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Predictions are published in FHIR R4 format, ready to integrate with EHR systems.

FHIR resources

This site publishes predictions as FHIR R4 resources, consumable directly by SMART on FHIR apps:

Resource	Path	Description
CapabilityStatement	`/fhir/metadata`	FHIR server capability statement
MedicationKnowledge	`/fhir/MedicationKnowledge/`	Drug resources
ClinicalUseDefinition	`/fhir/ClinicalUseDefinition/`	Predicted indications
Bundle	`/fhir/Bundle/all-predictions.json`	All predictions bundled

Search index

/data/search-index.json provides a search index of drugs and indications for building your own query interface.

Terms of use

Data on this site is for research reference only and must not be used as a basis for medical decisions.
When citing, credit InTxGNN (藥提醒科技有限公司) and cite the original TxGNN paper.
Downstream data remains subject to the licence terms of each original source (see Data Sources).

About the Developer

This platform is developed and operated by 藥提醒科技有限公司 (yao.care, company registration number 83620786, 12F, No. 220, Sec. 2, Taiwan Blvd., West Dist., Taichung City, Taiwan).

InTxGNN is the India site of the company’s “TxGNN Drug Repurposing” product line. The same system is deployed across 30 countries and regions, each named {CC}TxGNN (JpTxGNN, UsTxGNN, DETxGNN, and so on) at {cc}txgnn.yao.care. Product overview: https://www.yao.care/medical/txgnn/.

The TxGNN model itself was developed by the Zitnik Lab at Harvard Medical School and published in Nature Medicine. This platform is the production system 藥提醒科技有限公司 built on top of that model, covering national drug-registration data integration, dual knowledge-graph and deep-learning prediction, PubMed / ClinicalTrials evidence grading, and SMART on FHIR electronic health record integration.

Disclaimer
This report is for academic research reference only and does not constitute medical advice. Always follow your physician's instructions; never adjust medication on your own. Any drug repurposing decision requires full clinical validation and regulatory review.

Reviewed by: 藥提醒科技有限公司 (yao.care)