The Rise of Autonomous Labs in Life Science

Most drug candidates fail in clinical trials. Artificial intelligence and automation promise faster, more targeted, and ultimately more successful drug development. At the Falling Walls Science Summit 2025 in Berlin, Sartorius hosted a panel of leading experts from science and industry to discuss how AI is changing drug discovery and what challenges still need to be overcome.

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AI-driven drug discovery is one of the most prominent topics in life sciences today, offering exponential progress. AI and automation enable a faster understanding of biological mechanisms and allow prospective drug candidates to be tested more quickly.  

Within five years, it’s reasonable to expect mechanistic AI models that will begin to supplement – though not fully replace – cell and animal models.

Mark Owen – Scientist at Sartorius 

The five panelists emphasized the importance of the transition toward AI-driven and automated research environments for the life science industry. “If we keep that open approach and allow everyone to get the benefits from AI machine learning, we're going to see that every company is AI first,” said Rob Harkness from Biosero. “It's not just an assistant; it's going to be embedded into everything that we do.”

Autonomous labs combine robotics and AI to create research environments capable of designing, executing, and adapting experiments with minimal human intervention. “We’re not just talking about machines performing tasks; we’re talking about systems that make decisions and adapt experiments on their own,” noted Cord Dohrmann from Evotec. This shift could dramatically speed up discovery and improve reproducibility – two areas where drug development often struggles. 

Challenges to overcome 

To enable AI and powerful algorithms in life sciences effectively, the experts stressed the importance of both data quantity and quality. “The bigger your database, the better you will be able to diagnose patients, the better you will be able to develop the next possible drug,” said Cord Dohmann. He also emphasized the need for high-quality, well-organized data to ensure strong and reliable algorithms. In the end, the combination of both factors accelerates progress in this field.  

In the future, robotics could transform workflows, delivering precision and scalability that traditional labs cannot match. “It is important to understand that robots are very good at repetitive tasks, but if it's not fully predictive what you're going to do, you need a lot of flexibility,” explained Ola Engkvist from AstraZeneca. AI can provide that missing flexibility, enabling robots to handle more complex scenarios. To make this vision a reality, AI must become much more reliable and robust to fulfill intricate tasks in life science processes. 

The role of humans 

The experts also discussed how the role of humans will drastically change in automation-driven labs. As robotics and AI take over tasks, humans’ responsibilities will shift from execution toward problem-solving and creativity. This transformation requires combining scientific expertise with technological know-how, enabling companies to accelerate automation efforts and shaping the future of work in life sciences.

With evolving skill requirements, training and education must be completely reimagined. It will be essential to provide employees with multidisciplinary training to enable innovation in this field. “The innovation cycles have become so fast on individual technologies that one has to almost try to teach what the landscape will look like when you graduate,” said Cord Dohrmann, stressing the speed of change within the industry. 

Together for better health 

To conclude the discussion on autonomous labs in life sciences, moderator Krysia Sommers from Bayer posed the question: What needs to change to break down the walls to leverage AI in drug discovery? The experts agreed that collaboration is key – harmonizing processes and connecting systems to enable progress on a broader scale. To unlock the full potential of AI and automation, the industry must establish platforms and processes that foster networking, collaboration, and the exchange of data, tools, and expertise – both among people and across systems. 

We need to get away from everyone doing things on their own and working in silos. Working together, that is the way.

Rob Harkness - BIOSERO 

About Falling Walls

Each year in November, Falling Walls invites to its Science Summit in Berlin to explore the forefront of scientific breakthroughs and emerging trends that shape our world.​ This gathering unites experts from various scientific disciplines to explore groundbreaking research and foster collaborative solutions for the challenges of our time. Sartorius regularly joins the Science Summit by co-hosting expert plenary tables on topics around the life sciences.