
Prevention Is
Always Better
Than Cure
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About Us
Our team led by first class clinicians are always on hand to help progress your journey with Phoreverhealth, supporting you to improve and extend life. At Oxcitas our mission is to extend healthy human life: unearthing the mechanisms of ageing using ground-breaking AI drug development pipelines. Our proprietary approach allows us to model multi-dimensional ageing biomarker dynamics to discover relationships at scale and with lightning speed.
Our Trained Staff
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Dr. Garth Cruickshank
HEAD OF LABORATORY
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dr. phil brooks
HEAD OF PHYSICIANS
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dr. david buckley
HEAD OF PHARMACY
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Services
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Pharmacy
ISO - 9001 certified
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Physicians
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Laboratory
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Tests
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consultancy
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Diagnostics
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planning
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Healthcare
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Insight
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What is the relationship between ageing and disease ?
Whilst the FDA and NHS do not recognise chronological ageing in itself as a disease, we increasingly are able to recognise changing values of biological markers that correlate with progressive age – so called biological clocks.
“If BIOLOGICAL AGE IS GREATER THAN CHRONOLOGICAL AGE There is problem”
These biological markers however vary individually with other factors such as illness, and drugs, and across populations from different world regions. Hence using them individually to predict age is unreliable. But, by combining measures of a broad range of these biological markers which reflect many bodily functions, in a machine learning and AI computing platform, allows us to elicit data patterns which reliably predict age. Importantly where we have the knowledge of a subjects age but a ‘pattern’ which disagrees we can ask if the biological clocks are implying that the longevity of the subject is at risk.
Smith (1962) described the ageing processes as “those which render individuals more susceptible as they grow older to the various factors, intrinsic or extrinsic, which may cause death.” This allows us to ponder upon what those factors might be. However, the wording seems to indicate the homeostatic state of the subject whereas we increasingly recognise specific diseases and syndromes that appear to influence the ageing process, many of which are now susceptible to treatment.
One could take the more passive view of Castle and McCrae (1995) who suggest that “ageing is what happens to an organism over time” However for an individual whose wellbeing is at risk we would argue in favour of trying to identify and repair the ageing processes noted by Smith.
Hence our approach has been to look at a large number of biological markers and through the process of computation and pattern definition identify the key 30 or so markers that reliably indicate age. From this platform we can now screen individuals not only for how they match up chronologically to these marker projections, but also biologically from the individual and pattern defining markers, to show where an individual may be developing potential lifetime reducing problems. With this knowledge we can suggest how an individual can harness this information to improve their future, by changes in lifestyle, diet or therapy and monitor the impact of these, or by seeking medical specialist advice where appropriate.
Scientific & Reference
Scientific
Each biomarker has its own characteristic and varies with age, it forms a profile to predict age. Creating a signature.
Connect biomarkers to ageing.
Use the example of;
Insulin Like Growth Factor – variation with age
Insulin Like Growth Factor – variation with insulin resistance


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