Q&A: embracing AI in oncology: A fireside chat with industry leaders at AACR 2024

Learn from the leaders highlighting the importance of multimodal data, AI-driven diagnostics, and the necessity of innovative approaches to meet the challenges of oncology treatment.
Authors Iker Huerga
Executive Vice President of Life Sciences Strategy & RWD, Tempus

Cristian Massacesi
Chief Medical Officer and Oncology Chief Development Officer, AstraZeneca

At the recent AACR 2024 conference, attendees had the opportunity to gain insights into the future of drug development during an engaging fireside chat in the Industry Spotlight Theater. Iker Huerga, EVP of Life Science Strategy and Real World Data at Tempus, and Cristian Massacesi, Chief Medical Officer and Chief Development Officer for Oncology at AstraZeneca, discussed the transformative impact of artificial intelligence (AI) on drug development. Their conversation highlighted the importance of multimodal data, AI-driven diagnostics, and the necessity of innovative approaches to meet the challenges of oncology treatment.

Good morning, everyone, and welcome. Thanks for joining us today. I’m Iker Huerga from Tempus, and I’m here with Cristian Massacesi to discuss how AI is shaping drug development.

Cristian Massacesi: It’s a pleasure to be here, Iker. I’m excited to talk about my journey in drug development and the innovations we’re pursuing at AstraZeneca.

Cristian, could you share your background and what brought you to this point in your career?

Cristian Massacesi: Of course. I’m originally from Italy and have always been passionate about science and human connection. After practicing oncology and feeling frustrated with the limited treatment options, I joined the pharmaceutical industry. Now, at AstraZeneca, I oversee the development of safe oncology drugs and manage a large portfolio of clinical trials.

That’s impressive. Let’s dive into precision medicine in oncology. How do you see new drug modalities influencing this field?

Cristian Massacesi: Precision medicine is the future of oncology. At AstraZeneca, we’re focused on multimodal approaches, including antibody drug conjugates, radioconjugates, and immuno-oncology. We’re also exploring bispecifics, T-cell engagers, and cell therapies. The key is to combine these modalities to tackle tumor heterogeneity and ultimately aim for curing cancer.

What advancements have enabled these new drug modalities?

Cristian Massacesi: The progress in understanding cancer biology has been pivotal, driven by genomics and the integration of multi-omic data sets. This comprehensive view of cancer cells and the immune system is what’s propelling us forward.

Absolutely. And how are AI and multimodal data impacting drug development at AstraZeneca?

Cristian Massacesi: AI and multimodal data are invaluable across the drug development journey. They’re enhancing target identification, informing investment decisions, and refining patient population selection for clinical trials.


Can you tell us more about AI-enabled diagnostics?

Cristian Massacesi: We’ve developed an AI-powered computational pathology platform that improves biomarker assessments’ precision. It’s a computer vision model that provides additional information from IHC images, which is crucial for precision medicine.

What are some challenges you’re facing with AI in drug development?

Cristian Massacesi: We need more innovation in later stages of development. Operational challenges and technology adoption in clinical settings are areas we’re actively working on.

Collaboration between tech and pharma seems essential. What makes the Tempus-AstraZeneca partnership work?

Cristian Massacesi: Shared goals, focused pilots, and a dedicated team are key. We’ve had successes with real-world evidence data and organoid work, which wouldn’t have been possible without this collaboration.

Looking ahead, what potential do you see in large language models for drug development?

Cristian Massacesi: These models could be transformative, especially in discovering new mechanisms of action and advancing precision medicine. They might help us understand the nuances within disease subtypes.

In closing, what areas need more investment to eliminate cancer as a cause of death?

Cristian Massacesi: We need to embrace change and deal with complexity. AI and data science will continue to be pivotal in understanding cancer biology, detecting cancer earlier, and developing effective combination therapies.


The session concluded with a Q&A, where the speakers addressed the integration of single-cell data and proteomics, and the customization of ADC payloads for targeted patient populations.

In summary, the fireside chat at AACR 2024 provided a fascinating glimpse into the future of oncology, with AI and multimodal data at the forefront of innovation. The insights shared by Huerga and Massacesi highlighted the importance of embracing new technologies, fostering collaborations, and investing in areas that will drive progress in cancer treatment. As the industry continues to evolve, the role of AI in drug development remains a beacon of hope for patients and healthcare providers alike.

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