I head a specialized team of automation experts, software developers, and data specialists in the field of pre-clinical in vitro safety assessment within pharma R&D. Our core mission is to build the infrastructure for faster decision-making.

Because safety assessment sits downstream of early primary screening, we operate in a unique environment characterized by lower throughput but significantly higher biological variability and complexity. Right now, to support our team through the digital transformation happening across industry, we are actively developing comprehensive skill matrices for each researcher of our team. These matrices help team members tap into the right digital and automation tools to optimally accelerate their work.

Having worn multiple hats in this space, from managing lab automation in academia to working directly for an automation vendor, I’ve had a front-row seat to how diverse organizations adopt technology. What I’ve observed is that resistance is rarely about tech aversion, it’s about a rational, collective memory within the scientific community.

Throughout the industry's history, many labs were not successful when implementing rigid platforms that made high promises but couldn't handle high variability. Because researchers are naturally data-driven, those past sector failures instilled caution. The cultural bottleneck we face today isn't about teaching people how to click buttons, it's about actively rebuilding that trust, clarifying how their roles will evolve alongside these new tools, and demonstrating that automation exists to free up their cognitive energy for higher-level science.

True digital transformation requires moving past a purely tool-centric mindset. In my experience across different labs, simply buying advanced platforms and providing generic training without addressing the human element is a recipe for underutilized technology. For automated workflows to truly succeed, organizations should treat cultural adoption and role clarity with the exact same strategic weight as the technical implementation itself.

Our leadership team made a highly strategic decision years ago already: instead of just buying
technology, they invested in dedicated talent. By embedding experts such as automation scientists, software developers, and data experts directly alongside the laboratory scientists, leadership signalled that this transformation is an ongoing partnership. The 'human infrastructure' ensures scientists feel supported as they dive into new technology.

We rebuild trust from the ground up through three deliberate strategies:
1. Providing easy-to-use solutions: We ensure the tech is intuitive and solves their daily pain points.
2. Personality-based onboarding: We onboard people based on their unique personalities, giving eager early adopters the space to champion the systems first, while giving more hesitant scientists the time and space they need to observe and adjust.
3. Providing role clarity: We give our scientists a transparent, motivating outlook of their future roles. This is exactly why we use tool-based skill matrices. We show them that automation is a boon to their scientific judgement.

The primary bottleneck to the lab of the future is the human side of change, not technology. True innovation happens when we shift our focus from merely automating tasks to actively removing the repetitive labor that drains our scientists' cognitive energy.

The Lab of the Future for me is a highly connected data ecosystem where automated workflows handle high-variability physical tasks flawlessly. This allows data to flow directly into predictive AI insights, shifting human researchers away from manual execution and empowering them to focus entirely on earlier, clearer drug safety decisions.

I am particularly drawn to the Lab of the Future Amsterdam conference because it refuses to treat digital transformation as just a technical or engineering problem. When I attended last year, it was clear from the audience's questions that the industry is hungry for real answers regarding change management, culture, and human adoption. It is the perfect venue to share our resource-conscious philosophy and discuss how to keep scientists firmly at the centre of the digital journey.