PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development

• Published in: PLoS computational biology 2018-12, Vol.14 (12), p.e1006614
• Main Authors: Wilson, Jennifer L, Racz, Rebecca, Liu, Tianyun, Adeniyi, Oluseyi, Sun, Jielin, Ramamoorthy, Anuradha, Pacanowski, Michael, Altman, Russ
• Format: Article
• Language: English
• Subjects: Algorithms; Binding sites; Bioengineering; Biology and Life Sciences; Computational Biology; Computer and Information Sciences; Databases, Pharmaceutical; Decision Making; Disease; Drug and Narcotic Control; Drug Approval; Drug Development - legislation & jurisprudence; Drug Development - standards; Drug Development - statistics & numerical data; Drug Discovery - legislation & jurisprudence; Drug Discovery - standards; Drug Discovery - statistics & numerical data; Drug efficacy; Drug Interactions; Drug Repositioning; Drug-Related Side Effects and Adverse Reactions; Drugs; Effectiveness; Enzymes; Food; Genes; Genotype & phenotype; Humans; Kinases; Medicine and Health Sciences; Molecular interactions; Peripheral neuropathy; Pharmaceutical industry; Pharmacology; Phenotypes; Product safety; Proteins; Research and Analysis Methods; Safety; Side effects; Signal transduction; Signaling; Studies; Systematic review; Treatment Outcome; United States; United States Food and Drug Administration
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1006614

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.