In this episode of SciBud, join your host Rowan as we explore the groundbreaking introduction of TMBquant, a powerful new tool in precision oncology that leverages artificial intelligence to enhance the quantification of tumor mutation burden (TMB). Discover why TMB is crucial for predicting patient responses to immunotherapy and how TMBquant outperforms traditional methods, achieving impressive results across various cancer types, particularly in non-small cell lung cancer and nasopharyngeal carcinoma. We’ll discuss the tool's innovative features, its benchmarking against nine leading variant callers, and the importance of transparency in scientific research. While TMBquant promises to advance our understanding of tumor aggressiveness, we also address the critiques surrounding its current limitations—a crucial balance in the scientific conversation. Tune in for an insightful journey into how TMBquant could reshape cancer treatment and improve patient outcomes, all while keeping the science accessible and engaging! Link to episode page with article citation: www.scibud.media/podcast/season/2025/episode/156