ASH 2025 at a glance
Get ready for ASH 2025 with LucidQuest’s concise preview. We spotlight must-see sessions and emerging themes in hematology and AI.
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Key Topics from ASH 2025 Scientific Presentations
High-Risk AML & Conditioning Regimens
- Phase 2 myeloablative Bu-Clad-Thio-Ven plus post-transplant cyclophosphamide achieved 3-year PFS 58%, with best outcomes in TP53 wild-type disease.
Bleximenib in KMT2A and NPM1m AML
- Phase 3 HOVON 181 evaluates bleximenib + chemotherapy in KMT2Ar and NPM1m AML aiming to improve EFS and OS.
Blinatumomab & MRD in B-ALL
Blinatumomab improved MRD negativity and remission in adult B-ALL, with benefits across key molecular subgroups, supporting targeted strategies.
- First-Line CAR-T in B-ALL
Frontline CD19 CAR-T delivered high MRD-negative responses and durable leukemia-free survival, suggesting a potential alternative to upfront chemotherapy.
Acalabrutinib in Untreated LBCL
- Phase 2 acalabrutinib + frontline chemotherapy showed broad efficacy—especially in MCD/N1—with 50% response and 2-year PFS 84.8%.
Odronextamab in Untreated DLBCL
- OLYMPIA-3 Phase 1A reported 100% ORR in one cohort using odronextamab + chemotherapy; CRS was the most common AE.
Pembrolizumab-Based Salvage in cHL
- Pembrolizumab + GVD in R/R cHL achieved 95% CR and 100% PFS at 13.5 months, indicating strong durability.
KRd vs VRd in NDMM
- KRd delivered higher MRD-negative CR (31% vs 18%) and superior PFS, supporting its role in induction therapy.
CAR-T for RRMM (iMMagine-1)
- Anito-cel anti-BCMA CAR-T achieved 97% ORR and 93% MRD negativity in RRMM with manageable cytopenias and CRS.
Artificial Intelligence and Machine Learning at ASH 2025
STIM2 Gene Signature in CML
- STIM2 identified a 48-gene signature predicting treatment-free remission (AUROC 0.84).
AI in Bleeding Risk Prediction in Cancer
- ML using 1,000+ clinical features stratified bleeding risk with 18-fold variation across quintiles.
VTE Risk Transformer Model
- Trained on 80,808 cancer patients, predicting VTE with AUC 0.68–0.77, improving identification of high-risk groups.
SCD Diagnosis via SIGHT
- ML system reached 99.3% accuracy for SCD risk prediction from CBC data; SHAP identified MCHC as the top feature.
AI in Predicting CAR-T Outcomes in LBCL
- Serum metabolomics–based model predicted CAR-T response in R/R LBCL with AUC up to 0.99.
AML IDH1 Mutation From Marrow Images
- Deep learning predicted IDH1 mutation status from bone marrow morphology (AUROC 0.731–0.788).
AI in Predicting GVHD Post-Transplant
- GVHD-Intel 1.0 predicted acute and chronic GVHD with AUC up to 0.83, supporting scalable real-time risk assessment.
📅 Build your schedule around the topics that interest you.
📥 Download the ASH 2025_Preview_by_LucidQuest
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