The Pillars of Personalized Medicine
IndividuALLytics® is a data-driven, evidence-based company and as such we believe that good, frequent and consistent measurement (i.e. time-series data), viewed through the lens of small data analytics can uniquely inform treatment decisions for patients and practitioners. This requires the thoughtful integration of four pillar key sciences:
Highest Quality Multiple Chronic Condition Evidence-Based Clinical Care Cycle
Our approach to research, science and solution development is built upon the existing evidence. However, this is just the beginning because each person’s response to treatments is as different as their life styles, circumstances and values. The IndividuALLytics® framework builds upon the concept of P4 medicine (i.e. predictive, preventive, personalized, participatory).[1] [2] By using this framework coupled with the vision of small data and our proprietary N-of-1 analytics technology (IndividuALLytics Quotients or IAQplus™) allows for patient level science that informs the patient and practitioner about that patient’s unique response to treatment. This framework provides for adjustments and additions to treatment with quicker and more efficient treatment iterations based on their particular treatment response. (See Chronic Condition Specific IAHealthQuests).
This does not conflict with the traditions of the randomized clinical trial, nor is it inconsistent with a Big Data strategy or leveraging genomics. Our approach to small data is complementary and can add considerable new knowledge to treatment outcomes, patient needs and the personalization of care. When N-of-1 outcomes are aggregated, novel new response patterns emerge. It’s where population health meets precision medicine for best quality chronic condition care.
If you are patient, family/friend caregiver, provider, payer, digital health leader or other interested person, then please complete the Contact Us form to get more information and monthly news on improving multiple chronic condition care.
For more information and supportive documentation see selected articles listed below:
[1] Hood, L, et al. Systems biology and new technologies enable predictive and preventative medicine. Science306 (5696), 640-643 (2004).
[2] Flores, M et al. P4 medicine: how systems medicine will transform the healthcare sector and society. Personalized Medicine, 10 (6), 5656-576 (2013).
Expanded Information for a Better Understanding of Personalized Medicine and Related Information.
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