About this episode

Dr Andree Bates discusses the underutilization of molecular imaging data in pharma with Nijat Ahmadov, emphasizing the role of AI in transforming this data into actionable insights.

In this episode of AI For Pharma Growth, Dr Andree Bates speaks with Nijat Ahmadov, CEO of Nucs AI, about molecular imaging as one of pharma’s most underused data assets. Nijat explains why PET, CT and other molecular imaging data remain largely “untouched”: clinically valuable and created at scale, but still too often trapped in qualitative reads rather than structured, standardised data that can support decision making. As radioligand therapies expand in oncology, that gap becomes harder to ignore. The conversation explores how AI can help turn molecular imaging into computable, decision-grade data for patient selection, response monitoring and companion diagnostic strategy. Nijat argues that AI is no longer a nice-to-have in this space. Without it, pharma risks losing confidence in the outcomes that affect adoption, reimbursement and commercial success. They also discuss what it will take for AI-derived imaging biomarkers to become regulatory grade: analytical validation, reproducibility, diverse data sets, clinical validation and evidence that endpoints are meaningful, not just technically impressive. The key message is that imaging is not only diagnostic. Once structured…

People in this episode

Host: Dr Andree Bates

Guest: Nijat Ahmadov

Topics covered

• molecular imaging
• AI in pharma
• data standardization
• oncology
• radioligand therapy
• decision-making

Keywords

• molecular imaging
• AI
• pharma
• data assets
• radioligand therapy
• decision-grade data
• clinical validation

Mentioned in this episode

Organizations: Nucs AI

Products: PET, CT, radioligand therapies

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