About
Artificial intelligence is revolutionizing drug discovery as we know it, effectively replacing many high throughput screening studies with computer-generated insights.  By integrating predictive AI and machine learning (ML) technologies with in vivo validation, researchers can gain swift and precise drug response insights. Whether you seek to understand a candidate drug molecule’s mechanism of action or explore potential drug synergies, this approach can bring clear and compelling evidence of therapeutic efficacy to your oncology development program.

In this webinar, learn how integrating predictive AI, ML, and advanced cancer models into your drug discovery workflow may give your most promising anti-cancer agents the best chance at translational success.

Key Topics Include:
  • Discover all the ways predictive AI can be applied to accelerate oncology drug discovery and beyond.
  • Explore best practices for predictive AI platforms.
  • Delve into new preclinical and clinical case studies that pair predictive AI with in vivo validation for more insightful drug response and synergy data.
  • Experience our new virtual assistant tool in action — it uses natural language processing (NLP) to easily find tumor models with your desired genetic profiles.
Presenter
1721788135-44334ca40739047d
Michael Boice, PhD
Senior Director, Scientific Engagement and Key Accounts, Certis Oncology
Michael Boice, PhD, has over 20 years of experience in translational oncology drug development. Michael’s areas of scientific expertise include the development of novel oncology therapeutics, functional genomics and rare cancers. At Certis, he works directly with clients to enhance their discovery efforts through translational science discussions, optimizing the customer experience. He holds a PhD in Pharmacology from Weill Cornell Graduate School of Medical Sciences, Department of Pharmacology Memorial Sloan Kettering Cancer Center, Cancer Biology and Genetics.
Register To Watch Recording
First Name*
Last Name*
Email Address*
Job Title*
Organization / Company*
Country / Region*
Submit a question for the live Q&A:
utm_bmcr_source
Registration Terms
This event is hosted by the Scientist.com family of companies. Specific brands and sites associated with this event include InsideScientific. By registering and participating, you acknowledge that your personal data will be processed by the webinar platform (BigMarker) and Scientist.com. You also agree to receive email communication from InsideScientific about this webinar and other programs of similar nature. The sponsor of this webinar is Certis Oncology Solutions; by registering and participating, you acknowledge that your data will be processed in accordance with Certis Oncology Solutions' Privacy Policy. You may receive email communication from Certis Oncology Solutions about this webinar and programs of similar interest. You can withdraw your consent at any time from these communications.
Scientist.com Privacy Policy
✓ Yes, I consent to the registration terms.*
Certis Oncology Solutions Privacy Policy
✓ Yes, I consent to the registration terms.*
We use BigMarker as our webinar platform. By clicking Register, you acknowledge that the information you provide will be transferred to BigMarker processing in accordance with their Terms of Service and Privacy Policy.
Powered by BigMarker