Portable platform predicts chemo effectiveness for individual cancer patients
Rutgers researchers have created a portable device that they say can determine the efficacy of chemotherapy drugs, for a specific patient, in real time, with an accuracy of almost 96 percent. Teaming biosensors with machine learning, the device provides immediate results, aiding the selection of better drugs while reducing potential side effects.
Chemotherapy is often regarded as a bit of a shotgun approach in the battle against cancer. While it may kill tumor cells, it can also kill or damage healthy cells in the process. This chemical collateral damage is what causes side effects such as hair loss and gastrointestinal problems for many undergoing cancer treatment. So, if a more personal, targeted approach can be found – one that whittles down the choice of drugs to only those with the best cancer-killing firepower for that specific patient – then it's good news all round.
The members of the research team are from the engineering and medical campuses of Rutgers University. The team brought a range of skillsets together to create the novel device that works by identifying and counting live cancer cells as they pass between micro-fabricated electrodes through a tiny fluidic channel. Using multifrequency impedance spectroscopy in combination with machine learning to enhance accuracy, the sensor determines if a cell is alive or dead due to its specific electrical properties.
At present, devices used to analyze cell viability rely on staining the cells in order to determine their status, but this staining method can impair further molecular analysis and characterization of the cells down the line. The device built by the Rutgers team requires no staining, thereby eliminating this problem and opening up further analysis opportunities.
In the study, the team tested the device using cancer cells that had been treated with varying doses of an anti-cancer drug, and found the device to be up to 95.9 percent accurate. The next phase will involve testing the device on tumor samples from patients, with the hope that eventually, chemotherapy regimes might be tested before of administering them to patients. If this proves effective, chemotherapy patients may have better outcomes with far fewer side effects.
The paper is available to view now in the journal Microsystems & Nanoengineering.
Source: Rutgers University