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PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development.
Wilson, Jennifer L; Racz, Rebecca; Liu, Tianyun; Adeniyi, Oluseyi; Sun, Jielin; Ramamoorthy, Anuradha; Pacanowski, Michael; Altman, Russ.
Afiliação
  • Wilson JL; Department of Bioengineering, Stanford University, Palo Alto California, United States of America.
  • Racz R; Division of Applied Regulatory Science, US Food and Drug Administration, Silver Spring Maryland, United States of America.
  • Liu T; Department of Bioengineering, Stanford University, Palo Alto California, United States of America.
  • Adeniyi O; Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America.
  • Sun J; Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America.
  • Ramamoorthy A; Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America.
  • Pacanowski M; Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America.
  • Altman R; Department of Bioengineering, Stanford University, Palo Alto California, United States of America.
PLoS Comput Biol ; 14(12): e1006614, 2018 12.
Article em En | MEDLINE | ID: mdl-30532240
ABSTRACT
Failure to demonstrate efficacy and safety issues are important reasons that drugs do not reach the market. An incomplete understanding of how drugs exert their effects hinders regulatory and pharmaceutical industry projections of a drug's benefits and risks. Signaling pathways mediate drug response and while many signaling molecules have been characterized for their contribution to disease or their role in drug side effects, our knowledge of these pathways is incomplete. To better understand all signaling molecules involved in drug response and the phenotype associations of these molecules, we created a novel method, PathFX, a non-commercial entity, to identify these pathways and drug-related phenotypes. We benchmarked PathFX by identifying drugs' marketed disease indications and reported a sensitivity of 41%, a 2.7-fold improvement over similar approaches. We then used PathFX to strengthen signals for drug-adverse event pairs occurring in the FDA Adverse Event Reporting System (FAERS) and also identified opportunities for drug repurposing for new diseases based on interaction paths that associated a marketed drug to that disease. By discovering molecular interaction pathways, PathFX improved our understanding of drug associations to safety and efficacy phenotypes. The algorithm may provide a new means to improve regulatory and therapeutic development decisions.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Algoritmos / Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos / Desenvolvimento de Medicamentos Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Algoritmos / Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos / Desenvolvimento de Medicamentos Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos