CanBART: A generative foundation model of cancer molecular alterations for synthetic patient generation and genomic profile completion

Despite the rapid expansion of genomic profiling in oncology, real-world datasets remain limited in size and unevenly distributed, particularly for rare cancers and underrepresented patient populations. The number of available sequenced cases is often insufficient for robust machine learning, and even within existing cohorts, sequencing panels differ in gene coverage. As a result, crucial molecular features are frequently missing, making…