blood-cancer

A 20-minute lab-on-a-chip test distinguishes drug-resistant leukemia cells with 91% accuracy.

An optofluidic chip using laser light scatter patterns and SVM machine learning classified drug-resistant vs drug-sensitive leukemia cells with 91.1% accuracy in about 20 minutes. The label-free method requires no staining, making it practical for rapid clinical diagnostics.

A 20-minute lab-on-a-chip test distinguishes drug-resistant leukemia cells with 91% accuracy.

Key Findings

91.1% classification accuracy with SVM classifier
Detection within 10 minutes; full workflow in 20 minutes
Label-free—no staining or chemical preparation required
Potential for personalized leukemia treatment planning

Implications

Rapid resistance testing could allow earlier switching to effective alternative therapies in leukemia.

Caveats

Proof-of-concept with cell lines; abstract-only. Clinical validation with patient samples needed.

Source: Analytica chimica acta — 2026-06-15

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BET Inhibitor Target Selectivity Database

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A 20-minute lab-on-a-chip test distinguishes drug-resistant leukemia cells with 91% accuracy.

Key Findings

Implications

Caveats

Read more

Landmark DCIS trial, CRC microbiome & AML combos

Colorectal Cancer Microbiome Discovery Platform

GBM Tumor Microenvironment Drug Target Atlas

BET Inhibitor Target Selectivity Database