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ML powered drug selection platform for treating Type 2 Diabetes

ML powered drug selection platform for treating Type 2 Diabetes

Aevus is engineering an AI -powered Prescription Guidance Platform - Aevus Precision Rx for Endocrinologists/PCPs to tailor prescriptions for Type 2 diabetes (T2D) patients. In doing so, Aevus intends to improve drug outcomes, reduce medication switching and lower treatment costs. Once implemented within the clinical workflow, a physician will order prescription guidance from our platform using a sequence of mouse-clicks on his EHR system. The Precision Rx platform will interface seamlessly with the EHR system, extract a whole host of patient info (biographic info, prescription history, clinical observations, Adverse Drug Reaction history, etc.), analyze the data through a predictive/cognitive deep learning algorithm, benchmark it against prescription treatment and outcome data of similar patients from across the world and model out projected responses to T2D drug classes for the current diabetes patient. In doing so, the platform will essentially list out the 11 drug classes, attribute risk/toxicity scores to all the 11 drug classes and sort the drug classes in descending order of projected toxicity each unique patient. The findings and drug efficacy will be published as part of a guidance report with a turn-around time ~48 hrs. Using such an on-demand prescription guidance platform will render a second pair of clinical eyes to a physician and empower him/her to make a data-driven and statistically sound prescription decision to treat a Type-2 patient with diabetes. Co-Founded by three Johns Hopkins University alumni & backed by the scientific prowess of stellar medical and scientific advisors, Aevus’ team combines a strong combination of science and business professionals.

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Co-Founder of Aevus PD. Streamlining prescription management for Type 2 Diabetes, one patient at a time. Business background - consulting & MS - Johns Hopkins
Total raised


Funded over

1 round

Latest round

Pre-Seed (Nov 2019)