At CES 2026, leaders from Siemens and the Life Science and Healthcare businesses of Merck KGaA, Darmstadt, Germany came together to discuss a topic that is rapidly reshaping life sciences R&D: how digital technologies, artificial intelligence, and cross-sector collaboration are transforming drug discovery.

The conversation, titled “From Possibility to Probability: Accelerating Drug Development in the Lab of the Future,” explored how predictive models, connected research platforms, and experimental science are beginning to converge into a new generation of discovery workflows.

▶️ Watch the full panel discussion below.

A Shift Toward Predictive Discovery

For decades, drug discovery has relied on cycles of hypothesis, experiment, and iteration. While computational tools have supported researchers for years, advances in AI and data science are enabling a more predictive approach.

During the panel, Laura Matz, Chief Science and Technology Officer at Merck KGaA, Darmstadt, Germany, emphasized that the question facing the industry is no longer whether digital transformation will reshape drug development.

“The question isn’t whether AI will reshape drug development — it’s how quickly we can turn possibility into probability.”

Predictive models and digital chemistry tools now allow scientists to explore molecular design and synthesis strategies in silico before committing valuable laboratory resources. The result is a growing ability to prioritize the most promising experiments earlier in the discovery process.

The Lab of the Future Is Connected

Another key theme from the discussion was the importance of integrated digital research environments.

Modern drug discovery involves a complex combination of:

• computational modeling
• experimental biology and chemistry
• laboratory automation
• data platforms and analytics

When these systems operate in isolation, scientists often spend significant time navigating fragmented workflows and disconnected data.

As Karen Madden, Chief Technology Officer at Merck KGaA, Darmstadt, Germany, noted during the panel:

“AI is no longer a digital add-on. It’s becoming embedded in the systems that power modern science.”

The lab of the future will depend on platforms capable of connecting predictive tools, experimental data, and scientific collaboration within a unified environment. These connected systems allow researchers to move more seamlessly from design to prediction to experiment to analysis.

Partnerships Are Driving Innovation

A third insight from the panel was that building these connected research ecosystems requires collaboration across industries.

Advances in digital discovery rarely come from a single technology provider. Instead, progress increasingly emerges from partnerships that combine expertise in:

• scientific software and data platforms
• computational modeling and AI
• chemistry and materials science
• laboratory instrumentation and automation

The discussion highlighted how collaboration between technology developers, research organizations, and scientific suppliers is helping accelerate the development of more integrated and data-driven discovery workflows.

Looking Ahead

The ideas discussed at CES reflect a broader transformation already underway across life sciences R&D.

Predictive science, connected research platforms, and collaborative innovation are converging to reshape how scientists explore chemical space, design molecules, and plan experiments.

As these capabilities continue to evolve, the ability to move from possibility to probability — from promising ideas to confident experimental decisions — will become an increasingly powerful driver of innovation in drug discovery.