Unlocking Oncology Pipelines with Next-Gen AI and Functional Data, Upcoming Webinar Hosted by Xtalks

In this free webinar, learn how to harness integrated functional multi-omics to enhance translational confidence and de-risk early-stage drug development for oncology programs. The featured speaker will discuss how to leverage key applications of AI and machine learning for extracting novel, actionable insights from complex multi-omic tumor datasets. Attendees will learn pragmatic, strategic approaches to integrate multi-omic and AI approaches into their own R&D pipelines for enhanced target identification and validation. The featured speaker will discuss the critical role of functional multi-omic data in overcoming current bottlenecks in oncology drug target discovery and development.

TORONTO, Aug. 18, 2025 /PRNewswire/ -- 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.

Join Michael Ritchie, PhD, MBA, Chief Commercial Officer, Champions Oncology, for the live webinar on Wednesday, September 3, 2025, at 11am EDT (4pm BST/UK).

For more information, or to register for this event, visit Unlocking Oncology Pipelines with Next-Gen AI and Functional Data.

ABOUT XTALKS

Xtalks, powered by Honeycomb Worldwide Inc., is a leading provider of educational webinars and digital content to the global life science, food, healthcare and medical device communities. Every year, thousands of industry practitioners (from pharmaceutical, biotechnology, food, healthcare and medical device companies, private & academic research institutions, healthcare centers, etc.) turn to Xtalks for access to quality content. Xtalks helps professionals stay current with industry developments, regulations and jobs. Xtalks webinars also provide perspectives on key issues from top industry thought leaders and service providers.

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Contact:
Vera Kovacevic
Tel: +1 (416) 977-6555 x371
Email: [email protected]

SOURCE Xtalks