Scientific directions that matter for PIRIA.
This section focuses on peer-reviewed signals shaping oncology AI and translational research through 2026.
From target ideas to target assessment.
A 2026 Nature Reviews Drug Discovery review describes the expanding role of AI in target identification and assessment, while also stressing that meaningful validation remains difficult and that a target is only fully validated once a successful therapy reaches patients.
Pun FW et al. Target identification and assessment in the era of AI. Nat Rev Drug Discov 25, 534–552 (2026). DOI: 10.1038/s41573-026-01412-8.
Multi-omics is no longer optional.
Recent 2026 reviews across oncology emphasize integrating genomics, transcriptomics, proteomics, epigenomics and clinical variables, while identifying interpretability and generalizability as continuing bottlenecks for AI translation.
Recent 2026 peer-reviewed reviews in precision oncology and cancer AI; also see PIRIA Insights for selected references.Where and when the biology changes.
Spatial transcriptomics and longitudinal liquid-biopsy approaches are changing how tumor microenvironments and treatment response are studied. These approaches are especially relevant to immune-oncology and resistance questions.
Pantel et al. Nat Rev Clin Oncol. 2026. DOI: 10.1038/s41571-026-01181-8.