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Brainify.AI

USA, New York
Market: Medicine, Artificial Intelligence, Biotech
Stage of the project: Prototype or product is ready

Date of last change: 31.01.2023
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Idea

Brainify.AI is an AI/ML electroencephalography (EEG) biomarker platform for novel treatment development aimed at depression in women that increases the likelihood of new drug approval by 80%.

Current Status

Brainify.AI is currently negotiating with Eli Lily and Company and Takeda pharmaceutical companies to introduce the first AI/ML EEG biomarkers into the antidepressant clinical trials.

Problem or Opportunity

Depression has a misdiagnosis rate up to 50% and treatment efficacy lower than 33%. The depression rate is twice as high in females than in males. Females’ depression is under-recognized, despite its variability in subtypes (e.g., premenstrual dysphoric disorder, postpartum depression (PPD), and post-menopausal depression). Currently, there is only one approved drug on the market to treat PPD, while the rates of PPD remain high (with up to 20% of the female population in the US). The need for more objective measurement and variability in treatment options are essential.

Solution (product or service)

Brainify.AI develops revolutionary machine-learning (ML) models ​​that utilize electroencephalogram (EEG) data and can act as a potential biomarkers. Our Placebo Non-Responders Model identifies the probability of an individual responding to a placebo in Clinical Trials. It is used for sample stratification and increases the chance of positive outcomes in Phase II and Phase III of clinical trials. Our Brain Sex Phenotype Prediction Model and Brain Age Prediction Model can be used as candidates for biomarkers sensitive to the expression and activation of hormonal receptors in the human brain.

Business model

Brainify.AI plans to initiate direct sales to pharmaceutical companies and CROs.
· Per subject enrolled in the pharma trial or 10% of total phase 2 and 3 trial cost
· Later on per patient test

Incubation/Acceleration programs accomplishment

Harvard iLab Accelerator
iCorp Accelerator
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