SBIR Phase II: Enterprise Decision making using Activity Interaction technology

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 1052566
Agency Tracking Number: 1052566
Amount: $500,000.00
Phase: Phase II
Program: SBIR
Awards Year: 2011
Solicitation Year: 2011
Solicitation Topic Code: Phase II
Solicitation Number: N/A
Small Business Information
1250 Addison St, Ste 107, Berkeley, CA, 94702-1706
DUNS: 005557788
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 David Zhang
 (510) 725-8952
 david.zhang@bio-g.com
Business Contact
 David Zhang
Title: BS
Phone: (510) 725-8952
Email: david.zhang@bio-g.com
Research Institution
 Stub
Abstract
This Small Business Innovation Research (SBIR) Phase II project seeks to further research and implement a Network Algorithm for efficiently running large-scale network simulations and using those simulations to perform enterprise planning and risk analysis. The company's algorithms (and associated early-release software) have been shown to run supply chain models one order of magnitude faster, with one order of magnitude more complexity, than current simulation models commonly deployed. Bioproduction Group has created a simulation methodology that meaningfully links together highly-detailed operational level models with its large network-scale model. Each operations simulation is linked by network relationships such as supply and demand, product path flows, and inventory holding centers. Bioproduction Group has received contracts with several biotech firms to implement advanced prototypes of this research in biopharmaceutical manufacturing as they come online. The goal is to use this simulator to reduce biopharmaceutical inventory levels across the industry by 10% or more, while reducing risk across the manufacturing network. If successfully deployed in a large enterprise, it is believed that this inventory reduction would have a yearly return of more than $20mm per organization. The technology has the potential to be used across the biopharmaceutical industry to increase quality of care to the patient as well as reduce manufacturing costs. These goals have significant direct flow-on savings benefits to the hundreds of thousands of patients across the entire public and private healthcare sector.

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

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