In this sixth episode, Tommy Wood, Chief Scientific Officer of Nourish Balance Thrive, explains that the majority of modern disease is caused by our environment and as such, under our control.

Read the transcript

He shares his experience that A.I. coupled with ordinary blood tests, can inform us of changes we can make to protect/optimize our health, or when sick, lower the cost by predicting which further tests to conduct.

delete this row ---- In this sixth episode, Tommy Wood, Chief Scientific Officer of Nourish Balance Thrive, explains that the majority of modern disease is caused by our environment and as such, under our control.
Topics we discussed in this episode

Most chronic disease (e.g. diabetes, Alzheimer's, arthritis, certain cancers) we could eliminate by controlling our environment (e.g. diet, sleep, toxic exposures)
Sustaining long-term health by preventing, or slowing down the aging processes
Predicting chronic disease based upon subjective quality of life questionnaires or with the inclusion of simple blood tests, processed by machine learning algorithms
Prediction of biological age based upon simple blood tests, processed by machine learning algorithms
Personalizing lifestyle interventions to achieve longer health and life spans, using only simple blood chemistry processed with machine learning
Nourish Balance Thrive’s Blood Chemistry Calculator
Nourish Balance Thrive’s Elite Performance Analysis Tool
Laboratory biomarker ranges are averages derived from a sick population rather than a healthy nor optimized health population
Predicting where an individual's health may be further optimized (e.g. nutrient deficiencies, heavy metal loads, hormone levels) using only cheap blood tests processed by machine learning algorithms
Humans (e.g. doctors) would be unable to see valuable patterns in cheap blood test data
Lack of biological data derived from healthy individuals, masses of data derived from sick individuals
Groups working on health optimization as opposed to orthodox healthcare’s focus on sick care
Non-pathological insulin resistance, physiological insulin resistance
Elevated fasting glucose and predicted biological age
Genomics can’t optimize an individual's diet and lifestyle, at least at present
An individual's diet and lifestyle can be optimized today through subjective questionnaires and simple blood chemistry processed by machine learning algorithms
Most chronic disease is a metabolic disease
Ancestral health approach prevents or even reverses chronic disease; advanced technologies not needed
Digital phenotyping
Need to filter tap water and other environmental controls to protect our health span
The likelihood that most of the healthy population is in fact not “healthy”; the bar of “healthy” has been lowered so people don’t know of a “more well”
Gut issues underlie or contribute to many health issues we see today
Building tools that can track underlying trends or patterns in our blood biochemistry so that we can know if lifestyle interventions are working for us
Nutritional epidemiology is a broken science
Democratizing functional medicine
Engineering sustained health

Show links

Nourish Balance Thrive Website
Blood Chemistry Calculator
Elite Performance Analysis Tool
Digital Phenotyping Wikipedia Entry
Insilico Medicine Biological Age Prediction Calculator
Kenneth M. Ford Wikipedia Entry
Bryan Walsh Website
Institute for Human and Machine Cognition (IHMC) Website
Chris Kelly LinkedIn Profile
What is Functional Medicine Article
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