Agenda

Day 1  |  Day 2  |  Day 2

23 June

24 June

25 June

Day 3 – Session 1
Panel
12:00 – 13:15 BST

Digital transformation and pharma manufacturing

From digital twins and artificial intelligence (AI) to the Internet of Things (IoT), individual technologies are being steadily integrated into pharma manufacturing processes, but wholesale digital transformations remain elusive.  

This session will cover the big picture of digital and manufacturing, presenting strategic approaches to digitalisation, including: 

  • Practical ways to enhance digital innovation in pharma manufacturing 
  • Assessing which digital technologies will move the needle in 2026 and beyond 
  • Balancing technological progress with regulatory compliance 

Head of infusion solutions department
Global Head of AI and GenAI Practice
20/15 Visioneers
Professor of Pharmaceutical Sciences
Texas A&M University
Sponsored by
TURNITIN logo
Day 3 – Session 2
Panel
13:30 – 14:45 BST

Boosting manufacturing efficiency and reliability with AI

Moving from buzzword to bold implementations, artificial intelligence (AI) could have applications across the pharma manufacturing value chain to improve areas such as yield analytics and stock level maintenance. 

This session will look at where, and how, AI can boost to boost pharma manufacturing’s efficiency and reliability, including: 

  • Ensuring the right data foundations for AI success 
  • Identifying quick wins and developing long-term strategies 
  • AI tools that are already having a practical impact
Solutions Engineer
Turnitin
Reader in intelligent forensic data analysis
Liverpool John Moores University
Professor Dr
European University Cyprus (EUC)-Frankfurt Branch.
Day 3 – Session 3
Case study
15:00 – 16:15 BST

Making the Financial Pitch for Continuous Manufacturing: Thinking Like a CFO

The science and engineering behind continuous manufacturing (CM) has demonstrated the advantages this advanced technology has over tried and true batch manufacturing for pharmaceutical drug production. Nevertheless, adoption of CM has proceeded more slowly despite FDA support and reported benefits from various pilots and use cases. Part of what holds back further expansion of CM is uncertainty associated with capital and operating costs as well as touted efficiencies in the CM process. Making the case to senior management for CM, including financial decision makers requires an approach that takes a page from other industries to better make decisions under uncertainty with greater confidence. We’ll show how to turn your CM investment decision into a distribution of net present values (NPVs) in a simulation-based methodology that allows decision makers to invest in CM projects with greater levels of confidence.

Professor-of-the-Practice, Executive-in-Residence, SERC Director
University of Maryland