eWEAR: A Wearable Strain Sensor Captures In Vivo Tumor Progression
Meeting Reports
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Oct 19, 2022
Oncology researchers employ a suite of in vitro models that assess the efficacy of numerous drugs quickly and inexpensively. However, in vivo tests deliver results that are more closely related to clinical trials, but a high-throughput approach is unlikely to be feasible for in vivo tests. Typically, researchers evaluate the drug efficacy in in vivo animal models, such as mice, by simply comparing the change in tumor volume between treated and untreated controls. However, these comparative studies can be complicated by the errors simultaneously produced by inherent biological variations, low precision of measurement tools, as well as limited sample sizes. It will be desirable to develop new measurement tools capable of accurately predicting treatment response and tumor progression in vivo, based on high-resolution datasets that can transform the drug discovery process.
To fulfil this technological gap, a multidisciplinary research team led by Prof. Zhenan Bao leveraged their expertise in flexible electronics to design a wearable strain sensor that allows real-time monitoring of tumor progression, which is recently described in a publication on BioRxiv. The sensor records the change in tumor volume every 5 minutes and can readily generate datasets to determine the pharmacodynamic response of a given drug within hours of therapy initiation. This technology is termed FAST, standing for Flexible Autonomous Sensors measuring Tumor volume regression (Figure 1).
This FAST technology outshines other conventional tumor measurement techniques in three ways. First, the sensor can function during the entire measurement period without mechanical limitations or toxicity to living tissue. Second, the sensor is able to precisely detect small changes in tumor volume that might have been considered measurement error for calipers and bioluminescence imaging techniques. Last, the autonomous and non-invasive nature of FAST technology further enables large-scale preclinical drug screening in a rapid and inexpensive fashion.
Oncology researchers employ a suite of in vitro models that assess the efficacy of numerous drugs quickly and inexpensively. However, in vivo tests deliver results that are more closely related to clinical trials, but a high-throughput approach is unlikely to be feasible for in vivo tests. Typically, researchers evaluate the drug efficacy in in vivo animal models, such as mice, by simply comparing the change in tumor volume between treated and untreated controls. However, these comparative studies can be complicated by the errors simultaneously produced by inherent biological variations, low precision of measurement tools, as well as limited sample sizes. It will be desirable to develop new measurement tools capable of accurately predicting treatment response and tumor progression in vivo, based on high-resolution datasets that can transform the drug discovery process.
To fulfil this technological gap, a multidisciplinary research team led by Prof. Zhenan Bao leveraged their expertise in flexible electronics to design a wearable strain sensor that allows real-time monitoring of tumor progression, which is recently described in a publication on BioRxiv. The sensor records the change in tumor volume every 5 minutes and can readily generate datasets to determine the pharmacodynamic response of a given drug within hours of therapy initiation. This technology is termed FAST, standing for Flexible Autonomous Sensors measuring Tumor volume regression (Figure 1).
This FAST technology outshines other conventional tumor measurement techniques in three ways. First, the sensor can function during the entire measurement period without mechanical limitations or toxicity to living tissue. Second, the sensor is able to precisely detect small changes in tumor volume that might have been considered measurement error for calipers and bioluminescence imaging techniques. Last, the autonomous and non-invasive nature of FAST technology further enables large-scale preclinical drug screening in a rapid and inexpensive fashion.
