The Changing Role of Analytical Science in Drug Discovery

How complex biological models, larger datasets, and laboratory automation are shaping drug discovery decisions

By
James Strachan
August 27, 2026
3 min

The Analytical Scientist

Objective:

To discuss the evolving role of analytical science in drug discovery, including the challenges and opportunities presented by more physiologically relevant models and automation, as well as the trade-offs involved.

Approach:

Data Generation: Analytical science is increasingly generating larger datasets that inform decisions earlier in the drug discovery process.
Complex Models: The use of more physiologically relevant models introduces variability and challenges in data consistency and reproducibility.
Automation: Automation is utilized to manage variability and improve the practicality of complex models in drug discovery.

Key Findings:

Advancements in analytical technologies enhance data consistency and reliability.
Complex models introduce greater variability and challenges in scaling and maintaining data reproducibility.
Simpler assays can provide valuable insights early in the discovery process.

Interpretation:

Balancing biological complexity with practical assay design is crucial, with the choice of model depending on the specific scientific question and stage of discovery.

Limitations:

Complex models introduce inherent variability that cannot be fully controlled.
More sophisticated models require advanced handling and maintenance, impacting data reproducibility.