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Chemeleon Awarded NIH Grant to Develop Colorimetric Sensor for the Detection of Cerebrospinal Fluid

Chemeleon has been awarded a Phase I SBIR grant, "Development of a Colorimetric Sensor for Detection of Cerebrospinal Fluid Leaks", to further development of an easy-to-use colorimetric biosensor (like a pH test strip) to aid doctors in eliminating uncertainty and delays in diagnosing cerebrospinal fluid (CSF) leakage.

The product will have applications in multiple clinical scenarios, including traumatic brain injuries(TBI) in emergency departments (ED), lumbar punctures, spontaneous CSF leak cases, and during spinal surgeries. CSF leaks develop when there is a rupture in the membranes surrounding the brain or spinal cord. While some CSF leaks occur spontaneously, most are a result of a TBI, presenting as rhinorrhea, or a result of spinal surgery in which the clear CSF fluid mixes with blood and other liquids. Diagnosing CSF leaks is a well-known problem for neurosurgeons, as it is difficult to differentiate from common fluids.

It is estimated that there are 235,000 hospitalizations yearly for TBI and over 1.4 million spinal surgeries per year. In each case, physicians could benefit greatly by utilizing their technology to confirm or rule out CSF leaks. Currently, patient samples are sent out for third-party analysis, taking several days for results to return. Delayed treatment during this time increases patient morbidity, as well as further complications such as meningitis, brain infections, or stroke. In the case of spinal surgeries, a dural tear resulting in a CSF leak is a risk of spinal procedures. Currently there is no accurate, on-site test to help neurosurgeons identify CSF leaks during surgery.

The innovation of the proposed approach lies in the integration of a synthetic nanoreceptor, able to capture the b2-transferrin protein uniquely found in CSF, with a nanostructured surface capable of generating visible color changes upon capture of the targeted protein. The product will give neurosurgeons a simple-to-use, real-time diagnostics tool for identifying a CSF leaks. This technology will significantly reduce the number of undiagnosed and misdiagnosed CSF leaks, improving overall patient outcomes by preventing delayed treatment and the complications that arise from it.


Research reported in this publication is supported by the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under Award Number R43 NS112064. “The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.”

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