Day 3 The Future of Nutrition Technology
Healthier Through Optimized Grocery Shopping
FOOD IS MEDICINE Let food be thy medicine and medicine be thy food Hippocrates
Our Mission is: To Improve Overall Health & Reduce Preventable Healthcare Costs through better Nutrition
OUR DIGITAL NUTRITIONAL ECOSYSTEM Virtual supermarket presence with 300k products and price comparisons 30,000 data-connected supermarket locations and online retailers Food brand manufacturers and growers Farmers markets and farm share programs Educational content and food scoring Worksite cafeterias and vending machines
Restaurants ( in progress) Employers and Health Plans
NUTRISAVINGS FOOD CLOUD Food Data • 300,000 UPC/PLU • Nutrition Facts • Ingredients • Package Claims • Certifications • Product Image • Origin/Traceability
Enhanced Food Data • Quick Facts • Attributes • Allergy Flags • NutriSavings Score • Trade Up Recommendations
Marketing Data • Weekly Sales • Coupons • Purchase Data • Pharmacy Data
Behavioral data: • Purchase behavior • Menu planning • Diet adherence • Health Prevention • Personalization • Affordability • Progress Tracking
NutriSavings Food Cloud
Employer Data • Demographics • Age, Gender • Family • Socio Economic Data
Health Plans data • Pharmacy • Medical claims • Population health outcomes
Lifestyle data: • • •
Exercise Bio markers Progress tracking
ENHANCED PROFILE FOR GROCERY OPTIMIZATION
Personalization and optimization of the grocery purchase experience based on lifestyle, budget and health status.
Leads to better buying decisions and better health outcomes
NATIONAL MEASUREMENT OF CHANGE NutriSavings Score
2015
2016
2017
NUTRISAVINGS IS IMPROVING HEALTH OUTCOMES and as a Result, Reducing Healthcare Costs. Two Case Studies with Impressive Results:
7% Reduction in pre-diabetic population Savings of $7,900 annual per employee
21% reduction in hypertensive population
Savings of $1,320 annual per employee
6.3% reduction in obese population Savings of $28,000 annually
FOOD: A MAJOR DRIVER FOR HUMAN DEVELOPMENT
HUMAN DEVELOPMENT
▪ Total population 7.3BN People
3 Key Drivers
1. Well Being
▪
2. Education
3. Wealth
1BN fewer people living under extreme poverty
▪ Morbidity rate in children under 5 reduced by 43% ▪ Underweight children reduced by 60% in LATAM countries
•
Sources: Human Development Index 2018/PNUD; FAO (Food and Agriculture Organisation of the United Nations. Food and Nutrition Security in Latin America 2017
HUMAN DEVELOPMENT 3 Key Drivers
1. Well Being
FOOD SAFETY ALARM
2. Education
3. Wealth
FOOD SECURITY Availability Accessibility Use
Nutrition drives neural configuration
FOOD SECURITY
POLICY MAKERS
FOOD INDUSTRY
NUTRITIONAL SCIENTESTS
CHALLENGES & OPPORTUNITIES FOOD POLICY PROGRAMS & RECOMMENDATIONS SOCIAL / CONSUMER NEEDS
BRAIN DEVELOPMENT
URGE FOR INNOVATION
INNOVATION, TECHNOLOGY & NUTRITION
FOOD INDUSTRY DEVELOPMENTS
HTA / SOLUTIONS
INNOVATION IN FOOD INGREDIENTS
ACT WITH URGENCY
NUTRITIONAL SCIENTISTS
FOOD INDUSTRY
POLICY MAKERS
1. Well Being
2. Education
3. Wealth
ARTIFICIAL INTELLIGENCE LIFE SCIENCES AND HEALTHCARE
October 2018
INTELLIGENT BEHAVIOR
Recognize Objects and Events
Identify Signals and Patterns
Categorize and Classify
Remember and Retrieve
Interpolate and Extrapolate
Gauge Value or Importance
Connect Disparate Facts
AI TASKS AND ACTIVITIES Knowledge
Acquisition
Knowledge
Representation
Learning
and Inference
Knowledge
Retrieval
Developing
Trust Metrics
AI METHODS AND TOOLS
Logic Systems
Probability
Statistics
Linear Algebra
Ontology Design
Quantitative Graph Analysis
Topic and Concept Mining
….The Field Still Awaiting Its Albert Einstein….
