Gemtuzumab Ozogamicin
| Evidence Level: L5 | Predicted Indications: 50 |
Quick Overview
| Item | Value |
|---|---|
| Drug Name | Gemtuzumab Ozogamicin |
| DrugBank ID | DB00056 |
| Brand Names (EU) | Mylotarg |
| Evidence Level | L5 |
| Predicted Indications | 50 |
| Top Prediction Score | 98.49% |
Approved Indication (EMA)
Mylotarg is indicated for combination therapy with daunorubicin (DNR) and cytarabine (AraC) for the treatment of patients age 15 years and above with previously untreated, de novo CD33-positive acute myeloid leukaemia (AML), except acute promyelocytic leukaemia (APL).
Predicted New Indications
TxGNN model predictions for potential drug repurposing:
| Rank | Indication | Score | Source |
|---|---|---|---|
| 1 | acute myeloid leukemia with t(8;21)(q22;q22) translocation | 98.49% | DL |
| 2 | acute myeloid leukemia with CEBPA somatic mutations | 98.38% | DL |
| 3 | acute myeloid leukemia with inv3(p21;q26.2) or t(3;3)(p21;q26.2) | 98.34% | DL |
| 4 | Richter syndrome | 98.06% | DL |
| 5 | bulbar polio | 97.92% | DL |
| 6 | chronic myelogenous leukemia, BCR-ABL1 positive | 97.89% | DL |
| 7 | metastatic neoplasm | 97.26% | DL |
| 8 | malignant spiradenoma | 97.23% | DL |
| 9 | 5q35 microduplication syndrome | 97.16% | DL |
| 10 | myeloid leukemia | 97.02% | DL |
| 11 | acute myeloid leukemia with t(8;16)(p11;p13) translocation | 96.54% | DL |
| 12 | acute myeloid leukemia with t(9;11)(p22;q23) | 96.19% | DL |
| 13 | acute myeloid leukemia and myelodysplastic syndromes related to topoisomerase type 2 inhibitor | 95.94% | DL |
| 14 | acute myeloid leukemia with t(6;9)(p23;q34) | 95.88% | DL |
| 15 | therapy related acute myeloid leukemia and myelodysplastic syndrome | 95.79% | DL |
| 16 | neuralgic amyotrophy | 95.74% | DL |
| 17 | amyotrophic neuralgia | 95.40% | DL |
| 18 | acute myeloid leukemia with minimal differentiation | 95.26% | DL |
| 19 | inherited acute myeloid leukemia | 95.18% | DL |
| 20 | acute lymphoblastic/lymphocytic leukemia | 95.09% | 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.