Advances in pharmaceutical drug development and the pioneering use of cell-cultures to produce biologic compounds have the potential to usher in a new era of medicine. There are incredible opportunities for development of drugs which are highly effective in treating disease for subsets of the greater population. However, there are a number of practical factors which make this a real challenge. The rising cost and challenge of quality health care has placed tremendous pressure on the pharmaceutical industry to drugs to market faster and with lower costs. For traditional pharmaceutical compounds the time and cost to develop a new drug is enormous. Even after a successful drug is developed there is only a short time window to recoup costs before the market is open to low-cost generic compounds. This leads to several critical problems, but one of the main issues is that these economic pressures do not allow pharmaceutical companies to economically deliver drugs for anything other than very large populations of patients. To develop therapeutic agents for small populations and start to reap the benefits of personalized medicine it is necessary to reduce the cost of biologics plants and to maximize the capacity and operational efficiency of manufacturing. We propose a Phase I NIH SBIR project to address the critical barriers of high cost, high process uncertainty and variability. This project, aimed at developing a virtual biologics plant, has the following specific aims:
Aim 1 - Apply stochastic optimization techniques to provide Sim-Opt capability for our VirtECS(R) Scheduling Engine to manage process variability: research and apply stochastic optimization techniques in the literature to scheduling;ii) automate large numbers of runs for simulation plus optimization (Sim-Opt), and iii) develop the data management techniques required to analyze such data.
Aim 2 - Adapt the VirtECS(R) Scheduling engine for rapid 'Wet-start'rescheduling of processes due to the inherent uncertainty of biologics processes and the need to constantly adapt to changing conditions: i) adapt the solver to handle in-process tasks;ii) handle initial intermediate storage conditions;and iii) develop a methodology to restart the scheduler when unanticipated events occur.
Aim 3 - Develop a tool to help with visualization of results and communication about operations in the dynamic environment of a biologics manufacturing plant: i) visualize schedules information via a web-based interface;ii) allow individual users to control what information they see, and iii) provide a web-based capability for users to comment on scheduled activities and communicate with each other.

Public Health Relevance

The ultimate goal of this project is to develop a software package and a set of tools and processes to optimize the scheduling of biologics plants which make advanced medicines. This package will provide powerful capabilities for designing and operating pharmaceutical facilities in a way that reduces cost for the consumer and which may allow the era of personalized medicine to take a great step forward.
The aim of this Phase I project is to investigate the technical and financial feasibility of such a system, based on the VirtECS(R) Scheduling Engine.

National Institute of Health (NIH)
National Center for Advancing Translational Sciences (NCATS)
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
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Special Emphasis Panel (ZRG1-IMST-K (14))
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Filart, Rosemarie
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Advanced Process Combinatorics, Inc.
West Lafayette
United States
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