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Details of Grant 

EPSRC Reference: EP/E022294/1
Title: Strategic Feedback Control of Pharmaceutical Crystallization Processes
Principal Investigator: Nagy, Professor ZK
Other Investigators:
Researcher Co-Investigators:
Project Partners:
ABB Group AKZO Nobel AstraZeneca
BASF Cybernetica AS (Norway) University of Heidelberg
Department: Chemical Engineering
Organisation: Loughborough University
Scheme: First Grant Scheme
Starts: 08 May 2007 Ends: 07 October 2010 Value (£): 216,088
EPSRC Research Topic Classifications:
Design of Process systems Particle Technology
EPSRC Industrial Sector Classifications:
Chemicals Pharmaceuticals and Biotechnology
Related Grants:
Panel History:  
Summary on Grant Application Form
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.
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Organisation Website: http://www.lboro.ac.uk