A Practical Tool for Managing the Complexity of Biologics Process Manufacturing

描述(申请人提供)：基于细胞培养技术的生物制品生产代表着制药业的巨大进步。使用生物过程而不是化学过程产生了具有更大利润的独特疗法， 以知识为基础的进入壁垒，以及开发针对特定人群的治疗方法的能力(即个性化医学)。分子生物学家在研究和开发新的细胞培养技术方面取得了显著的进展。制药业的未来在很大程度上依赖于对生物制品制造过程的有效管理。过程的不确定性和可变性是生物制品生产中固有的。这些因素是成功的关键障碍，如果我们要尽可能有效地管理生物过程，就必须克服这些障碍。拟议的项目旨在提供一种创新产品，该产品基于高保真的“虚拟生物工厂”，可以准确地捕捉过程的动态和相互作用，并允许进行准确的场景分析。建议的方法和特征可能为降低资本成本、提高收益率和盈利能力提供显著的新能力，并允许朝着个性化药物迈出新的步伐。我们提出了NIH SBIR第二阶段项目，以解决高成本、高工艺不确定性和可变性的关键障碍。该项目旨在利用虚拟生物制药厂开发一种软件产品，具有以下具体目标和方法：目标1-通过在我们的VirtECS(R)调度引擎中开发快速响应技术来处理工艺可变性，从而加强对生物制品生产工艺的管理。我们的方法是开发一个由求解器支持的用于重新调度的直观界面，其中包含来自用户的关于工艺条件、劳动力可获得性或资源水平的新信息。目标2-开发一个有效的预警系统，作为VirtECS(R)的一个新模块，它使用Sim-Opt过程模拟来预测潜在的过程混乱，并提供一种新的主动过程管理方法。我们将利用模拟优化技术来自动识别“处于风险”的活动，并提供分析以识别导致负面事件概率最高的潜在任务。目标 3-通过创建基于Web、以日程安排为中心的通信和协作工具来改进运营。将为桌面和移动观看者开发一个以网络为中心的时间表工具，提供有关工厂状态的最新信息，并允许用户对时间表发表评论。AIM 4-将这些功能与支持灌流和进料分批生物反应器的能力集成到一种新的软件产品中：VirtECS(R)Biologics。我们将把第一阶段的结果扩展到基于灌流的生物制剂设施，提供新的能力来优化混合配方并减少可变性。

DESCRIPTION (provided by applicant): 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.