LUMIQO offers a healthcare‑grade AI platform that automates the capture, identification, and reporting of adverse events directly from electronic health record systems for oncology research teams. By integrating clinical expertise with AI and data science, it streamlines safety data workflows, reducing manual effort and accelerating the progression of cancer drug trials from discovery to patient delivery.
Funding
Funding not disclosed
Founders
Product
Problem
Oncology clinical trials still rely on manual, paper‑based processes to capture and report adverse events, leading to extensive labor, data duplication, and delays in safety reporting. These outdated workflows increase operational strain on research teams and can slow the delivery of new cancer therapies to patients.
Solution
LUMIQO offers a healthcare‑grade AI platform that automates the identification, capture, and reporting of adverse events directly within existing electronic health record (EHR) systems. By integrating clinical expertise with machine‑learning models, the solution extracts safety data from routine clinical documentation, reducing the need for manual entry. The platform standardizes data across sites, validates entries, and generates regulatory‑compliant reports in real time. This automation shortens the safety data workflow, lowers labor costs, and accelerates trial timelines, helping oncology research teams keep pace with rapid therapeutic innovation.
Target Audience
Primary customers are oncology research teams and clinical trial sponsors that manage safety data within EHR systems, including academic medical centers and pharmaceutical companies conducting cancer trials.
Features
- AI‑driven extraction of adverse event information from structured and unstructured EHR data
- Seamless integration with major EHR platforms, eliminating duplicate data entry
- Automated validation and formatting of safety data to meet regulatory reporting standards
- Real‑time generation of adverse event reports with audit trails for compliance
- Dashboard for research teams to monitor safety metrics and workflow efficiency