Akkure Genomics, a leading Irish digital AI health company has announced details of a ground-breaking project which is aimed at developing clinical trial matching technologies for precision medicine augmenting Microsoft’s “Health Insights” AI technology.

The “Clinical Trial Matcher” is an enterprise grade AI model that matches patients to potentially suitable clinical trials, according to the trial’s eligibility criteria and patient data. The model helps with finding relevant clinical trials that patients could be qualified for, as well as with finding a cohort of potentially eligible patients for a list of clinical trials.

Today there are more than 82,000 clinical trials actively recruiting participants worldwide, with increasingly complicated trial eligibility criteria. However, enrollment in clinical trials is based on manual screening of millions of patients, each with up to hundreds of clinical notes requiring review and analysis by a healthcare professional, making it an unsustainable process. Given this, it is not surprising that up to 80 percent of clinical trials miss their clinical trial enrollment timelines, and up to 48 percent fail to meet clinical trial enrollment targets according to data provided by Tufts University. The Clinical Trial Matcher model aims to solve this exact problem by effectively matching patients with diverse conditions to clinical trials for which they are potentially eligible through analysis of patient’s data and the complex eligibility criteria of clinical trials.

Akkure Genomics helps patients utilise their own genomic data or DNA to improve their chances of finding a clinical trial. Commenting on the deployment, Dr Oran Rigby, Founder of Akkure Genomics commented “At AKKURE GENOMICS we leverage Project Health Insights, which empowers our own AI and digital DNA platform capabilities, to help patients get matched to clinical trials based on their individual medical diagnoses, thus boosting enrollment, improving the chances of finding a precision-matched trial and accelerating discovery of new therapeutics and cures.”

Hadas Bitran, Partner Group Manager with Microsoft Health and Life Sciences said “We live in an era with unprecedented increases in the size of health data. The potential benefit of leveraging this health data is enormous. There is a need for effective tools for extracting information that is buried in this data and using it to derive valuable insights, inferences, and deep analytics that can make sense of the data and support clinicians. These insights can assist healthcare professionals in understanding clinical data, like patient profiling, clinical trials matching, and more.”

Microsoft is also partnering with John’s Hopkins University Medical Center on its other “Health Insights” enterprise AI platform, the Oncology Phenotype, which is a model that enables healthcare providers to rapidly identify key cancer attributes within their patient populations with an existing cancer diagnosis.

Key Features of the Clinical Trial Matcher model include “Interactive Matching” where the model provides insights into missing information that is needed to further narrow down the potential clinical trial list and support for various modalities of patient data such as unstructured clinical notes, structured patient data, and Fast Healthcare Interoperability Resources (FHIR®) bundles. The trial matcher supports scenarios that are both Patient Centric and “Trial Centric” and supports search across built-in knowledge graphs for clinical trials.

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