Accelerate Upstream Process Development Using Hybrid Modeling, Upcoming Webinar Hosted by Xtalks

In this free webinar, learn how hybrid modeling can bring predictive decision-making earlier into upstream process development. The featured speakers will discuss how historical bioreactor data and molecule-specific experiments can support clone-specific process optimization and earlier control of product-quality attributes. Attendees will also explore case studies showing how model-based approaches can reduce experimental work and shorten development timelines.

TORONTO, Nov. 3, 2026 — As biopharmaceutical programs advance under increasingly compressed timelines, upstream development teams face pressure to deliver optimized, quality-targeted processes earlier. Early decisions still rely heavily on platform knowledge and expert judgment, while historical bioreactor data is rarely leveraged quantitatively. This webinar will explore how hybrid modeling can bring predictive, model-based decision-making into upstream development earlier, helping optimize processes during clone selection.

Central to this approach is knowledge transfer: reusing data from prior programs to build a reliable hybrid model when new-program data is still scarce. The session will examine how relevant historical programs are identified using a multivariate strategy that scores candidate datasets on product-quality similarity, process-performance similarity and design-space coverage. These models can then support in-silico, clone-specific optimization. Because the model is established early, its predictions can be confirmed within experiments already planned in the workflow, reducing the need for dedicated optimization studies.

Through two case studies, the featured speakers will discuss how the same strategy adapts to different programs and quality objectives. The first, a monoclonal-antibody intermediate of an antibody-drug conjugate (ADC) developed under a compressed resupply timeline, used model-guided optimization to reduce acidic variants while maintaining titer without additional experiments. The second, another ADC intermediate at first-in-human development, applied the same approach to optimize glycan quality attributes. Together, these examples demonstrate how model-based optimization can control multiple product-quality attributes earlier in development.

Attendees will understand how integrating historical data, hybrid models and a small amount of molecule-specific experimentation can replace sequential, intuition-driven optimization with model-based decision-making. This approach reduced development timelines by up to six months and experimental runs by up to 50% relative to conventional workflows.

Register for this webinar to learn how hybrid modeling can accelerate upstream process development, reduce experimental requirements and support earlier control of product-quality attributes.

Join experts from Bristol Myers Squibb, Juan C. Gonzalez Rivera, PhD, Principal Scientist in Biologics Upstream Process Development; and Yikun Huang, PhD, Senior Scientist in Upstream Process Development within Biologics, for the live webinar on Tuesday, November 17, 2026, at 11am EST (5pm CET / EU-Central).

For more information, or to register for this event, visit Accelerate Upstream Process Development Using Hybrid Modeling.

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

SOURCE Xtalks