InsightRX Unveils Apollo Gold, a Powerful New Tier of the Apollo Analytics Platform

  • Published April 30, 2024

SAN FRANCISCO, April 30, 2024 – InsightRX – which provides cloud-based precision medicine software to optimize treatment decisions – announced the immediate availability of a new, premium tier of the company’s Apollo analytics platform that provides comprehensive insights into clinical performance aimed at improving departmental treatment policies and protocols. 

InsightRX Apollo provides customers with real-time metrics on the effectiveness of precision medicine programs, enabling users to identify clinical impact, recognize opportunities for improvement, and accelerate process improvement initiatives. 

"Facilitating data-informed decisions through robust analytics is core to our mission," stated Sirj Goswami, Ph.D., CEO and co-founder of InsightRX. "Our customers seek deeper insights to enhance patient care. Apollo Gold represents a significant step forward in precision, offering a pathway to actionable data that will benefit patients, clinicians, provider organizations, and the entire healthcare system."

A key use case for Apollo is to monitor antibiotic stewardship programs. The ‘Goldilocks nature’ of under or over-dosing vancomycin runs the risk of developing antibiotic resistance or acute nephrotoxicity and acute kidney injury (AKI), leading to worsening (and potentially fatal) patient conditions, longer hospital stays, and higher costs of care. AKIs impact nearly a half-million patients in the U.S. annually, costing an extra $4.7 billion to $24.0 billion in healthcare costs each year. 

Want to learn more about Apollo Gold? Vanessa Burns shares InsightRX's vision for the new tier in an updated product vision statement here.



About InsightRX
InsightRX is a healthcare technology company that develops cloud-based applications for precision medicine and clinical analytics designed to individualize treatment at the point of care. The platform leverages patient-specific data, pharmacology models, and machine learning to understand each patient’s unique kinetic profile and can be integrated seamlessly within operational workflows.