Develops a multimodal prognostic platform that uses AI to analyze imaging, genetic, phenotypic, molecular, and clinical data for forecasting disease progression in age-related disorders, with a focus on Alzheimer’s disease. This platform provides precise patient stratification and validated digital biomarkers, enabling improved clinical decision-making and accelerated drug development for healthcare providers and pharmaceutical companies.
Funding
$1.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Clinical trials for age-related disorders, particularly Alzheimer's disease, face challenges due to the heterogeneity of patient populations and the slow, variable rate of disease progression. This makes it difficult to identify suitable participants and accurately measure treatment effects, leading to increased costs and high failure rates.
Solution
Perceiv AI offers a multimodal prognostic platform that leverages artificial intelligence to forecast disease progression in age-related disorders, with a focus on Alzheimer’s disease. The platform integrates diverse data types—imaging, genetic, phenotypic, molecular, and clinical variables—to provide precise patient stratification and validated digital biomarkers. By identifying subgroups with similar disease trajectories, Perceiv AI enables improved patient selection for clinical trials and enhances the ability to detect treatment effects. The AD-Px™ prognostic engine helps pharmaceutical companies accelerate drug development by reducing screen failure rates and optimizing trial design.
Target Audience
The primary customers are pharmaceutical companies and healthcare providers involved in clinical trials and treatment of age-related disorders, specifically Alzheimer's disease, seeking to improve patient selection and accelerate drug development.
Features
- Multimodal data integration: Combines imaging, genetic, phenotypic, molecular, and clinical data for comprehensive patient characterization.
- AI-driven forecasting: Employs deep learning to predict individual disease trajectories and treatment response.
- Patient stratification: Precisely targets subgroups of interest within heterogeneous populations.
- Validated digital biomarkers: Provides specific and thoroughly validated biomarkers for clinical decision-making.
- AD-Px™ prognostic engine: Reduces screen failure rates in Alzheimer's disease trials.
- ISO 27001 certification and HIPAA compliance: Ensures data security and privacy.