NetraMark utilizes Attractor AI to analyze complex patient data in clinical trials, identifying causal relationships that enhance patient stratification and optimize inclusion/exclusion criteria. This technology improves trial efficiency by reducing sample sizes and increasing the likelihood of successful outcomes, addressing the challenges of patient heterogeneity and placebo response.
Funding
$1.3M 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 often suffer from patient heterogeneity and variability in treatment response, including placebo effects, making it difficult to identify effective treatments and optimize trial design. Traditional methods struggle to fully capture and understand the complex relationships within patient data, leading to inefficient trials and potentially inconclusive results.
Solution
NetraMark offers an AI-driven platform, NetraAI, that analyzes complex patient data from clinical trials to identify causal relationships and improve patient stratification. Powered by Attractor AI, a proprietary long-range attractor algorithm, the platform uncovers hidden correlations and defines patient characteristics to enhance trial efficiency and reliability. NetraAI generates insights to improve inclusion/exclusion criteria, leading to larger effect sizes and lower p-values, while also identifying patients eliciting a placebo response. The platform's multidimensional patient profiling is enhanced through large language models, providing explainability and augmenting insights with extensive medical and scientific literature.
Target Audience
The primary target audience includes clinical trial professionals, medical scientists, and researchers in pharmaceuticals and biotechnology seeking to improve clinical trial design, patient stratification, and efficacy analysis.
Features
- Attractor AI: A proprietary long-range attractor algorithm for deciphering hidden patient correlations and identifying causal factors.
- NetraAI: Analyzes patient populations to enhance the efficiency and reliability of clinical trials.
- NetraPlacebo: Identifies patients eliciting a placebo response by combining attitudinal, psychological, and historical trial data.
- NetraGPT: Adds explainability to NetraAI using large language models and extensive medical literature.
- Improves inclusion/exclusion criteria: Generates insights to maximize the responsive patient population.
- Multidimensional patient profiling: Enhances patient profiling through the perspective of medical and scientific literature.