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An integrative multi phenotype pipeline for drug evaluation pharmacogenomics and attribute prediction

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41TR001908-01
Agency Tracking Number: R41TR001908
Amount: $224,991.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 300
Solicitation Number: PA15-270
Solicitation Year: 2015
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-03-01
Award End Date (Contract End Date): 2018-08-31
Small Business Information
Del Mar, CA 92014-4134
United States
DUNS: 080191447
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (650) 283-2988
Business Contact
Phone: (650) 283-2988
Research Institution
9500 Gilman Drive, Mail Code 0934
LA JOLLA, CA 92093-0934
United States

 Nonprofit College or University

The process of drug discovery is costly and many promising compounds fail during clinical trials By then
expenses upward of $ million dollars per failed drug may have incurred and these financial risks hamper
research efforts and ultimately reduce the availability of treatment options In this research proposal we are
using systematic approaches to map the relationships between drugs genes and phenotypes i e the ability of
a drug to elicit a certain molecular response in a cell with a specific gene mutation These efforts aim at
generating three important insights
By performing these mapping systematically across many drugs and many phenotypes we generate
phenotypic profiles that can aid in the classification of new compounds enabling us to predict how well
these compounds may fare in later clinical stages thus reducing cost and risk in drug development
By characterizing existing drugs more thoroughly we can discover novel off label usages for existing
drugs thus expanding treatment options of FDA approved compounds
By understanding gene drug phenotype relationships one by one we can assemble a complete picture
of drug gene interactions an important milestone in the development of personalized
pharmacogenomics that would allow patient specific treatment planning
To accomplish these goals we will employ a novel yeast based phenotypic screening platform and use data
driven ontologies to understand the similarities between drugs in the phenotype gene space Overall this work
will move us closer to a comprehensive understanding of how phenotypes arise from the genome and how
complex relationships between genes and drugs shape our medical treatment strategies PROJECT NARRATIVE
We propose to develop a drug screening platform and database that will allow improved prediction of a drugandapos s
side effects mode of action cross reactivity and other important pharmacological attributes in the context of
gene mutations This system would reduce drug discovery cost encourage rare disease research and
ultimately lead to personalized pharmacogenomics the ability to select drugs and therapies based on the
genetic makeup of individual patients to optimize treatment results

* Information listed above is at the time of submission. *

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