| アブストラクト | 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. |
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| ジャーナル名 | PLoS computational biology |
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| Pubmed追加日 | 2018/12/12 |
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| 投稿者 | Wilson, Jennifer L; Racz, Rebecca; Liu, Tianyun; Adeniyi, Oluseyi; Sun, Jielin; Ramamoorthy, Anuradha; Pacanowski, Michael; Altman, Russ |
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| 組織名 | Department of Bioengineering, Stanford University, Palo Alto California, United;States of America.;Division of Applied Regulatory Science, US Food and Drug Administration, Silver;Spring Maryland, United States of America.;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.;Department of Genetics, Stanford University, Palo Alto California, United States;of America. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/30532240/ |
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