New digital design project for pharmaceutical product development

Posted Jul 17, 2019 by Tim Sandle
A consortium of industry, academia and government have developed a new approach to digital design for pharmaceutical product and process development. Called ADDoPT, the focus is on process understanding and predictive modeling.
A nurse shows vials of anti-dengue vaccine at Parang Elementary School in Marikina  west of Manila o...
A nurse shows vials of anti-dengue vaccine at Parang Elementary School in Marikina, west of Manila on April 4, 2016
Noel Celis, AFP
ADDoPT (Advanced Digital Design of Pharmaceutical Therapeutics) is a major U.K.-led supply chain project established in response to the challenges currently faced by the pharmaceuticals and healthcare industries. These challenges include long medicine development cycles and where processes efficiency is often sub-optimal. For example, in pharma it is typical to have a limit of 300,000 defect parts per million (2 sigma); this compares less well with the automotive (6,000 per million, four sigma) and semiconductor (three per million, six sigma) industries.
The idea behind the project is that new digital design and manufacturing techniques can give pharmaceutical manufacturers a means to streamline their design, development and manufacturing processes. This is based on applying process understanding and predictive models to industrial workflows in order to enhance decision making and accelerate development.
The core aims are to enable companies to better understand of new product development risks; to lead to better decision making and resource prioritisation; to create a culture of targeted and efficient experimentation; to accelerate product development; and to better design and scale-up for those products and processes which show signs of being viable.
Partners in the project include the University of Leeds, the U.K. government, and industrial representatives Pfizer, GlaxoSmithKline, AstraZeneca and Bristol-Myers Squibb. According to European Pharmaceutical Review, the partners will help to integrate a wide range of predictive models and present industrial case studies. This will hopefully enable more targeted future experimentation, a better understanding of risk and subsequent improved design and scale-up for new products and processes.
According to Kevin Roberts, of Leeds University: "Instead of doing a lot of very expensive trial and error in the lab and in manufacturing design, ADDoPT will be developing the use of computer modeling and design tools to help plan the design and manufacturing process from raw materials through formulation, manufacturing and quality testing."
He adds: "The idea is to identify and eliminate non-viable drugs as early as possible in the process and concentrate time and resources on the right things."