CMMI-EPSRC - Right First Time Manufacture of Pharmaceuticals (RiFTMaP)
Lead Research Organisation:
University of Sheffield
Department Name: Chemical & Biological Engineering
Abstract
The UK pharmaceutical industry produces 16% of the world's well-known medicines, employs more than 66,000 people (200,000 more indirectly) and contributes over £8.8 billion to the UK GVA. The current covid-19 crisis has highlighted the need for the UK and the USA to have a strong, smart pharmaceutical manufacturing base. The FDA in the USA has identified continuous pharmaceutical manufacturing as a highly promising solution to these challenges by enabling lower capital cost, smaller footprint and highly efficient facilities, which can be distributed geographically, improve national security by reducing dependency on foreign suppliers and can produce multiple products on demand with minimum risk to quality. However, the UK Government Made Smarter Review highlights that we still have a way to go to achieve a Right First Time smart manufacturing system as an enabler for the digitalization of continuous manufacturing in pharmaceutical industry.
Addressing these challenges are the domain of process systems engineers. By developing right-first-time (RFT) smart manufacturing systems incorporating Industry 4.0 concepts, we intend to address these key challenges in pharmaceutical manufacturing. Our hypothesis is that the development of a systematic framework for smart continuous pharmaceutical manufacturing can deliver key benefits to the industry including:
- Reduced time to market of new products;
- Reduced waste and increased resilience; and
- Reduced cost of manufacture.
To develop this framework, we have brought together a world leading team of process systems and pharmaceutical engineers from four universities in the UK and USA. An important and unique element of this proposal is the ability to validate state of the art models, control and optimization procedures on three cutting edge continuous manufacturing experimental platforms: (1) Consigma 25 wet granulation line at University of Sheffield (UK); (2) Dry granulation line at Purdue University (USA); and (3) Continuous direct compression line, also at Purdue.
The outcome of this project will be a framework and computational tools for optimal design of pharmaceutical processes with a real-time process management system and a flexible real-time release testing framework, all verified at pilot scale.
Addressing these challenges are the domain of process systems engineers. By developing right-first-time (RFT) smart manufacturing systems incorporating Industry 4.0 concepts, we intend to address these key challenges in pharmaceutical manufacturing. Our hypothesis is that the development of a systematic framework for smart continuous pharmaceutical manufacturing can deliver key benefits to the industry including:
- Reduced time to market of new products;
- Reduced waste and increased resilience; and
- Reduced cost of manufacture.
To develop this framework, we have brought together a world leading team of process systems and pharmaceutical engineers from four universities in the UK and USA. An important and unique element of this proposal is the ability to validate state of the art models, control and optimization procedures on three cutting edge continuous manufacturing experimental platforms: (1) Consigma 25 wet granulation line at University of Sheffield (UK); (2) Dry granulation line at Purdue University (USA); and (3) Continuous direct compression line, also at Purdue.
The outcome of this project will be a framework and computational tools for optimal design of pharmaceutical processes with a real-time process management system and a flexible real-time release testing framework, all verified at pilot scale.
Organisations
- University of Sheffield (Lead Research Organisation)
- AstraZeneca (United Kingdom) (Project Partner)
- Lannett (Project Partner)
- Purdue University (Project Partner)
- IBM (United Kingdom) (Project Partner)
- GlaxoSmithKline (United Kingdom) (Project Partner)
- Pfizer (United States) (Project Partner)
- Alexanderwerk Gmbh (Project Partner)
- Natoli Scientific (Project Partner)
- Process Systems Enterprise (United Kingdom) (Project Partner)
- Eli Lilly (United States) (Project Partner)
Publications
Bounitsis G
(2023)
33rd European Symposium on Computer Aided Process Engineering
Ferdoush S
(2023)
Fast time-resolved micro-CT imaging of pharmaceutical tablets: Insights into water uptake and disintegration.
in International journal of pharmaceutics
Monaco D
(2023)
Modelling the effect of L/S ratio and granule moisture content on the compaction properties in continuous manufacturing.
in International journal of pharmaceutics
Wang L
(2022)
Model driven design for integrated twin screw granulator and fluid bed dryer via flowsheet modelling
in International Journal of Pharmaceutics
Huang Y
(2024)
Hybrid model development and nonlinear model predictive control implementation for continuous dry granulation process
in Computers & Chemical Engineering
Bounitsis G
(2024)
Stable optimisation-based scenario generation via game theoretic approach
in Computers & Chemical Engineering
Bounitsis G
(2022)
Data-driven scenario generation for two-stage stochastic programming
in Chemical Engineering Research and Design