New digital design and manufacturing techniques offer pharmaceutical manufacturers the possibility of a systems-based, digital approach to substantially streamline their design, development and manufacturing processes. The ADDoPT collaborative consortium has been working to explore how emerging process understanding and predictive models can beapplied and embedded within industrial workflows to enhance decision making and accelerate development.

IN AN INCREASINGLY digitalised world, it is evident that pharmaceutical manufacture is still built on heuristics. Process and product development is mostly achieved by "making and testing", development cycles are long and processes efficiency is sub-optimal. As the sector transitions from the era of "blockbuster" drugs and market expectations change with the drive towards personalised medicines, sector leaders clearly recognise the need to transform the capability, flexibility and speed of their development workflows and supply chains. ADDoPT1 (Advanced Digital Design of Pharmaceutical Therapeutics) is a major UK-based supply chain project established in response to the challenges faced by the industry. The four-year, £20.4m government-industry-academia collaboration has enabled partners from across the pharma value chain to define a system for top-down, knowledge-driven digital design and digital operation for drug products and their manufacturing processes. The aim is to integrate a wide range of predictive models and insight from industrial case studies at four major pharmaceutical companies, allowing more targeted future experimentation, a better understanding of risk and subsequent improved design and scale-up for robust products and processes. In the words of the former chair of the Medicines Manufacturing Industry Partnership, ADDoPT’s objective is to "create virtual medicine manufacturing systems to make sure they are effective and efficient before creating them in the real world".2

-----------------------------------------------------------------------
Editor's Note:

If you have any suggestion to the content, 

please email: Julia.Zhang@ubmsinoexpo.com