How can functional multi-omic tumor data enable AI-driven target discovery and translational confidence?
For pharma R&D and data science leaders, the demand for precise translational decisions has never been higher. However, the datasets currently available frequently fall short; they’re fragmented, lack the necessary depth or don’t accurately reflect real patient biology. This fundamental shortage of integrated, functional and clinically relevant data creates a significant bottleneck, impacting everything from the efficacy of internal AI models to the reliability of biomarker hypotheses.
In this case-driven webinar, the featured speaker shares how a multi-disciplinary team harnessed a deeply profiled, functionalized tumor dataset to uncover and validate a novel oncology target: Vacuolar Protein Sorting–associated protein 4 (VPS4A/B).
The discovery process began with a gene knockdown screen performed in 3D ex vivo cultures derived from clinically annotated patient-derived xenograft (PDX) tumors. Functional outcomes were integrated with deep transcriptomic data to train a machine learning model that accurately predicted VPS4 sensitivity. This approach led to the identification of CHAMP-002, a chemotype that triggered potent immunogenic responses and showed efficacy across multiple tumor types, including in combination with PD-1 blockade.
This webinar will outline a framework for integrating deep tumor data into translational workflows that incorporate:
- AI/ML-ready datasets that are exportable, structured and grounded in fundamental tumor biology
- Integrated multi-modal layers, clinical history, omics, phenotypic data and drug response, all within a single, coherent system
- Data that maps to real-world patient cohorts, not abstract in vitro models
- Translational alignment for internal decision-making, target selection, biomarker validation and early development strategy
Teams struggling with limitations with public datasets, failed to reproduce internal models or are looking to advance precision oncology initiatives, this webinar offers a window into how functionalized tumor data can drive more innovative R&D.
Register for this webinar to learn how functional multi-omic data and AI integration can accelerate cancer target discovery.
- AI ,
- AI Drug Development ,
- AI Technology ,
- Artificial Intelligence ,
- Bioanalytical Testing ,
- Biomarkers ,
- Cancer ,
- CRO ,
- Drug Development ,
- Drug Discovery ,
- Drug Target ,
- Drug Target Identification ,
- Multiomics ,
- Oncology ,
- Oncology Drug Development ,
- Oncology Drugs ,
- Other Software ,
- Pre-Clinical ,
- Precision Medicine ,
- Translational Research ,
- Tumor
Speaker
Michael Ritchie, PhD, MBA, Chief Commercial Officer, Champions Oncology
Michael Ritchie, PhD, MBA, joined Champions Oncology in July of 2014 and currently serves as Chief Commercial Officer, overseeing all aspects of commercial development. Prior to joining Champions, he worked in the oncology research unit at Pfizer, managing therapeutic development programs in the antibody-drug conjugate space and developing novel therapeutic antibody programs. Dr. Ritchie received an MBA from New York University, a doctorate in Biochemistry from Temple University School of Medicine and completed a postdoctoral fellowship in Neuroscience at Harvard Medical School.
Message PresenterWho Should Attend?
This session is tailored for senior biopharma professionals involved in:
- AI/ML Model Development for drug discovery and preclinical strategy
- Translational Research & Precision Medicine leadership
- Biostatistics, Bioinformatics and Oncology Data Science
- Target discovery, biomarker strategy and external innovation
- Clinical Development and Companion Diagnostic Strategy
Audience Job Titles:
- Vice President, Head of Statistical Sciences
- Associate Vice President for Clinical Development
- Senior R&D Director of Medical Artificial Intelligence
- Global Chief Information Officer
- Senior Director, R&D Strategic Resourcing
- Vice President, Data and AI Convergence R&D
- Executive Director, Biostatistics
- Executive Director, Healthcare AI and Data Innovation
- VP, Innovation, Architecture and Infrastructure
- Executive Director, External Innovation
- Vice President of Quantitative Medicine and Genomics
- Vice President, Global Head of Precision Medicine and Translational Research and Companion Diagnostics
- Senior Director, Innovation
- Vice President, Biotherapeutics Discovery
What You Will Learn
Webinar attendees will leave with a strategic understanding of:
- How to harness integrated functional multi-omics to enhance translational confidence and de-risk early-stage drug development for oncology programs
- How to leverage key applications of AI and machine learning for extracting novel, actionable insights from complex multi-omic tumor datasets
- Pragmatic, strategic approaches to integrate multi-omic and AI approaches into their own R&D pipelines for enhanced target identification and validation
- The critical role of functional multi-omic data in overcoming current bottlenecks in oncology drug target discovery and development
Xtalks Partner
Champions Oncology
Champions Oncology is a global preclinical and clinical research services provider that offers end-to-end oncology R&D solutions to biopharma organizations. With the largest and most annotated bank of clinically relevant patient-derived xenograft (PDX) and primary hematological malignancy models, Champions delivers innovative highest-quality data through proprietary in vivo and ex vivo platforms. Through its large portfolio of cutting-edge bioanalytical platforms, groundbreaking data platform and analytics, and scientific excellence, Champions enables the advancement of preclinical and clinical oncology drug discovery and development programs worldwide. For more information, please visit www.ChampionsOncology.com.
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