A Practical Tool for Managing the Complexity of Biologics Process Manufacturing

描述（由申请人提供）：药物开发的进展和细胞培养物生产生物化合物的开创性应用有可能开创医学的新时代。有令人难以置信的机会，开发药物，这是非常有效的治疗疾病的子集更大的人口。然而，有一些实际因素使这成为一个真实的挑战。不断上涨的成本和高质量医疗保健的挑战给制药行业带来了巨大的压力，使药物以更快的速度和更低的成本上市。对于传统的药物化合物，开发新药的时间和成本是巨大的。即使在一种成功的药物被开发出来之后，在市场向低成本的非专利化合物开放之前，也只有很短的时间窗口来收回成本。这导致了几个关键问题，但其中一个主要问题是，这些经济压力不允许制药公司经济地为非常大的患者群体以外的任何人提供药物。要为小群体开发治疗药物并开始获得个性化医疗的好处，就必须降低生物制剂工厂的成本，并最大限度地提高生产能力和运营效率。我们提出了一个第一阶段NIH SBIR项目，以解决高成本，高工艺不确定性和可变性的关键障碍。该项目旨在开发虚拟生物制剂工厂，具有以下具体目标：目标1 -应用随机优化技术为我们的VirtECS（R）调度引擎提供Sim-Opt能力，以管理过程可变性：研究并应用文献中的随机优化技术进行调度; ii）自动化大量的模拟加优化（Sim-Opt）运行，以及iii）开发分析此类数据所需的数据管理技术。目标2 -由于生物制品工艺的固有不确定性和不断适应变化的条件的需要，使VirtECS（R）调度引擎适应快速“湿启动”工艺重新调度：i）使求解器适应处理过程中任务; ii）处理初始中间存储条件; iii）开发一种方法，在发生意外事件时重新启动调度程序。目标3 -开发一种工具，以帮助可视化的结果和沟通的动态环境中的生物制品制造厂的操作：i）可视化的时间表信息通过基于Web的界面; ii）允许个人用户控制他们看到的信息，和iii）提供基于Web的能力，为用户评论预定的活动和相互沟通。 公共卫生相关性：该项目的最终目标是开发一个软件包和一套工具和流程，以优化生产先进药物的生物制剂工厂的调度。该软件包将为设计和运营制药设施提供强大的能力，从而降低消费者的成本，并使个性化医疗时代向前迈出一大步。该项目第一阶段的目的是研究基于VirtECS（R）调度引擎的这种系统的技术和财务可行性。

DESCRIPTION (provided by applicant): 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.