Driving Clinical Trial Efficiency and Diversity
Automate Site Selection and Patient Recruitment Plan Generation
Driving Clinical Trial Efficiency and Diversity
Automate Site Selection and Patient Recruitment Plan Generation
Automate Site Selection and Patient Recruitment Plan Generation
Automate Site Selection and Patient Recruitment Plan Generation
Our mission is to optimize clinical trials by making them inclusive, efficient, and accessible through data-driven, automated site selection and targeted patient recruitment and retention planning.
Clinical trials face challenges in recruitment and site selection, causing delays and limiting diversity. By leveraging innovative technology and data-driven solutions, we accelerate timelines, broaden access, and ensure more inclusive, reliable outcomes.
Karneyium's flagship platform, TerraTrials™, combines SDOH with spatial AI to deliver hyperlocalized patient recruitment and engagement strategies. By targeting underserved populations and optimizing site selection, we enable faster, more inclusive trials with tailored outreach that drives impactful results.
TerraTrials™ is Karneyium's real-time geospatial platform powered by Spatial AI, Social Determinants of Health (SDOH) and clinical data. It automates site selection, models enrollment curves, and delivers hyperlocalized recruitment strategies.
We ensure data safety with HIPAA, HITECH, and GDPR compliance, using encryption, audits, and team training. Transparency and third-party vetting reinforce our commitment to protection standards.
TerraTrials™ integrates real-world data, SDOH, and clinical data to automate site selection and deliver hyperlocalized recruitment plans, ensuring efficient, diverse, and impactful trials.
TerraTrials™ uses GenAI and customized LLM workflows to provide data-driven insights, guiding hyperlocalized strategies for patient recruitment, retention, and site selection, enabling faster, smarter, and more inclusive trials.
TerraTrials™ uses AI to balance recruitment speed with diversity goals, modeling enrollment curves and predicting site performance to ensure efficient, inclusive trials.
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