AI and Machine Learning with Advanced Preclinical Cancer Models for Improved Clinical Translation

Michael Boice, PhD, Senior Director, Scientific Engagement and Key Accounts, Certis Oncology Solutions Inc.

Michael Boice, PhD, has over 20 years of experience in translational oncology drug development, from bench science to business development. As Senior Director of Scientific Engagement and Key Accounts at Certis Oncology Solutions, Michael works directly with biopharmaceutical clients to enhance their preclinical programs through a collaborative approach to scientific problem-solving and optimized study designs.

Michael’s areas of scientific expertise include the development of novel oncology therapeutics, functional genomics and rare cancers. 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.

Long H. Do, PhD, Director, Bioinformatics, Certis Oncology Solutions Inc.

Featured CertisAI™ Expert Panelist for the Q&A Period

Long H. Do, PhD, has over 10 years of experience advancing the application of bioinformatics and machine learning in preclinical drug development. He has helped advance many candidates through the drug discovery pipeline, overseeing bioinformatics departments supporting IND-enabling programs and successful enrollment into clinical trials, including a first-in-class osteoarthritis candidate (currently Phase III) and a colorectal/non-small cell lung cancer candidate (Phase I). His expertise in drug development includes the identification of mechanisms of action, pharmacodynamic response (both preclinical and clinical), machine learning-based biomarker discovery for patient selection and high throughput virtual screening to find new candidate compounds.

As Director of Bioinformatics and Data Science at Certis Oncology Solutions in San Diego, California, Dr. Do leads a team of scientists responsible for the company’s bioinformatics initiatives, including the development of machine learning algorithms to identify predictive and prognostic biomarkers, analysis pipelines for next-generation sequencing data, cloud-based high performance compute clusters and client-facing web-based applications. Dr. Do also leads Certis’ AI-directed precision oncology initiatives to guide functional testing and personalize treatments for patients diagnosed with recurrent, resistant and otherwise recalcitrant cancers.

Dr. Do holds a Bachelor of Arts degree in Molecular and Cellular Biology from the University of California, Berkeley, and a PhD in Biology with a specialization in Bioinformatics from the University of California, San Diego. He completed postdoctoral research at the University of California, San Diego, and served as a Lecturer in Bioinformatics at the same institution.