Strategic Feedback Control of Pharmaceutical Crystallization Processes

药物结晶过程的策略反馈控制

• 批准号: EP/E022294/1
• 负责人: Zoltan Nagy
• 金额: $ 27.53万
• 依托单位: Loughborough University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FE022294%2F1
• 关键词: Strategic; Feedback; Control; Pharmaceutical; Crystallization

A significant proportion of materials are produced in crystalline form. Many of these crystals are obtained by nucleation and growth from solution. This type of crystal production is often referred to as industrial crystallization. Crystallization is a key separation and purification unit in most of the pharmaceutical, food and fine chemical processes, with a significant impact on the efficiency and profitability of the overall process. Over 90% of all pharmaceutical products contain active ingredients produced in crystalline form and typical raw material cost for a single batch of active pharmaceutical ingredient is $1 to $2 million. Failure to meet product specifications incurs significant costs. For efficient downstream operation (such as filtration and drying) and product effectiveness (e.g. bioavailability, tablet stability) the control of crystal purity, size distribution and shape can be critically important. The crystal size and shape affect the dissolution rate, which is an important property of crystals for medicinal use. In the pharmaceutical industry, the relative impact of drug benefit versus adverse side effects can depend on the dissolution rate. Control of crystal size and shape enables the optimization of the dissolution rate to maximize the benefit while minimizing the side effects. Poor control of crystal size and shape can also result in unacceptably long filtration or drying times, or in extra processing steps, such as recrystallization or milling, and can influence the purity of the product which is especially important in the food and pharmaceutical industries, in which the crystals are consumed. Improved control of crystallization processes offer possibilities for better product quality and improved process efficiency, for example by reducing time to market (and extending the length of time before patent expiration), and the reduction of compromised batches, therefore providing significant increase in quality of life, for example by making new drugs available more quickly and at lower cost. However, controlling crystallization is challenging due its high nonlinearity and its high sensitivity to process conditions. The aim of the research is to develop a systematic and comprehensive framework for controlling pharmaceutical crystal formation that incorporates first-principles simulation models, efficient dynamic optimization and model based control algorithms, as well as novel mathematical analysis techniques. The approach will allow to control the shape of the crystal and the overall form of the size distribution by repeatedly solving a constrained nonlinear optimization problem in real-time that will adjust the operating conditions to achieve the desired targets, and guarantees that the process operates within feasible conditions. Uncertainties in the operating conditions will be incorporated in the controller design to reduce variability of the product quality from its desired value. Measurements provided by in situ process analytical technology will be used in real-time by the feedback control strategy to estimate and predict the product quality for different operating conditions. This technique will be useful in treating several industrially important key problems in crystallization, such as controlling the formation of desired polymorphs and/or achieving consistent product quality despite of uncertainties due to scale-up. The end result of the project will be a novel methodology for crystallization control, which will provide a comprehensive framework (including model, algorithm, software and equipment) for the robust design of desired polymorph, crystal shape as well as the form of the crystal size distribution for specific applications (e.g. drug delivery and dosage, or proteomics), opening the way toward systematic crystal engineering in the future.

以结晶形式产生的材料很大一部分。这些晶体中的许多是通过溶液的成核和生长获得的。这种晶体生产通常称为工业结晶。结晶是大多数药物，食物和精细化学过程中的关键分离和纯化单元，对整个过程的效率和盈利能力产生了重大影响。超过90％的所有药品中包含以结晶形式生产的活性成分，一批活跃的药品成分的典型原材料成本为1至200万美元。不符合产品规格会带来巨大的成本。为了有效的下游操作（例如过滤和干燥）以及产品有效性（例如生物利用度，片剂稳定性），控制晶体纯度，尺寸分布和形状可能至关重要。晶体尺寸和形状会影响溶解速率，这是用于药用使用的晶体的重要特性。在制药行业中，药物益处与不良副作用的相对影响可能取决于溶解率。控制晶体尺寸和形状的控制可以优化溶解速率，以最大程度地提高益处，同时最大程度地减少副作用。对晶体尺寸和形状的控制不良也可能导致长期过滤或干燥时间，或者在额外的加工步骤（例如重结晶或铣削）中，并且可以影响产品的纯度，这在食品和制药行业中尤为重要，在食品和制药行业中，消耗了晶体。改善了结晶过程的控制提供了更好的产品质量和提高过程效率的可能性，例如，减少上市时间（并延长了专利到期前的时间长度），并减少批次的降低，因此可以使生活质量的显着提高，例如，通过使新药更快，更快地可提供新的药物。但是，由于其高非线性和对过程条件的高灵敏度，控制结晶具有挑战性。该研究的目的是开发一个系统的全面框架来控制药物晶体形成，该框架结合了第一原理模拟模型，有效的动态优化和基于模型的控制算法以及新颖的数学分析技术。该方法将通过反复在实时解决受约束的非线性优化问题来控制晶体的形状和尺寸分布的整体形式，以调整操作条件以实现所需的目标，并确保该过程在可行条件下运行。在操作条件下的不确定性将纳入控制器设计中，以从其所需值中降低产品质量的可变性。原位过程分析技术提供的测量将通过反馈控制策略实时使用，以估算和预测不同操作条件的产品质量。该技术将有助于处理结晶中的几个重要重要的关键问题，例如控制所需的多晶型物和/或达到一致的产品质量，尽管由于扩展而导致不确定性。该项目的最终结果将是一种用于结晶控制的新方法，该方法将提供一个全面的框架（包括模型，算法，软件和设备），用于强大的所需多晶型，晶体形状以及特定应用的晶体尺寸分布的形式（例如，药物输送和剂量或蛋白质组学），打开朝着系统的晶体晶体机器，未来。