Implementation pathway
The personalized treatment module through TxAgent can be implemented in four steps:
- data entry: Collect key patient parameters (age/genotype/complications/medication history), e.g. enter "CYP2C9*3 mutation + history of hypertension"
- algorithmic matching: Systematic cross-referencing of 200+ biomedical tools to screen for genotype-appropriate drugs (e.g., recommending chlorthalidomide for those with CYP2C9 mutations)
- dose calibration:: Dynamic dosage adjustment based on renal function and other indicators (e.g., reduce 50% dosage if creatinine clearance <30 ml/min)
- Program validation: Verification of drug target-patient gene expression matches through the Open Targets database
typical caseOptimization of regimen for diabetic patients: 1) Enter "HbA1c 8.5% + overweight" 2) Systematically exclude thiazolidinediones (risk of weight gain) 3) Prioritize SGLT2 inhibitors (both weight loss benefits) 4) Generate a detailed regimen that includes dosage and monitoring metrics.
scalability: It can be accessed to the hospital HIS system to realize automatic filling of electronic medical records, saving 60% data entry time.
This answer comes from the articleTxAgent: the AI tool that helps doctors analyze drug effects and treatment optionsThe
May not be reproduced without permission:AI productivity tools " How to optimize existing treatment protocols for personalized medicine?