THE EIGHT PILLARS OF AI ► Taxonomies and Ontologies ► Logical Formalisms ► ► ► ► ►
Analogical Reasoning Bayesian Methods Connectionism Evolutionary Methods Reinforcement Learning
► DNA (not what you are thinking)
CRITICAL NEED FOR SMARTER TOOLS CURRENT
Siloed Data Warehousing Ad Hoc Analysis Ad Hoc Reporting Low Resolution Process Tracking
CHANGE
SITUATION:
REQUIRED:
Integrated Multiscale Data Automated Model Development Seamless Informatics-Based Evidence Adaptive Workflow and Processes
AREA A Population Models
AREA B Pathway Analysis
Patient stratification and model development based on:
Pathway analysis and biomarker discovery based on:
• • • • •
Demographics Diagnostics Therapeutic history Adverse events Home and work environment • Family and social profile
• • • • • •
Genomics Proteomics Metabolomics Lipidomics Glycomics Transcriptomics
AREA C Chemical Characterization
Chemical characterization and model development based on: • 2D/3D chemical structures • Measured physiochemical properties • Computed stereochemical properties • Toxicity assays for different structures/targets/species • Structural alerts and AOPs
RATIONAL EXPERIMENTATION
► Strength
► Consistency ► Specificity ► Temporality ► Biological Gradient ► Plausibility ► Coherence ► Experiment ► Analogy
IN SILICO BIOLOGIST
DATA ASSESSMENT
MODEL ASSESSMENT
ACTIONABLE INFORMATION
ACTIONABLE INFORMATION
PILOT PROJECTS
Drug Properties
Chemical Toxicity
Pathway Identification
Cardiovascular Disease
Cancer Treatment Adherence
Pathogen Infection
Cancer Diagnostics/Prognostics
Lab-on-Chip Technology
Drug Development
Separation Mixture
Personalized Nutrition
Home Compounding Food-as-Drug
The Use of AI for Pathway Analysis and Nutrient Drug Testing in Degenerative, Neoplastic and Infectious Diseases
Dennis A. Steindler, Ph.D. Senior Scientist Director, Neuroscience and Aging Lab JM USDA HNRCA, Friedman School, Sackler School of Biomedical Sciences, CTSI, Tufts University
Š Tufts University, Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging
Studying iPS-, Adult Tissue Derived- and Cancer Stem Cells simultaneously provides insights into potential Stem Cell Pathologies‌.And also provides a sensitive and reliable bioassay for screening new AI-generated therapeutic approaches.
Infectious Transcellular Transmission of Toxoplasma gondii, Viruses, Toxins and Other Pathogens‌Infect Human Neural Stem Cells and Affect Neurodegenerative, Neoplastic and Inflammatory Gene and Protein Networks
Walton et al., Development, 2006; Ngo et al Scientific Reports, 2017
Steindler and Reynolds, Adv Nutrition, 2017; Deleyrolle et al., in prep
Machine Learning….AI....and Personalized/Precision Standard of Care, Integrated and Regenerative Medicine
“…Tufts Analytics Platform (TAP), a software engineering initiative to develop better tools for multiscale modeling of chemical, biological and clinical systems. A major objective of the initiative is to increase the use AI and Machine Learning technologies to discover and characterize complex biological mechanisms driving health and illness in a manner not possible through traditional research methods….” J. Gormley
Thank you to all our sponsors!