When medicine is informed solely by clinical practice guidelines, however, the patient is not treated as an individual, but rather as member of a group.
Personalized medicine, is the use of information derived from knowing the patient as a person.
How can digital health contribute ?
Datasets around an individual concern personal health but also factors not directly related but which can have an influence.
Datasets can concern and individual health such as clinical images, clinical data (history…), genetic data….together these are called personomics. [nique biological characteristics are defined by the tools of precision medicine: genomics, proteomics, metabolomics, epigenomics, pharmacogenomics, and other ″- omics. ″]
Datasets can be matched with an individual such as weather, sunshine….
Sounds complicated: an example please !
We believe personalised medicine can help in the management of chronic skin conditions such as Atopic Dermatitis. It’s a research question.
In order to investigate this we would like to measure the evolution of the skin condition together with other data.
More precisely, we are working in Madagascar which is an elongated country as well as with different, climates altitude and weather.
A lot remains unknown in the pathogenesis of Atopic Dermatitis, and subsequently in the prediction of flares.
Clinically these are easy to note and the level of itch, sleeping disturbance and severity index evolve.
As a research question and potentially a solution we would like to correlate the evolution of the condition with environmental data.
It is therefore hoped that altitude, humidity, latitude, sunlight exposure, urban or rural geolocalisation can be collected. With sunlight exposure we can infer vitamin D production levels (correlate with the skin color of the subject)