Risorious offers a clinical decision support platform that provides evidence-based guidelines for prescribing neuropsychiatric medications. The platform helps clinicians optimize treatment plans by offering personalized recommendations based on patient data and current research.
Funding
Funding not disclosed
Founders
Product
Problem
Current psychiatric diagnostic systems often lead to ineffective medication prescriptions due to a lack of objective indicators and failure to account for individual patient variability. This results in an average of 4.3 years of inappropriate treatment for mental health patients and inefficiencies in clinical drug trials. Additionally, the absence of readily available tools for self-assessment makes it difficult for individuals to proactively monitor their mental well-being.
Solution
Risorious leverages EEG and other biometric data to provide solutions for personalized mental healthcare. For clinicians and pharmaceutical companies, Risorious offers a drug-response prediction platform that analyzes patient-specific data to identify optimal medication matches and improve the efficiency of clinical trials by selecting appropriate participant groups and objectively measuring drug efficacy. For individual users, Risorious provides wearable-based solutions that quantify mental states such as focus and stress, enabling early detection and management of mental health issues. The company's technology aims to integrate quantitative mental health assessments into both clinical practice and daily life.
Target Audience
Risorious serves pharmaceutical companies and clinicians seeking to optimize drug development and treatment plans, as well as insurance companies aiming to improve risk management and expand coverage for mental health conditions. They also target individuals interested in proactively monitoring and managing their mental well-being through wearable technology.
Features
- EEG-based drug response prediction, providing clinicians with a list of medications likely to be effective for individual patients.
- AI-powered algorithms for identifying suitable candidates for clinical trials and objectively measuring drug efficacy.
- Wearable EEG devices (EZRest, Bluesafe) for continuous monitoring of cognitive function and emotional state.
- Algorithms for quantifying focus and stress levels from wearable data, offering personalized recommendations for improvement.
- Integration with existing wearable devices (smartwatches, bands) to leverage readily available biometric data.
- AI-driven insurance risk models that quantify mental health risks for actuarial and underwriting purposes.