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.
