The excitement surrounding AI/ML in the BioPharmaceutical industry is not without reason – from identifying novel drug targets and optimizing molecule design to develop more successful lead candidates, to improving manufacturing yield, to adjusting clinical trial design for more successful uptake, the potential is limitless. But often overlooked is the potential of AI/ML within clinical development, and how process and product data capture tools can offer more opportunities to refine and reduce product development timelines.

In our earlier webinar, we shared the concepts digital transformation leaders need to manage implicitly as part of their digital transformation strategies. In this session, we examine the practical steps BioPharma organizations should take in order to instill AI/ML in their processes, the relationship between data completeness, data quality and AI/ML, and how the right tools can be leveraged to move organizations closer to their goal of a lab of the future.

“Ultimately, we need to be confident the data we are using in our AI application is of the highest possible standard.”

– Dr. Craig Williamson | Lead Platform Product Manager, Integrations Strategy, IDBS

• Practical steps to unlock AI value in scientific and clinical workflows 

• How data completeness and high-quality inputs prevent costly AI biases and errors 

• FAIR-aligned “Data Backbone” principles—enabling findability, accessibility, interoperability, and reuse 

• Why context-rich, structured data matters for AI/ML in pharma—across R&D and clinical pipelines 

• Tools and strategies to establish traceability and support lab-of-the-future ambitions 

This session is crafted for professionals leading AI and data transformation strategies in pharmaceutical and life sciences organizations: 

• R&D and Clinical Development Leaders aiming to reduce timelines and identify new drug targets 

• Informatics, Data Science & AI Teams seeking more trustworthy ML pipelines 

• Data Governance & Compliance Officers focused on regulatory data integrity 

• Lab Managers & Process Engineers working toward fully integrated, future-ready labs 

If you’re driving enterprise-scale digital transformation and AI initiatives, this session is essential.