Acalabrutinib
| Evidence Level: L5 | Predicted Indications: 50 |
Quick Overview
| Item | Value |
|---|---|
| Drug Name | Acalabrutinib |
| DrugBank ID | DB11703 |
| Brand Names (EU) | Acalabrutinib |
| Evidence Level | L5 |
| Predicted Indications | 50 |
| Top Prediction Score | 98.73% |
Approved Indication (EMA)
Calquence as monotherapy or in combination with obinutuzumab is indicated for the treatment of adult patients with previously untreated chronic lymphocytic leukaemia (CLL).Calquence in combination with venetoclax with or without obinutuzumab is indicated for the treatment of adult patients with previously untreated chronic lymphocytic leukaemia (CLL).Calquence as monotherapy is indicated for the treatment of adult patients with chronic lymphocytic leukaemia (CLL) who have received at least one p
Predicted New Indications
TxGNN model predictions for potential drug repurposing:
| Rank | Indication | Score | Source |
|---|---|---|---|
| 1 | mantle cell lymphoma | 98.73% | DL |
| 2 | B-cell neoplasm | 97.70% | DL |
| 3 | lymphoma, non-Hodgkin, familial | 97.64% | DL |
| 4 | colon adenocarcinoma | 96.60% | DL |
| 5 | lymphosarcoma | 94.81% | DL |
| 6 | small intestinal Burkitt lymphoma | 94.04% | DL |
| 7 | small intestinal mucosa-associated lymphoid tissue lymphoma | 93.83% | DL |
| 8 | thyroid gland mucosa-associated lymphoid tissue lymphoma | 93.76% | DL |
| 9 | breast mucosa-associated lymphoid tissue lymphoma | 93.67% | DL |
| 10 | tonsillar lymphoma | 93.67% | DL |
| 11 | neoplasm of mature B-cells | 93.25% | DL |
| 12 | lymph node cancer | 92.30% | DL |
| 13 | polyclonal hypergammaglobulinemia | 92.29% | DL |
| 14 | chest wall lymphoma | 92.25% | DL |
| 15 | lymphoma | 91.78% | DL |
| 16 | follicular lymphoma | 91.74% | DL |
| 17 | monoclonal paraproteinemia disease | 91.28% | DL |
| 18 | interdigitating dendritic cell sarcoma | 91.15% | DL |
| 19 | follicular lymphoma, susceptibility to, 1 | 91.10% | DL |
| 20 | subcutaneous panniculitis-like T-cell lymphoma | 90.90% | DL |
Showing top 20 of 50 predictions.
About TxGNN Predictions
Prediction Sources
| Source | Description |
|---|---|
| KG | Knowledge Graph - Network topology-based associations |
| DL | Deep Learning - Neural network score prediction |
Evidence Levels
| Level | Definition |
|---|---|
| L1 | Multiple Phase 3 RCTs / Systematic Reviews |
| L2 | Single RCT or multiple Phase 2 trials |
| L3 | Observational studies / Large case series |
| L4 | Preclinical / Mechanistic / Case reports |
| L5 | AI prediction only (current) |
Clinical Validation Needed
Research Use Only: These predictions are computational hypotheses that require clinical validation. They should NOT be used for clinical decision-making.
Next Steps for Validation
- Literature Review: Search PubMed for existing evidence
- Clinical Trial Search: Check ClinicalTrials.gov for ongoing studies
- Mechanistic Analysis: Evaluate biological plausibility
- Preclinical Studies: Conduct in vitro/in vivo validation
- Clinical Trials: Design and conduct human studies
Data Access
- FHIR API:
/fhir/ClinicalUseDefinition/ - CSV Download: All Predictions
- GitHub: yao-care/EuTxGNN
Citation
If using this data, please cite:
@article{huang2023txgnn,
title={A foundation model for clinician-centered drug repurposing},
author={Huang, Kexin and others},
journal={Nature Medicine},
year={2023},
doi={10.1038/s41591-023-02233-x}
}
Disclaimer: This report is for research purposes only and does not constitute medical advice. Drug repurposing predictions require rigorous clinical validation before any therapeutic application.