Our vision is bold, to ensure lab to hand translation of clinical grade diagnostic devices to reach every corner of the earth and beyond including literal outer space. We say hand and not bedside because we believe the future of healthcare in societies ahead and the access of global healthcare in current societies in remote areas will only be achieved if tools are built to easily be used by individuals themselves. We imagine a world where medicine is not a care of the sick but a continuous regular monitoring of healthy individuals enabling precision and personalized early disease detection, where anyone in remote regions of the world be it in low-income nations or confict zones can learn about their disease state and the healthcare of our fellow humans advancing our extraterrestrial exploration are secured. Our vision is to elevate the standard of clinical care for those with low resources here on earth while at the same time enabling the next endevours of humanities ourterspace exploration. Such an ambitious goal is too grand for any one research lab to achieve alone, it takes a village. We aim to achieve our goal by leveraging a diverse interdiciplinary internal team and extensive external collaborations with other research groups and industry partners at the intersection of state-of-the-art engineering, biomedicine and artificial intellegince tools. Ultimately, our goal is to impact humanity for the better, ensuring global access to healthcare for anyone literally anywhere!
Developing spectroscopic fingerprinting based Dx
Machine learning tools for point-of-need Dx
Clinical datasets are often limited in number and pose a challenge for traditional algorithm training. In addition, in extreme environments such as remote regions of the world and outer space, it is impossible to access to the cloud and have reliable power source. Here we aim to develop unique algorithms and device architectures to make AI based analysis accessible for applications in extreme environments. We will leverage resources and collaborations from the MIT Schwarzman college of computing.
Enabling liquid clinical sample preparation
Bloodstream infection in particular is a very deadly disease state where by only a few bacteria cause severe illness. However, the handful bacteria among the billions of red blood cells and thousands of white blood cells present per milliliter of blood are difficult to isolate. This necessitates the culturing step in gold standard diagnostic apporach. Here, we tackle this needle in a haystack problem utilizing acoustic bioprinting of picoliter volumes that include single to few cells generated directly from the fluid surface.
The Tadesse lab will continue to innovate in this realm desiging new approaches for tailored liquid clinical samples such as urine, saliva and blood. In addition we will work on addressing major engineering and technology bottlenecks in the clinical translation of novel sample prepartion technologies.
Novel optical imagining approaches for Dx
Nano-chemistry for ultra-sensitive disease Dx
Clinical datasets are often limited in number and pose a challenge for traditional algorithm training. In addition, in extreme environments such as remote regions of the world and outer space, it is impossible to access to the cloud and have reliable power source. Here we aim to develop unique algorithms and device architectures to make AI based analysis accessible for applications in extreme environments. We will leverage resources and collaborations from the MIT Schwarzman college of computing.
Fundamentals of light biomatter interaction
Portable robust devices for extreme environment Dx
Automated high-throughput setups for in-lab vetting of Dx
Prior to miniaturization and field tests we will ensure efficiency of our diagnostic device concepts in house by utilizing high throughput autonomous versions of the diagnostic tools to run thousands of clinical and lab grown samples from our collaborators at the Ragon Institute and Mass General Hospitals. We envision such a tools could be translated for use in large hospital and centralized clinical laboratory settings as well as in other research labs.