Drug Repurposing: From AI to Evidence
NlTxGNN uses the Harvard TxGNN model to predict drug repurposing candidates for 145 CBG-MEB approved drugs, identifying potential new therapeutic uses.
Browse Drug Reports Learn Methodology
Drug Search
Enter a drug name or disease name to find repurposing predictions. Supports generic names, brand names, and disease keywords.
Key Features
Each report integrates clinical trial IDs (NCT), literature references (PMID), and CBG-MEB approval information for complete traceability.
L1 (Multiple Phase 3 RCTs) to L5 (AI prediction only) classification helps prioritize candidates for validation.
Focused on 145 CBG-MEB approved medicines with repurposing predictions ready for research.
FHIR R4 compliant API and SMART on FHIR app for seamless EHR integration.
Quick Navigation
| Category | Description | Link |
|---|---|---|
| High Evidence | L1-L2, priority for clinical evaluation | View drugs |
| Medium Evidence | L3-L4, requires additional validation | View drugs |
| AI Predictions | L5, research direction reference | View drugs |
| Full Drug List | All 145 drugs (searchable) | Drug List |
| Health News | Automated health news monitoring | View News |
| FHIR API | Integration endpoints | FHIR Metadata |
About This Project
NlTxGNN uses the TxGNN deep learning model published by Harvard’s Zitnik Lab in Nature Medicine to predict potential new therapeutic uses for CBG-MEB approved medications.
“TxGNN is the first foundation model designed for clinician-centered drug repurposing, integrating knowledge graphs with deep learning to predict drug efficacy for rare diseases.” — Huang et al., Nature Medicine (2023)
Statistics
| Item | Count |
|---|---|
| Drug Reports | 145 |
| Regulatory Agency | Medicines Evaluation Board (CBG-MEB) |
Data Sources
This report is for research purposes only and does not constitute medical advice. Drug use should follow physician guidance. Any drug repurposing decisions require complete clinical validation and regulatory review.
Last updated: 2026-03-10 | Maintainer: 藥提醒科技有限公司 (yao.care)
Over de ontwikkelaar
Dit platform wordt ontwikkeld en beheerd door 藥提醒科技有限公司 (yao.care, inschrijvingsnummer 83620786, 12F, No. 220, Sec. 2, Taiwan Blvd., West Dist., Taichung City, Taiwan).
NlTxGNN is de Nederlandse site van de productlijn “TxGNN Drug Repurposing” van het bedrijf.
Hetzelfde systeem is uitgerold in 30 landen en regio’s, elk met de naam {CC}TxGNN
(JpTxGNN, UsTxGNN, DETxGNN, enzovoort) op {cc}txgnn.yao.care.
Productoverzicht: https://www.yao.care/medical/txgnn/.
Het TxGNN-model zelf is ontwikkeld door het Zitnik Lab van Harvard Medical School en gepubliceerd in Nature Medicine. Dit platform is het productiesysteem dat 藥提醒科技有限公司 op dat model heeft gebouwd; het omvat de integratie van nationale geneesmiddelregistratiegegevens, dubbele voorspelling met kennisgraaf en deep learning, bewijsgradering op basis van PubMed / ClinicalTrials, en integratie met elektronische patiëntendossiers via SMART on FHIR.