Xtalks to Host Webinar on AI and Molecular Advances in Hematologic Cancer Drug Development

Apr 14, 2026
Xtalks will host a free webinar on April 30, 2026, focusing on how molecular reclassification, minimal residual disease, and AI are transforming precision hematology. Experts from NeoGenomics and Fortrea will discuss AI-driven diagnostics and molecular endpoints in cancer research.

In a press release, Xtalks announced a free webinar titled "Redefining Hematologic Malignancy Drug Development: How Molecular Reclassification, MRD, & AI is Reshaping Precision Hematology," scheduled for April 30, 2026, at 11 a.m. EDT. The event will explore how molecular reclassification and artificial intelligence are influencing precision medicine in hematologic cancers.

The session will feature Maria Prendes, Head of Scientific Affairs at NeoGenomics, and Maria Ignacia Berraondo, Executive Medical Director at Fortrea. They will discuss the use of molecular residual disease (MRD) as a surrogate endpoint in drug development and the role of AI-driven digital hematopathology in improving diagnostic precision.

The webinar aims to highlight how integrating molecular diagnostics, multi-omic data, and AI-based predictive modeling can accelerate therapeutic assessment and refine patient stratification in hematologic malignancies. Registration for the event is open through the Xtalks website.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Life AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Healthcare & Life Sciences AI AI Brief AI Brief (X)
Free newsletter

Life AI Weekly

Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.