AI-enabled technologies are revolutionizing the drug development process, from target identification and lead optimization to early biomarker validation. By leveraging big data, bioinformatics and machine learning, cancer drug development and translational research teams can identify novel biomarkers, prioritize leads and make better informed preclinical decisions. Whether a strategy involves bringing novel cancer therapies to market or repurposing existing drugs, maximizing AI in cancer research can help unlock the full potential of candidate drugs and expedite the path to approval.
In this webinar, the featured speaker will explore how in silico innovations can bring new insights to oncology translational research and the drug development process.
Join this webinar to learn about utilizing AI in cancer research to bring precision to biomarker discovery, model and patient stratification and decision-making.
Long H. Do, PhD, Director, Bioinformatics, Certis Oncology Solutions Inc.
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 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.
Who Should Attend?
Pharmaceutical scientists and cancer researchers interested in advancing translational science and improving clinical success.
What You Will Learn
Attendees will learn about utilizing AI to:
- Predict the efficacy of an investigational compound and identify the most relevant models to test
- Prioritize the most promising compounds
- Rank cancer types most likely to respond to a lead candidate
- Employ machine learning technologies to identify predictive biomarkers and uncover drug mechanisms of action
- Select optimal cancer models for in vitro and in vivo studies
- Project a compound’s potential synergistic effects when combined with commercialized or investigational drugs
Certis Oncology Solutions
Certis Oncology Solutions is a life science technology company committed to accelerating the development of new cancer therapies and realizing the promise of precision oncology. Our product is Oncology Intelligence™ — highly predictive therapeutic response data derived from advanced biological models of cancer and enhanced with AI-driven bioinformatics. Certis partners with therapeutics developers to help close the problematic translation gap between preclinical studies and clinical trials. Through more clinically relevant, well-characterized and annotated cancer models, advanced imaging technology, including x-ray irradiation with image-guided radiation therapy, and thoughtfully designed custom studies, our proprietary platform brings greater certainty to go/no-go drug development decisions.