SBIR/STTR Research Award

kinetic Flux Balance Analysis (kFBA) Framework to Simulate Multi-Cell Metabolism

Award identifier 218163c5561e85916ead951d5c3a83e136e80b0afc54ab1304bf43547ede1f1aAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$112,185

Program and phase

SBIR · Phase I

Award year

2008

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
GT LIFE SCIENCES, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
PHS2007-2
Topic code
Not reported

Research abstract

DESCRIPTION (provided by applicant): Abstract With the advancements in high throughput technologies and a growing volume of clinical data that is becoming available through public initiatives and within biopharmaceutical companies, there is an immediate an d imperative need for developing computational tools to analyze and understand this data and with the ultimate aim to predict the whole body response to environmental and genetic changes. To develop a comprehensive platform for modeling human metabolism, a n integrated dynamic and steady state framework is required for modeling metabolism at the whole-body and intracellular level. To understand and characterize such complex biological systems, computational models have been developed that fall generally with in two categories, top-down or bottom-up models. While these approaches, by themselves, do not provide an accurate representation of complex dynamic biological systems, in this proposal, we seek to integrate the top-down and bottom-up approach to simulate the dynamic human physiological conditions by development of a hybrid dynamic/steady state-framework. We have developed an integrated kinetic FBA modeling framework that allows for the integration of clinical data with intracellular metabolic network analy sis. This approach utilizes kinetic rate equation parameters and input nutrient concentrations to calculate dynamic intracellular metabolite concentrations. Using the software technology platform SimPhenyTM, we have reconstructed metabolic networks for hep atocyte, adipocyte and myocyte. In addition, the development of an integrated model of hepatocyte and adipocyte was used to characterize in distinct physiological conditions and resulted in the generation of testable hypotheses that can be investigated exp erimentally. The assessment of the scientific and computational feasibility of developing an integrated kinetic FBA approach and application to a multi-cell model framework will be an important step towards a comprehensive metabolic modeling platform in hu man disease research and drug development. PUBLIC HEALTH RELEVANCE: With the advancements in high throughput technologies and a growing volume of clinical data that is becoming available through public initiatives and within biopharmaceutical companies, th ere is an immediate and imperative need for developing computational tools to analyze and understand this data and with the ultimate aim to predict the whole body response to environmental and genetic changes. In this proposal, we seek to simulate the dyna mic human physiological conditions by development of a hybrid dynamic/steady state-framework. The assessment of the scientific and computational feasibility of developing an integrated kinetic Flux Balance Analysis (FBA) approach and application to a multi -cell model framework will be an important step towards a comprehensive metabolic modeling platform in human disease research and drug development.

Technology keywords

Not reported

Agency intelligence

Department of Health and Human Services

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