Toward point-of-care assessment of patient response: a portable tool for rapidly assessing cancer drug efficacy using multifrequency impedance cytometry and supervised machine learning
We present a novel method to rapidly assess drug efficacy in targeted cancer therapy, where antineoplastic agents are conjugated to antibodies targeting surface markers on tumor cells. We have fabricated and characterized a device capable of rapidly assessing tumor cell sensitivity to drugs using mu...
Gespeichert in:
Veröffentlicht in: | Microsystems & nanoengineering 2019-07, Vol.5 (1), p.1-11, Article 34 |
---|---|
Hauptverfasser: | , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | We present a novel method to rapidly assess drug efficacy in targeted cancer therapy, where antineoplastic agents are conjugated to antibodies targeting surface markers on tumor cells. We have fabricated and characterized a device capable of rapidly assessing tumor cell sensitivity to drugs using multifrequency impedance spectroscopy in combination with supervised machine learning for enhanced classification accuracy. Currently commercially available devices for the automated analysis of cell viability are based on staining, which fundamentally limits the subsequent characterization of these cells as well as downstream molecular analysis. Our approach requires as little as 20 μL of volume and avoids staining allowing for further downstream molecular analysis. To the best of our knowledge, this manuscript presents the first comprehensive attempt to using high-dimensional data and supervised machine learning, particularly phase change spectra obtained from multi-frequency impedance cytometry as features for the support vector machine classifier, to assess viability of cells without staining or labelling.
Microfluidics: Enabling the rapid assessment of cancer drug efficacy
By measuring cells passing through electrodes, this microfluidics device could soon predict patient response to cancer therapy. Mehdi Javanmard and his team from Rutgers University in the United States developed a device that detects whether a cancer cell is alive based on the shift in its electrical properties as it passes through the device’s spectroscopy detection circuit. The team tested their device using cancer cell samples treated with different concentrations of a targeted anti-cancer drug. The device was able to rapidly assess live cell counts up to an accuracy of 95.9%. Future studies will test the device on clinical samples, and it is hoped that this device may one day be used as a convenient assay to pit patient tumor samples against therapies – giving a reliable indicator of response before treatment is administered. |
---|---|
ISSN: | 2055-7434 2096-1030 2055-7434 |
DOI: | 10.1038/s41378-019-0073-2 |