02.12.26 -- Taking The First Steps Towards Digitalizing Biopharma Development

For many bioprocessing applications, both artificial intelligence (AI) and machine learning (ML) can be used in every phase of development to support optimization and streamline repetitive processes.

Learn more about the desire for deeper collaboration between innovator companies and their CDMO partners and why companies are seeking robust drug development capabilities in-house.

Traditional biomanufacturing relies too heavily on trial and error. By integrating AI and mechanistic models into early design, developers can overcome productivity limits and accelerate timelines.

Unplanned downtime, audit stress, and missed calibrations signal it’s time to rethink maintenance. Here are nine signs that your operation needs a modern EAM or CMMS to boost compliance and efficiency.

Discover how AI is revolutionizing biotech manufacturing as Toni and Christian reveal the story, strategy, and regulatory impact behind their innovative AI model validation cheat sheet.

Overcome data integrity challenges in your bioanalytical lab. Find out how a connected data strategy streamlines operations and enhances regulatory compliance.

See how an approach with modular N-1 perfusion strategies shortens seed train timelines and reduces facility strain — enabling upstream processes that scale efficiently for commercial manufacturing.

Investigations into viable air excursions are difficult to perform using traditional methods. Examine why a real-time viable particle counter is key to providing process improvement.

Building the right cleanroom involves critical early decisions. Read about a methodical framework ensuring flexibility, compliance, and operational readiness from initial concept through delivery.

ATMPs challenge existing E&L practices in single-use manufacturing. Gain expert insight into regulatory gaps, risk management needs, and the urgency for tailored approaches.