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Probabilistic Pharmacokinetic Models for Diagnosis, Prognosis, and Personalized Treatment

Award Information
Agency: Department of Defense
Branch: Defense Health Program
Contract: W81XWH-18-C-0014
Agency Tracking Number: H17B-003-0041
Amount: $149,920.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: DHA17B-003
Solicitation Number: 2017.0
Timeline
Solicitation Year: 2017
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-03-19
Award End Date (Contract End Date): 2018-10-18
Small Business Information
1410 Sachem Place, Charlottesville, VA, 22901
DUNS: 120839477
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Dr. Michael DeVore
 (434) 973-1215
 barron@bainet.com
Business Contact
 Connie Hoover
Phone: (434) 973-1215
Email: barron@bainet.com
Research Institution
 Virginia Commonwealth University
 Andrea Publow
 410 North 12th Street
Room 642
Richmond, VA, 23298
 (804) 828-6772
 Nonprofit college or university
Abstract
Clinicians have recognized that the nature of diseases can be highly individual resulting in different patterns of onset and progression. In turn, the response of an individual to drugs is also unique and governed by a variety of factors. Pharmacokinetic models represent the movement of a drug through the body, and personalized pharmacokinetic models aim to capture the unique responses of specific individuals. The overall goal of the Phase I research effort is to develop a methodology for using probabilistic modeling in silico to construct personalized pharmacokinetic models. The team of Barron Associates and Virginia Commonwealth University will leverage prior research to accomplish this goal. A general model that represents a large cohort of individuals will first be generated based on existing data and known model structures. Any available information regarding a specific patient can then be used to personalize the model for that patient by computing conditional distributions over expected outcomes. Phase I proof-of-concept demonstrations will apply the proposed methodology to two different application areas: diabetes and traumatic brain injury. The team will also develop initial clinical strategies for how personalized pharmacokinetic models might guide diagnosis, prognosis, and treatment.

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

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