Until now, biophysical datasets have had limited clinical utility due to low throughput, with most techniques measuring only tens of cells per hour. Such approaches are characterized by low reproducibility, extended time-to-results and complex operations. Generating meaningful diagnostic information requires the analysis of thousands of cells, and clinical settings require accuracy, simplicity and rapidity, especially in the emergency department.
After years of methodical research and testing, we’ve pioneered a technology that integrates microfluidics, machine learning, high-speed imaging and cell mechanics to rapidly provide reliable information to aid in the early detection of fast-moving diseases like sepsis.
Three decades of work in labs spanning the globe tells us that the biomechanical properties of cells - the responses of cells to mechanical forces, the motion and kinetics of cell trajectory and viscosity, and the morphology and deformability of cells - are all intimately linked with their underlying state.
Our technology observes differences in the biomechanical properties of individual cells by identifying global state changes such as Activation, Differentiation, Migration and Proliferation. We simply ‘squeeze’ each cell to see how it behaves.
In immune cells, Activation associated with the dysregulated host response in sepsis can be measured at the protein level, but can also be understood by observing cellular mechanics and structure. Using our patented ‘squeeze’ technology, Cytovale’s approach reveals an entirely new way to map disease and quantify immune state activity in real time.
Three decades of work in labs spanning the globe tell us that the biomechanical properties of cells are intimately linked with their underlying state. Host immune cells behave in different ways, depending on the health of the host, or patient. With our patented technology, we’ve unlocked an entirely new way to map disease based on how immune host cells react to pressure.
Highly replicative cancer cells are significantly more deformable than their non-cancerous, benign precursors.
Immune activation can be readily distinguished from baseline biomechanical signatures, and chronic vs. acute inflammation states have notable differences.
Pluripotent stem cells become less deformable as they commit to a lineage and differentiate.
Metastatic cancer cells are notably more deformable than those with reduced metastatic potential.
If we can’t quickly diagnose what’s wrong, we don’t know how to accurately and effectively treat the patient.
A small blood sample, requiring no special collection tube, method or preparation, is drawn from the patient.
With just two user steps, the sample is prepped and loaded on a single-use microfluidic cartridge, with proprietary features for assessing the biomechanical properties of individual cells.
Under flow, precision microfluidic features apply precise and uniform hydrodynamic forces to tens of thousands of individual cells, and the resulting cellular deformation is captured with high speed videography at over 500,000 frames per second. Dozens of metrics are quantified for each cell, including morphology metrics prior to squeezing and structural metrics during the squeezing event.
Each patient’s unique signature is compared to established profiles of robustly constructed multidimensional disease signatures, reduced by machine learning techniques, to determine a diagnostic score, reportable to the clinician within minutes.
With the Cytovale system, we will reveal the disease state of the patient upon presentation in the emergency department to enable clinicians to make appropriate and timely care decisions such as rapid triage to critical care and appropriate prescribing of antibiotics. It’s a cellular squeeze that could accelerate triage to save critical time, exorbitant care costs, and most importantly, save lives.