Ward Neefs

AI & Digitalization Expert

Ward Neefs is a life-science professional with a strong focus on software, data, and digitization in the pharmaceutical sector. At QbD Group, he applies his background in bio-engineering and artificial intelligence to optimize digital systems and processes for pharma manufacturing.

Biography

Ward Neefs holds a master's degree in bio-engineering (bio-nanotechnology) and a second master’s in Artificial Intelligence, both obtained at KU Leuven University. His fascination with software and data in life sciences was born during his studies and has continued to shape his professional journey.

Since joining QbD Group, Ward has contributed to key digital transformation projects. He worked on Master Batch Record implementations for COVID vaccine production at Pfizer and later acted as a business analyst for the rollout of a new Manufacturing Execution System (MES) at Pfizer Puurs.

Currently, Ward is supporting a manufacturing-focused project at Sanofi, where he contributes to process automation and code flexibility improvements.

Ward regularly shares insights on the role of AI in pharma and has contributed to QbD’s blog. He also participated in two panel discussions on AI in medical writing at the EMWA 2024 Spring Conference in Valencia.

Ward's key areas of expertise

Artificial Intelligence in Pharma

Applying AI to improve pharmaceutical processes, systems, and decision-making.

MES & Batch Record Implementation

Digitalizing manufacturing operations through structured data and automation.

Process Automation

Improving process flexibility and software code logic in GMP-regulated environments.

Digital Health & Data Strategy

Combining engineering expertise with AI to support digital health innovations.

AI is here to stay. Yes, AI is a hype — but for good reason, and it will no doubt change society (it already has). However, there is a profound lack of understanding of how it actually works among most users. This carries some risk: it can lead to overestimating its capabilities, or to misuse due to a lack of understanding. It can also create a culture of fear, as humans tend to fear what they do not understand. It is therefore important that, moving forward, we aim to demystify AI model architectures and move away from this extreme black-box view of AI.