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Computer-Assisted Strain Construction And Development Engineering (CASCADE)

Award Information
Agency: Department of Defense
Branch: Office for Chemical and Biological Defense
Contract: W911NF-07-C-0041
Agency Tracking Number: C061-107-0045
Amount: $749,520.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: CBD06-107
Solicitation Number: 2006.1
Solicitation Year: 2006
Award Year: 2007
Award Start Date (Proposal Award Date): 2007-04-02
Award End Date (Contract End Date): 2008-04-02
Small Business Information
5405 Morehouse Drive Suite 210
San Diego, CA 92121
United States
DUNS: 071401090
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Tom Fahland
 Senior Research Scientist
 (858) 362-8557
Business Contact
 Christophe Scilling
Title: President
Phone: (858) 862-8550
Research Institution

The recent advances of modern high-throughput genomic technologies have resulted in a large number of fully sequenced microbial organisms. The construction of these comprehensive metabolic models serves many purposes including encapsulating all the data and allowing for in silco experiments to be performed that can drive experimental work and aid in strain development and optimization. The creation of a full metabolic reconstruction requires a significant amount of manual work; an automated procedure for rapidly developing metabolic models would be extremely valuable for the biotechnology field. We intend to use our recently developed automated metabolic model construction system and apply this to build a complete predictive model of Pichia pastoris for use in recombinant protein production. We will perform dedicated experiments to complete and validate the in silico metabolic model of Pichia pastoris and use this model to develop metabolic intervention strategies and optimize the process feed strategy to increase production of a protein of interest to the DOD. This combined computational and experimental methodology takes advantage of the simulation and predictive powers of the complete genome-scale metabolic model to drive experimentation and create rational-based metabolic intervention changes and process development changes.

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

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