University of Harvard group and Dr. Eric Topol's interpretation of new Nature paper validates Algocyte's and OIA's main value proposition
Traditional blood testing often relies on standard reference ranges based on population averages to inform clinicians and patients, but new results on 12,000 adults who received multiple Complete Blood Count tests across 20 years, show that individuals have unique features that effectively act like health fingerprints. This new study published in Nature shows that these personalised benchmarks can significantly improve early disease detection by providing a better and more precise picture of an individual health.
“Our study suggests CBCs vary a lot from person to person even when completely healthy.” A more personalized approach could give more insight into a person’s health or disease.”
A Complete Blood Count or CBC is the most common diagnostic test and most popular blood test with over 4 Billion of them performed every year world wide, 500 million only in the U.S.
The test is deeply related to the immune system and is a key diagnostic tool that can be informative for a number of diseases and conditions including infection, inflammation, cancer, anaemia, heart disease, and more.
“For all the talk of “personalized medicine” over the last two decades, potentiated by the human genome sequence, this enriched interpretation of one’s lab test would be simple to implement with further validation and the right computing platform, ideally using multimodal A.I. that integrates the electronic record, labs, scans, and rest of a person’s many layers of data”
Dr. Eric Topol’s description of such a system is what the Algocyte® platform implements, effectively instantiating a solution for personalised medicine on these findings and by using A.I. on common blood marker behaviour to learn each person’s individual reference values over time.
“The clinical world seems to be catching up with OIA’s value proposition based on our research that led to the development of Algocyte. Algocyte effectively implements the solution for these findings and represents a step towards population-scale precision medicine, offering tailored care based on individual common markers.”
Algocyte® compares a user blood test results to their own historical data, rather than to generic population standards from which clinicians can identify subtle changes that may indicate early stages of blood- and immune-related conditions. It also combines with multimodal data, including their own clinical history, lifestyle and events.
Algocyte®, developed by Oxford Immune Algorithmics® (OIA), is a set of AI causal-driven solutions that enable remote digital endpoints in healthcare pathways to understand health and disease based on adaptive, personalised and precision blood testing.
Oxford Immune Algorithmics® is a deep-tech start-up associated with UK's Golden Triangle, the universities of Oxford, Cambridge and King's College London that applies Artificial General Intelligence (hybrid causal predictive & generative AI) based on symbolic regression and program synthesis to deliver decentralised mission-driven solutions to everyone today.
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