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Artificial Intelligence for Discovery in Life Sciences.

Sushovan Chanda¹, Silvio O Rizzoli^1,2, Ali H Shaib¹

¹Department of Neuro- and Sensory Physiology, University Medical Center Göttingen, Göttingen 37073, Germany.

Bioconjugate Chemistry

|July 1, 2026

Summary

Artificial intelligence (AI) is revolutionizing life sciences by enhancing existing methods and enabling new discoveries. AI is transforming areas from microscopy to hypothesis generation, accelerating biological insights.

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Area of Science:

Life Sciences
Bioinformatics
Computational Biology

Background:

Artificial intelligence (AI) is increasingly integrated into life sciences research.
Early applications focused on image analysis tasks like denoising and segmentation.
AI's role has expanded significantly beyond initial applications.

Purpose of the Study:

To survey the transformative impact of AI across diverse life science domains.
To highlight AI's role in both imaging and non-imaging applications.
To discuss challenges and future directions for AI in biological discovery.

Main Methods:

Review of AI applications in microscopy (fluorescence, cryo-EM, expansion microscopy).
Exploration of AI in structural biology, protein engineering, and molecular design.
Analysis of AI for hypothesis generation, experimental design, and autonomous experimentation.
Discussion of AI integration with chemistry and instrumentation.

Main Results:

AI enhances imaging modalities and links different imaging types.
AI accelerates development of tools like fluorescent probes.
Large language models and multi-agent systems are aiding literature synthesis and hypothesis generation.
AI is enabling more autonomous experimental workflows.

Conclusions:

AI is a fundamental new tool for biological discovery, extending beyond image analysis.
AI integrates measurement, design, and reasoning capabilities.
Addressing challenges in validation, interpretability, and generalizability is crucial for realizing AI's full potential.