-86, 2024 Mar.
Article em En | MEDLINE | ID: mdl-38315404
ABSTRACT
The growth in breadth and depth of artificial intelligence (AI) applications has been fast, running hand in hand with the increasing amount of digital data available. Here, we comment on the application of AI in the field of drug development, with a strong focus on the specific achievements and challenges posed by rare diseases. Data paucity and high costs make drug development for rare diseases especially hard. AI can enable otherwise inaccessible approaches based on the large-scale integration of heterogeneous datasets and knowledge bases, guided by expert biological understanding. Obstacles still exist for the routine use of AI in the usually conservative pharmaceutical domain, which can easily become disillusioned. It is crucial to acknowledge that AI is a powerful, supportive tool that can assist but not replace human expertise in the various phases and aspects of drug discovery and development.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Doenças Raras Limite: Humans Idioma: En Revista: Pharmaceut Med Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Doenças Raras Limite: Humans Idioma: En Revista: Pharmaceut Med Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Alemanha