AI Has Transformed Oncology Drug Development

Dr. David Spigel highlighted how artificial intelligence is reshaping cancer research and patient care.

Updated on Sept. 28, 2026 in Cancer

Bold flat-color editorial illustration depicting a lattice of modular glass beakers and geometric blocks, representing systemic oncology research. — Artificial intelligence is increasingly used to manage complex oncology drug development and match patients to appropriate clinical trials efficiently. AI Illustration. Upload story photo >

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Artificial intelligence has become a structural force in oncology drug development over the last five years. Experts now utilize the technology to navigate an increasing volume of complex therapies and clinical trials.

Why it matters

The rapid expansion of biomarker subsetting requires sophisticated tools to manage treatment options effectively. AI helps bridge the gap by matching patients to trials and therapies with greater precision.

Artificial intelligence is currently being integrated into clinical trial matching and result assessment. This shift follows five years of growth in using molecular testing to track treatment responses through minimal residual disease measures.

The players

David Spigel

David Spigel serves as the president and chief medical officer of the Sarah Cannon Research Institute.

The details

At the Patient-Centered Oncology Care conference in Nashville, Dr. David Spigel discussed how AI helps manage the vast landscape of competing cancer therapies. Future methods are expected to identify patient selection factors that extend beyond traditional genetic markers.

The Patient-Centered Oncology Care conference took place in 2026.
The structural shift in oncology drug development occurred over the past 5 years.

The Big Picture

This development follows research paradigms prioritized by institutions like the Sarah Cannon Research Institute. It signifies a transition toward AI-driven precision medicine that could fundamentally alter how experimental drugs reach the patient population.

Patients may see improved access to relevant clinical trials as AI tools better match them to emerging therapies. These technological advances aim to refine personalized care through more precise biomarker analysis and targeted treatment pathways.

The takeaway

Artificial intelligence allows researchers to process large volumes of complex data to find the right treatment for specific patient profiles. As biomarker subsetting expands, these tools will become essential for navigating modern oncology outcomes.