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Personalized Medication Software for BCL-2 Inhibitor in AML Patients Using Machine Learning and Genomics

NCT06295029 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 200

Last updated 2024-03-06

No results posted yet for this study

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.

Conditions

Sponsors & Collaborators

  • The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School

    lead OTHER

Principal Investigators

  • Yudong Qiu · The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-03-01
Primary Completion
2027-12-31
Completion
2027-12-31

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06295029 on ClinicalTrials.gov