Biologics manufacturing based on cell culture techniques represents a tremendous advance in the pharmaceutical industry. The use of biological rather than chemical processes result in unique therapeutics with greater profitability, a knowledge-based barrier to entry, and the ability to develop therapeutics targeted at specific subsets of the population (i.e., personalized medicine). Remarkable progress has been made by molecular biologists in the research and development of novel cell culture techniques. The future of the pharmaceutical industry relies heavily upon the effective management of biologics manufacturing processes. Process uncertainty and variability are inherent in biologics manufacturing. These factors are critical barriers to success which must be overcome if we are to manage biologic processes as effectively as possible. The proposed project aims to deliver an innovative product based on a high-fidelity "virtual biologics plant" which can accurately capture the dynamics and interactions of the process and allow for accurate scenario analysis. The methodologies and features proposed may provide dramatically new capability for reducing capital costs, improving yield and profitability, and allow new strides to be made towards personalized medicine. We propose a Phase II NIH SBIR project to address the critical barriers of high cost, high process uncertainty and variability. This project, aimed at developing a software product utilizing a virtual biologics plant, has the following specific aims and approaches:
Aim 1 - Enhance the management of biologics production processes by developing Rapid Response techniques within our VirtECS(R) Scheduling Engine to deal with process variability. Our approach will be to develop an intuitive interface supported by the solver for rescheduling which incorporates new information from the user on process conditions, labor availability or resource levels.
Aim 2 - Develop an effective Early Warning System as a new module for VirtECS(R) which uses Sim-Opt process simulation to forecast potential process upsets and provide a new proactive approach to process management. We will utilize simulation-optimization techniques to automatically identify "at-risk" activities, and provide analysis to identify the underlying tasks which lead to highest probability of negative events.
Aim 3 - Improve operations by creation of a web-based Schedule-centric Communications and Collaboration Tool. A web-based schedule-centric tool will be developed for desktop and mobile viewers providing up-to-date information on the state of the plant, and allow users to comment on the schedule.
Aim 4 - Integrate these features with the ability to support perfusion as well as fed-batch bioreactors in a new software product: VirtECS(R) Biologics. We will extend Phase I results to perfusion- based biologics facilities, provide new capability to optimize pooling formulations and decrease variability.

Public Health Relevance

The ultimate goal of this project is to develop a versatile software package 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 II project is to develop a powerful fully-functional prototype of such a system, based on the VirtECS(R) Scheduling Engine.

National Institute of Health (NIH)
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
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Special Emphasis Panel (ZRG1)
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Colvis, Christine
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Advanced Process Combinatorics, Inc.
West Lafayette
United States
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