The digital phenotyping platform, PhenOM, is delivering personalized and actionable healthcare insights around diagnosis, treatment, risk, utilization, and clinical trials
OM1, a leading real-world data, outcomes and technology company with a focus on chronic conditions, launched PhenOM, its artificial intelligence-powered platform for personalized medicine. Calibrated using OM1’s longitudinal health history datasets, PhenOM uses AI to identify unique digital phenotypes associated with conditions and outcomes and compare patients’ records to them to highlight risks and opportunities. PhenOM powers personalized healthcare insights at scale across the entire healthcare ecosystem, from life science research to point-of-care clinical decision making.
AiThority Interview Insights: AiThority Interview with Joshua Wilson, Commercial Director, JAPAC at Crimtan
“Most people have now heard of the promise of AI through GPT-4, but we still have not seen many really mature, real-world clinical applications using advanced language models”
PhenOM is an AI that gathers detailed information from large patient datasets – including unstructured clinical notes and disease activity metrics – to isolate unique patterns associated with patients with distinct characteristics. PhenOM synthesizes these patterns into unique digital phenotypes or ‘fingerprints.’ These phenotypes can be studied to inform research and deployed in real-world datasets – inside and outside OM1 – as well as in health systems and through standalone patient-facing web portals.
Calibrated using OM1’s differentiated, high-quality data cloud – which is based on billions of data points from more than 300 million patients – PheonOM was built with expert clinician oversight. With an overarching mission to improve individual care and population health, the platform powers five solutions that address pain points across the healthcare system:
- Diagnostic Insights: Finding patients with rare, undiagnosed, or misdiagnosed conditions, including subgroups of interest
- Treatment Insights: Personalizing treatment recommendations to improve access to care and individualizing treatment selection
- Risk Insights: Predicting risk of specific negative outcomes, including disease progression, complications, and catastrophic events
- Utilization Insights: Enabling focus on patients at risk for higher utilization, and utilization growth, over time
- Clinical Trial Insights: Accelerating trial startup and recruitment by identifying patients most likely to meet qualifications for enrollment, including those potentially overlooked
Read More about AiThority Interview: AiThority Interview with Rick Farnell, Chief Executive Officer of Tracer
Patient expectations over the last several years have shifted – from the adoption of virtual care and accessibility to the use of advanced technology to improve outcomes – but a persistent gap remains between population-level insights and individual patient experience: personalization. Recognizing this gap, OM1 developed PhenOM to translate patterns in large-scale data into meaningful outputs at the individual level and to better understand patient populations, diagnoses, progression, and treatment response.
“Most people have now heard of the promise of AI through GPT-4, but we still have not seen many really mature, real-world clinical applications using advanced language models,” said Dr. Joseph Zabinski, Managing Director of AI & Personalized Medicine at OM1. “PhenOM is groundbreaking technology because it uses AI to translate actionable insights from our highly enriched datasets and phenotyping technology into opportunities for more personalized healthcare. This capability creates a huge potential for impact for all stakeholders, from identifying patients with under-diagnosed conditions to enabling personalized assessments of benefit for particular therapies and accelerating clinical trial enrollment.”
Latest AiThority Interview Insights : AiThority Interview with Oji Udezue, Chief Product Officer at Typeform
[To share your insights with us, please write to sghosh@martechseries.com]
Comments are closed.