Monday, 01 June 2020

SIME completes study validating clinical AI platform in RDS

06 May 2019 | News

Data demonstrating that AI accurately predicts Respiratory Distress Syndrome (RDS) in premature babies, enables company to accelerate product development and begin next phase clinical studies in Europe, the US and China

SIME, a Clinical AI company generating unique biological data to deliver life-saving solutions, announced the publication of its pivotal 'Fast Assessment of Lung Maturity at Birth' study. The study validates the first application on the company's patented AI Platform: a rapid point-of-care neonatal Lung Maturity Test (LMT).

Building on previous clinical data published in 2016, the 'Fast Assessment of Lung Maturity at Birth' study demonstrates that by measuring lung maturity biomarkers, AI can predict Respiratory Distress Syndrome (RDS) with high accuracy (91% sensitivity) moments after birth.

RDS is the leading cause of mortality and morbidity in premature babies, and although it can be alleviated with immediate treatment, there is currently no clinical tool that is able to predict the disease fast enough to be clinically effective. LMT generates the information needed to screen millions of babies for RDS each year, addressing one of the most urgent unmet needs in neonatology.

SIME's novel Data Engine generates unique data from biological samples at the point of care. These data are then analysed by the platform's proprietary AI algorithms to predict disease, discover new biomarkers and develop life-saving tools for doctors and nurses.

LMT is the first example of how this technology, and the data it generates, can be used to deliver preventative care, improve outcomes and reduce healthcare costs.      

Completion of the study has enabled SIME to accelerate platform development, and begin next phase clinical studies of LMT in China, Europe and, following a recent clinical partnership agreement, the US. Keeping with the company's commitment to full clinical data transparency, all study results will be published and disseminated.


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