Renalytix AI plc announced a collaboration with AstraZeneca to develop and launch precision medicine strategies for cardiovascular, renal and metabolic diseases. The first stage in the collaboration will use KidneyIntelX, an artificial intelligence-enabled in vitro diagnostic platform, to examine further improving outcomes for patients with chronic kidney disease (CKD) and its complications, in coordination with the Mount Sinai Health System. The goal of the first stage is to help improve guideline-based standard-of-care for optimal utilization of existing and novel therapeutics using the KidneyIntelX testing platform and proprietary care management software. An estimated 700 million patients worldwide have CKD,1 which is also associated with an increased risk of metabolic and hematologic complications, such as hyperkalemia (elevated levels of potassium in the blood) and anemia.2,3 The first stage will assess the impact of AI-enabled in vitro diagnostic solutions to optimize utilization of therapeutics in CKD under current standard of care protocols.

RenalytixAI is a developer of artificial intelligence (AI) enabled clinical diagnostic solutions for kidney disease, one of the most common and costly chronic medical conditions globally. RenalytixAI's solutions are being designed to make significant improvements in kidney disease risk assessment, clinical care and patient stratification for drug clinical trials. RenalytixAI's technology platform will draw from distinct sources of patient data, including large electronic health records, predictive blood-based biomarkers and other genomic information for analysis by learning computer algorithms. RenalytixAI intends to build a deep, unique pool of kidney disease-related data for different AI-enabled applications designed to improve predictive capability and clinical utility over time. In 2019, RenalytixAI expects to launch KidneyIntelXTM, an artificial intelligence in vitro diagnostic product intended to support physician decision making by improving identification, prediction, and risk stratification of patients with progressive kidney disease.

The role of artificial intelligence (AI) in healthcare continues to rise. According to a June 2018 ABI Research report, the number of patient monitoring devices, which also includes AI for home-based preventative healthcare, that use data to train AI models for predictive analytics will be 3.1 million in 2021, up from 53,000 in 2017. That connectivity is predicted to save hospitals around $52 billion in 2021. "We now have exponential increases in digital healthcare data due to the internet, electronic health records, personal health records, cellphones, wearable devices, digital medical devices, sensors and many other factors," said Drew Gantt. "This data will fuel algorithmic solutions, clinical decision support tools, and visual tools in the near term."

The role of artificial intelligence (AI) in healthcare continues to rise. According to a June 2018 ABI Research report, the number of patient monitoring devices, which also includes AI for home-based preventative healthcare, that use data to train AI models for predictive analytics will be 3.1 million in 2021, up from 53,000 in 2017. That connectivity is predicted to save hospitals around $52 billion in 2021. "We now have exponential increases in digital healthcare data due to the internet, electronic health records, personal health records, cellphones, wearable devices, digital medical devices, sensors and many other factors," said Drew Gantt. "This data will fuel algorithmic solutions, clinical decision support tools, and visual tools in the near term."

The role of artificial intelligence (AI) in healthcare continues to rise. According to a June 2018 ABI Research report, the number of patient monitoring devices, which also includes AI for home-based preventative healthcare) that use data to train AI models for predictive analytics will be 3.1 million in 2021, up from 53,000 in 2017. That connectivity is predicted to save hospitals around $52 billion in 2021. "We now have exponential increases in digital healthcare data due to the internet, electronic health records, personal health records, cell phones, wearable devices, digital medical devices, sensors and many other factors," said Drew Gantt. "This data will fuel algorithmic solutions, clinical decision support tools, and visual tools in the near term."

Mount Sinai Health System on Friday announced an exclusive multiyear license and partnership with RenalytixAI, an artificial-intelligence startup with offices in New York and the United Kingdom. The goal is to reduce the $98 billion in preventable kidney disease and dialysis costs by predicting which patients are at the greatest risk of advanced kidney disease and taking steps to treat them early on. The venture will draw from the more than 3 million electronic health records in Mount Sinai's system, plus an additional 43,000 patient records in Mount Sinai's BioMe BioBank, part of the Charles Bronfman Institute for Personalized Medicine. The bank collects DNA and blood serum from a diverse patient base to identify biomarkers, substances that can indicate disease, infection or environmental exposure. All data will be de-identified to protect patient privacy "We can look at relationships that we could never look at before," said RenalytixAI CEO James McCullough.