ReviveMed is a precision-medicine platform that utilizes AI to analyze over 10,000 metabolites, creating digital metabolic twins that provide insights into patient-specific disease and drug response. This technology enables accurate predictions of immunotherapy effectiveness in cancer patients, addressing the challenge of low response rates and adverse effects associated with current treatments.
Funding
$6M 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
Cancer immunotherapy, while revolutionary, benefits fewer than 20% of patients, while over 35% experience severe immune-related adverse events. Current methods lack the ability to accurately predict individual patient response to immunotherapy before treatment, leading to ineffective treatments and unnecessary side effects. Existing metabolic health assessments rely on limited metrics like BMI and fasting glucose, failing to capture the full picture of an individual's metabolic state.
Solution
ReviveMed offers a precision-medicine platform that leverages AI to analyze over 10,000 metabolites, creating "digital metabolic twins" that provide patient-specific insights into disease and drug response. This technology enables accurate prediction of immunotherapy effectiveness in cancer patients, addressing the challenge of low response rates and adverse effects. The platform characterizes significantly more metabolites than other platforms, using this large-scale metabolomic data to create computer representations of metabolic processes within multi-omic contexts. These digital twins also predict metabolic health beyond traditional metrics, assessing the risk of type 2 diabetes, cardiovascular disease, and other chronic conditions. By integrating metabolomics data with AI, ReviveMed aims to optimize clinical trial design, identify novel drug targets, and improve patient stratification.
Target Audience
The primary target audience includes oncologists, researchers, and pharmaceutical companies focused on precision medicine, immunotherapy, and metabolic health.
Features
- AI-powered analysis of over 10,000 metabolites to create digital metabolic twins
- Prediction of patient response to cancer immunotherapy before treatment
- Identification of immuno-metabolic mechanisms associated with disease progression
- Assessment of metabolic health beyond BMI and traditional lipid panels
- Integration of metabolomics data with ctDNA tests to improve accuracy
- Proprietary pre-trained foundation models for fine-tuned AI model development
- Identification of novel biological insights for drug target discovery and indication expansion