Aevus Precision Rx logo — Machine-Learning powered prescription guidance for Type 2 Di...

Aevus Precision Rx

Machine-Learning powered prescription guidance for Type 2 Diabetes

Founded 2019 United States Norman, United States 2-10 employees AI, Biotechnology +2

General Information

Company Name Aevus Precision Rx
Founded Year 2019
Location United States Norman, United States
Employees 2-10
Industries AI, Biotechnology, Health Care +1
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About Aevus Precision Rx

Aevus is engineering a ML -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 T2D drug outcomes, reduce medication switching and lower treatment costs. Co-Founded by two 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. 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, ADR 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 diabetic. Upon commercialization, Precision Rx will be marketed as a SaaS platform to large university and private integrated healthcare systems. The platform will be implemented as a ‘plug-and-play’ EHR utility, wherein a doctor can order the test at the click of a button and receive a patient report on-the-fly.

Taxonomy: Precision Medicine, Diabetes Treatment, Deep Learning, EHR Integration, Personalized Medicine, Prescription Guidance, Medical AI, Adverse Drug Reactions, Data-driven Healthcare, SaaS Platform, Clinical Decision Support, Healthcare Analytics, Patient Treatment Optimization

No funding data available for Aevus Precision Rx yet.

Aevus Precision Rx Alternatives & Competitors

Aevus Precision Rx vs
Delphyr
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Delphyr is a medical data platform that unlocks patient-level data analytics for busy clinicians.

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Cipherome, Inc
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Tempus AI
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Tempus AI, Inc. (NASDAQ: TEM) is a technology company leading the adoption of AI to advance precisio...

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FAQ About Aevus Precision Rx

Machine-Learning powered prescription guidance for Type 2 Diabetes
Aevus Precision Rx was founded in 2019.
Aevus Precision Rx is headquartered in Norman, United States.
Aevus Precision Rx operates in AI, Biotechnology, Health Care and Machine Learning. Its work centres on Precision Medicine, Diabetes Treatment, Deep Learning and EHR Integration.
Aevus Precision Rx has approximately 2-10 employees.
Top alternatives and competitors to Aevus Precision Rx include Delphyr, Cipherome, Inc, Tempus AI, InsightRX, AESOP Technology. These companies operate in related industries and serve comparable markets. You can compare them side by side on Bounce Watch.
Aevus Precision Rx and Delphyr are both companies in similar industries. Compare their funding, team size, growth signals, and market position on Bounce Watch to see which one fits your needs.

Source: BounceWatch company record for Aevus Precision Rx, https://bouncewatch.com/company/aevus-precision-diagnostics, updated 25 October 2024. When citing, please name BounceWatch and link this page.

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