Fast and simple biomarker detection by computational microscopy

Detection of low concentrations of biomarkers, such as low-abundant proteins in physiological samples, is crucial for early-stage diagnosis and disease monitoring.

However, existing detection methods are often laborious, costly, and time consuming, rendering them unsuitable for such applications.

Based on advances in computational PSF engineering microscopy made during our ERC Starting Grant, and in combination with microfluidic design, we developed a simple and fast biomarker detection method which allows accurate and sensitive results with minimal hands-on sample processing, which we have validated for potential applicability in diagnostics, and specifically, for continuous monitoring.

As a target clinical application towards which we can optimize our engineering efforts, we demonstrate the potential for preventative diagnostics via a collaboration with Rambam Medical Center (Israel), focusing on monitoring cell-based cancer treatments.

While cell-based therapies can be highly effective, they have introduced new types of cytokine-related adverse effects that can be debilitating and even life threatening.

Due to the current lack of appropriate diagnostics for preventative treatment, these adverse effects are mitigated only when symptoms arise, which might be too late.

We hypothesize that earlier detection using our method will enable preventive treatment and reduction in frequency and severity of these adverse events, transforming patient outcome.

We will develop a multiplexed cytokine detection scheme that reaches clinically significant sensitivity, and assess the effectiveness of this approach by monitoring CAR-T patients.

In the duration of the project, we will conduct a market research and develop regulation strategy with the aid of industrial and medical collaborations, advancing our diagnostic method toward commercialization.