AI may be dominating the conversation, but systems integration could be the bigger challenge for pharma manufacturers. This article explores why connecting fragmented systems, data and processes is becoming essential to building a smarter, more AI-ready manufacturing environment.
Pharma manufacturers have more data than ever, but collecting it is only the beginning. This article explores how manufacturers are shifting their focus from building digital capabilities to using data to solve real problems, improve decision-making and deliver measurable value.
AI is moving from theory to practical application in pharma manufacturing. From predictive maintenance and faster root-cause analysis to helping operators access information, manufacturing leaders are increasingly focused on where AI is delivering real value in GMP environments – and what it takes to implement it successfully.
Based on industry research conducted for ManuPharma 2027, this article explores the challenges currently at the top of the manufacturing and technical operations agenda. From finding practical applications for AI and getting more value from manufacturing data to improving batch release, managing ageing assets and strengthening European manufacturing, the focus is firmly on making transformation work in practice.
It also looks at the people behind that transformation – including the skills, adoption and workforce challenges that come with greater automation and digitalisation – and why manufacturers are increasingly looking to their peers for real-world examples of what works.