Can AI predict cancer's next move before drug resistance develops?

Drug resistance remains one of the greatest challenges in oncology drug development. Most targeted therapies are designed to treat today's tumor biology, leaving researchers to react only after resistance mutations emerge. But what if artificial intelligence (AI) could help predict how cancer evolves before treatment begins?

In this episode of Early Signals, recorded live at ASCO 2026, Syneos Wael Harb, MD, Head of R&D and Scientific Strategy in Oncology, speaks with Violet Zahedi, MD, Founder and CEO of Synamics Therapeutics, about how AI, computational biology and protein modeling are being used to anticipate resistance mutations and design more durable cancer therapies.

Drawing on her experience as both a physician and biotechnology founder, Dr. Zahedi explains why oncology has traditionally taken a reactive approach to drug resistance, and how predictive AI platforms could fundamentally change the way targeted therapies are discovered, optimized and commercialized. Rather than redesigning drugs after resistance develops, her team is using machine learning, structural biology and protein modeling to predict cancer's next evolutionary move before it occurs.

The discussion explores the growing role of AI in oncology drug discovery, including its potential to accelerate lead optimization, improve compound prioritization, support biomarker-driven patient stratification and reduce the time and cost associated with developing next-generation cancer therapies. Dr. Zahedi also shares how her team validated its predictive platform using EGFR inhibitors and Aurora A kinase inhibitors, highlighting collaborations with the Mayo Clinic and presenting new findings at ASCO 2026.

Whether you're involved in oncology clinical development, precision medicine, AI-driven drug discovery or biopharmaceutical R&D, this episode explores how predictive resistance intelligence may reshape the future of cancer drug development.

In this episode, you'll learn:

· Why drug resistance remains one of oncology's greatest unmet challenges

· How AI can predict resistance mutations before they emerge

· The role of AlphaFold, computational biology and protein structure prediction in drug discovery

· How predictive resistance modeling may accelerate oncology drug development

· Opportunities to improve compound prioritization and patient stratification

· What AI could mean for the future of precision oncology and targeted therapies

The views expressed in this podcast belong solely to the speakers and do not represent those of their organization.

If you want access to more future-focused, actionable insights to help biopharmaceutical companies better execute and succeed in a constantly evolving environment, visit the Syneos Health Insights Hub. The perspectives you’ll find there are driven by dynamic research and crafted by subject matter experts focused on real answers to help guide decision-making and investment. You can find it all at https://www.syneoshealth.com/insights-hub.

Like what you’re hearing? Be sure to rate and review us!

We want to hear from you! If there’s a topic you’d like us to cover on a future episode, contact us at podcast@syneoshealth.com.

What if artificial intelligence could help remove the uncertainty from cancer treatment decisions?

Precision oncology has already transformed cancer care by matching therapies to actionable biomarkers, but today's advances are moving beyond genomics alone. By integrating molecular, clinical and pathology data at scale, AI is helping researchers and clinicians better predict treatment response, identify the right patients for therapies and accelerate the development of more personalized cancer care.

In this episode of The Syneos Health Podcast: Early Signals, Wael Harb, MD, Head of R&D and Scientific Strategy in Oncology at Syneos Health, sits down with Ezra Cohen, MD, Chief Medical Officer at Tempus AI, to discuss how multimodal data and artificial intelligence are reshaping precision oncology. Together, they explore the evolution of biomarker discovery, the growing role of AI in clinical decision-making and what it will take to bring truly individualized cancer care into routine practice.

The conversation also explores how digital pathology, real-world data and AI-enabled clinical workflows are improving patient selection, supporting guideline-directed care and laying the foundation for earlier detection and more precise treatment strategies.

Topics include:

• Why precision oncology extends beyond targeted therapies to reducing uncertainty throughout the patient journey
• How multimodal data and AI are improving biomarker discovery and treatment selection
• The promise of digital pathology and AI-powered clinical decision support
• Using real-world data to improve immunotherapy response prediction
• Closing care gaps through AI-enabled clinical workflows
• The future of minimal residual disease, early detection and personalized cancer treatment
• Why collaboration and data sharing will be essential to unlocking AI's full potential in oncology

The views expressed in this podcast belong solely to the speakers and do not necessarily represent those of their organizations.

The views expressed in this podcast belong solely to the speakers and do not represent those of their organization.

If you want access to more future-focused, actionable insights to help biopharmaceutical companies better execute and succeed in a constantly evolving environment, visit the Syneos Health Insights Hub. The perspectives you’ll find there are driven by dynamic research and crafted by subject matter experts focused on real answers to help guide decision-making and investment. You can find it all at https://www.syneoshealth.com/insights-hub.

Like what you’re hearing? Be sure to rate and review us!

We want to hear from you! If there’s a topic you’d like us to cover on a future episode, contact us at podcast@syneoshealth.com.

Less than 5% of patients participate in clinical trials today; a statistic that has remained virtually unchanged for more than two decades despite massive advances in science and technology.

In this episode of Early Signals, Dr. Wael Harb sits down with Kent Thoelke, Founder and CEO of Paradigm Health, to explore why clinical research still relies on outdated workflows and how AI, electronic health records and real-time data are creating an opportunity to fundamentally redesign the clinical trial ecosystem.

Drawing on more than 30 years in clinical research, Kent explains why simply digitizing existing processes isn't enough. Instead, he argues the future lies in embedding research directly into routine patient care, using AI to identify eligible patients before they're missed, automate manual data collection and accelerate decision-making across sponsors, investigators and regulators.

The conversation also explores Paradigm's collaboration with the FDA to pilot real-time clinical trials, where AI-generated clinical signals are transmitted directly from electronic health records to support faster regulatory review and more efficient trial execution.

Whether you're leading oncology development, clinical operations or regulatory strategy, this episode offers a practical look at how AI may reshape the future of clinical research—not by replacing people, but by removing the operational barriers that keep patients from accessing clinical trials.

In This Episode, You'll Learn:

• Why clinical trial participation has remained below 5% despite decades of innovation
• How AI and large language models are transforming patient identification and trial matching
• Why community health systems may hold the key to expanding oncology research access
• How AI-powered electronic health record integration can automate clinical trial data collection and reduce manual workload
• What the FDA's real-time clinical trial initiative could mean for sponsors, regulators and patients
• Why the future of clinical research depends on redesigning workflows rather than simply digitizing existing processes
• How AI could reshape drug development over the next five years—from smarter trial execution to more predictive development strategies

The views expressed in this podcast belong solely to the speakers and do not represent those of their organization.

If you want access to more future-focused, actionable insights to help biopharmaceutical companies better execute and succeed in a constantly evolving environment, visit the Syneos Health Insights Hub. The perspectives you’ll find there are driven by dynamic research and crafted by subject matter experts focused on real answers to help guide decision-making and investment. You can find it all at https://www.syneoshealth.com/insights-hub.

Like what you’re hearing? Be sure to rate and review us!

We want to hear from you! If there’s a topic you’d like us to cover on a future episode, contact us at podcast@syneoshealth.com.