Cell Phone-based Lateral Flow Assay for Blood Biomarker Detection

The ability to integrate a sensor platform with a cell phone for health monitoring and disease diagnosis for astronauts in space exploration has the potential to be cost effective and space saving. In this proposal, Intelligent Optical Systems (IOS) will build upon expertise in lateral flow test strip (LFTS) assays by integrating an LFTS with a cell phone for the quantitative measurement of blood-based biomarkers. Our innovative and extremely cost-effective multi-analyte LFTS approach is imminently suited for space travel. All "microfluidics" (sample transport, reagent storage, mixing, etc.) take place via capillary action with no moving parts, no flow channels, and in a 5 mm x 5 mm x 30 mm space. Taking advantage of the built-in flash and high resolution camera, we will modify a commercially available cell phone with optical filters, lenses, a UV LED excitation source and a cassette holder for LFTS image capture. Quantum dots (QD) will be incorporated as labels with high quantum yield, resulting in higher sensitivity and narrow emission peaks in a multiplexed assay. In Phase I, we will develop and optimize a cell phone-based LFTS platform with the ability to quantitatively detect multiple biomarkers within clinically relevant ranges. The images of the LFTS will be captured on the cell phone and analyzed on a computer by the end of the Phase I. In Phase II, we will develop cell phone-based software for on-cell phone detection and data processing with expanded panels of biomarkers; advancing the TRL from 5 to 7.

Future space missions will require prolonged stays of crew members onboard space stations, and on other spacecraft during journeys to other planets. Increasingly complex space missions will also require the health status of astronauts to be monitored, preferably in a simple point-of-care apparatus that is compact and simple. The IOS system will enable NASA to monitor the health status of crew members by means of simple blood-based biomarker detection. A lateral flow test strip will be integrated with a cell phone into a simple and compact blood biomarker detection platform. This platform will gather diagnostic information in the absence of medically trained personnel, and can also monitor the health of aircraft pilots, cabin crews, passengers, and others in aeronautics-related occupations.

A cell phone-based serum biomarker detection platform will be cost-effective and compact not only for space exploration; it will also benefit the overall healthcare industry. Cell phones are becoming increasingly prevalent all over the world, with approximately 5 billion subscribers worldwide, and in the U.S. approximately one in three adults owns a smart phone. The ability to integrate a simple LFTS assay with a cell phone will enable healthcare providers to perform blood tests for many diseases on a wide population, including populations in remote areas where healthcare facilities are sparse. Such a platform can have a major impact in developing countries where a simple cell phone can be converted into a blood marker detection platform, avoiding the cost of acquiring dedicated medical equipment; furthermore, this point-of-care device improves the probability of early detection, yielding additional savings in overall cost of healthcare. Military field medicine will also benefit from the availability of a versatile handheld medical blood testing device that takes advantage of the ubiquitous mobile phone to minimize weight and power requirements.

This is early/mid-stage (TRL 5) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

None of these are guaranteed paths for this specific project — TechPort itself doesn't have an "apply" button. Reaching out to the contact(s) above with a specific question is usually the fastest way to find out what's actually open.