PathFXweb: a web application for identifying drug safety and efficacy phenotypes

Author:

Wilson Jennifer L1ORCID,Wong Mike2,Chalke Ajinkya3,Stepanov Nicholas3,Petkovic Dragutin23,Altman Russ B14

Affiliation:

1. Department of Bioengineering, Stanford University, Stanford, CA, USA

2. CoSE Computing for Life Sciences, San Francisco State University, San Francisco, CA, USA

3. Department of Computer Science, San Francisco State University, San Francisco, CA, USA

4. Department of Genetics, Stanford University, Stanford, CA, USA

Abstract

Abstract Summary Limited efficacy and intolerable safety limit therapeutic development and identification of potential liabilities earlier in development could significantly improve this process. Computational approaches which aggregate data from multiple sources and consider the drug’s pathways effects could add to identification of these liabilities earlier. Such computational methods must be accessible to a variety of users beyond computational scientists, especially regulators and industry scientists, in order to impact the therapeutic development process. We have previously developed and published PathFX, an algorithm for identifying drug networks and phenotypes for understanding drug associations to safety and efficacy. Here we present a streamlined and easy-to-use PathFX web application that allows users to search for drug networks and associated phenotypes. We have also added visualization, and phenotype clustering to improve functionality and interpretability of PathFXweb. Availability and implementation https://www.pathfxweb.net/. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Institutes of Health

Food and Drug Administration

UCSF-Stanford Center for Excellence in Regulatory Sciences and Innovation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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