InnoVations in MedTech – No Specimen, No Delay
Real-Time Diagnostics at the Point of Care
Breakthrough in Non-Invasive Diagnostics: Real-Time Pathogen & Disease Detection Using AI-Enhanced Spectroscopy
- Our diagnostic platform eliminates the need for swabs, blood draws, or lab processing. Using a fingertip scan and AI/ML, we deliver actionable results in under 30 seconds – right at the point of care.
- AI-powered, no-specimen diagnostic platform enables rapid, non-invasive, lab-free detection, providing instant, highly accurate point-of-care results—without the need for biological samples.
· Read more about our cutting-edge approach to diagnostics.
Our Inventions
No Specimen Diagnostic Device
- A laser shines on the patient’s fingertip
- Optical sensors capture unique spectral signatures
- AI/ML algorithms instantly classify infection status
- Results are displayed in real time – no lab, no waiting
- Environmentally friendly
Please Read our Peer-Reviewed Published Manuscript
Validated Clinical Accuracy
- 455-patient clinical study
- Achieved AUROC of 0.896 for infection detection
- Proven consistent performance across ER, ICU, urgent care settings
- Peer-reviewed publication
Built for Emergency & Urgent Care
- 30-second turnaround – faster than rapid antigen or PCR
- Zero specimen handling – ideal for high-volume triage
- Non-invasive and repeatable – safer for immunocompromised patients
Powered by Optical Engineering + Machine Learning
- Spectroscopy offers molecular-level precision
- AI/ML trained on labelled clinical datasets
- Platform supports future expansion to other disease targets
* Backed by Patients and Patents*
Comments
- “Your work on integrating artificial intelligence with Raman spectroscopy for diagnostic purposes is indeed innovative. The concept of a device that can be easily recalibrated for different medical applications is promising.”
- “This will replace blood testing in 10 years.”
- “The potential here seemed incredibly powerful and could revolutionize noninvasive testing.”
- “The sky is the limit with this technology”
Pipeline
- Next-Gen Precision Surgical Cancer Probe
- Autonomous Infusion Device
Autonomous Infusion Device
Reduce IV Alarms by Automatically
- Change low volume bags
- Flush catheters
- Unkink tubing
- Aspirate air bubbles
- Charge low batteries
Meet the Team
Founder/CEO
Allen B Chefitz, MD
Surgeon/Scientist
Extensive experience in medical device innovation and a track record of successful patent development. The lead investigator has developed several patented devices in the diagnostic and therapeutic space, with a focus on improving surgical outcomes. Led an interdisciplinary team of experts in the design, building and clinical validation of a patented no specimen diagnostic device. Oversees the project’s clinical and technical aspects, ensuring that the device aligns with real-world surgical needs. Responsible for integrating clinical insights into the design, development, and validation phases of the project
Chief Operating Officer
Elisa Long, MD
MS in Computer Science, MIT
Healthcare technology strategy, networking, and study design. Oversees partnership development, study execution, and milestone tracking. Established key collaborations with Northeastern University and MIT CSAIL. Drives stakeholder engagement for multi-center clinical trials.
Scientific Advisor
Rohit Singh, PhD
Research Scientist at MIT and Expert in Machine Learning and Genomics
Expert in artificial intelligence and machine learning with experience in developing algorithms for patented real-time diagnostic devices. Previous projects include training AI/ML models for high-sensitivity medical diagnostics. Co-inventor of the no specimen diagnostic device. Co-founder Martini.ai
Consultant
Yongwu Yang, PhD
Physical Chemistry, MIT, Optical Engineering
Optical Engineer, who earned a PhD in Physical Chemistry at MIT in 1992 and then worked as a postdoctoral associate at the Barnett Institute of Northeastern University in optical engineering. Provided expertise in Raman Spectroscopy technology incorporating it into a finger inserted no specimen diagnostic point-of-care device.
Peter Szolovits, PhD
Scientific Advisor
Professor of Computer Science and Engineering in the MIT Department of Electrical Engineering and Computer Science (EECS) and an Associate faculty member in the MIT Institute of Medical Engineering and Science (IMES) and its Harvard/MIT Health Sciences and Technology (HST) program. He is also head of the Clinical Decision-Making Group within the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).
Patents
US Patent No. 11,872,708 “Monitoring and Maintaining an Intravenous Assembly Without Medical Staff Involvement For Safe Distancing Enforcement” Jan 16 2024
U.S. Patent No. 11,452,454 “Self Administered Non-Invasive Transcutaneous Viral Detector” Sept 27, 2022
U.S. Patent No. 11,304,605 “Self Administered Non-Invasive Transcutaneous Viral Detector” April 19, 2022
U.S. Patent No. 12,121,321 “Self Administered Non-Invasive Transcutaneous Viral Detector” Oct 22, 2024
U.S. Patent No. 11,291,408 “Eyewear System For Detecting And Indicating Presence Of Coronavirus” April 5, 2022
U.S. Patent No. 10,906,180 “Monitoring And Maintaining An Intravenous Assembly Without Medical Staff involvement For Safe Distancing Enforcement” Feb. 2, 2021
U.S. Patent No. 12,121,765 “System for Monitoring and Maintaining an intravascular Assembly” Oct 22, 2024
Along with several Continuation Patents, Foreign Applications and Pending Patents.
