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Personalized Medication Software for BCL-2 Inhibitor in AML Patients Using Machine Learning and Genomics
Sponsor: The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Summary
Severe neutropenia caused by venetoclax,a B-cell lymphoma-2(BCL-2) inhibitor, is the main cause of venetoclax tapering, drug discontinuation, and treatment delay. This study combines machine learning and genomics, hoping to develop models to predict venetoclax dose in Acute myeloid leukemia(AML) patients and compare the efficacy and safety differences of model-guided individualized medication regimen with current conventional regimen. According to the demographic information, the drug information, the drug concentration of the target patients, the laboratory examination, the single nucleotide polymorphism(SNP) information and the adverse reactions of the AML patients, and the model was constructed through machine learning.
Official title: Dose Optimization and Personalized Medication Software Research of BCL-2 Inhibitor Based on Machine Learning Combined With Genomics in Patients With Acute Myeloid Leukemia
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
200
Start Date
2024-03-01
Completion Date
2027-12-31
Last Updated
2024-03-06
Healthy Volunteers
No