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An overview of our science

Last updated:
Dec 19, 2020
Read time:
6 min
Figure 1: ZOE’s ongoing program of research.

ZOE’s mission

ZOE is a health science company that was founded on the belief that novel digital technologies can enable human research at an unprecedented depth and scale, in order to tackle global health issues. Our approach combines artificial intelligence, digital technologies and collaboration with leading scientists around the world. Our research ranges from the ongoing PREDICT studies, which is the world's largest in-depth nutritional research program, to an 800,000 person observational study to measure the accuracy of our AI diagnostic for COVID-19

ZOE believes that recent technological advances make it possible to carry out high-quality human research in a real-world setting, and therefore answer questions that have not previously been feasible. Combining large-scale biological data with machine learning and microbiome sequencing has enabled us to predict personal nutritional responses to foods and provide people with a better understanding of their unique metabolism and gut microbiome1. These personalized insights can allow individuals to make impactful changes to improve their overall health.

An overview of the problem

Non-communicable diseases (NCDs) impacted by dietary risk factors, such as type two diabetes and cardiovascular disease, are the leading cause of mortality and morbidity in the developed world, and continue to increase at alarming rates2,3,4,5. Unfortunately, current dietary and lifestyle approaches to tackle obesity and other major risk factors for these conditions are not achieving the positive impact that we all wish for. This is also true in developing countries, where a double burden of infectious and chronic diseases exists6.

Reducing diet-related risk factors associated with these conditions is one of the most impactful ways to reduce ill-health, as well as lessening their detrimental impact on individuals and society as a whole7,8,9. However, our recent studies have demonstrated that our responses to food are unique, and therefore a “one-size-fits-all” approach to diet is unlikely to be the best strategy to enhance health1. Therefore, ZOE’s ambition is to improve human health through precision nutrition by understanding how to eat the right way for our own biology and harness the potential power of the trillions of microbes in our gut.

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*due to be updated soon with further scientific updates.

ZOE’s scientific program

Our ongoing PREDICT program comprises the largest in-depth nutrition studies in the world to date. The PREDICT studies are designed so their data can be seamlessly combined in our machine learning models, enabling us to understand and predict personalized metabolic responses to foods, to provide people with nutritional recommendations tailored to their unique biology.

These clinical trials have allowed us to collect biological data in unprecedented detail from thousands of US- and UK-based study participants, on hundreds of thousands of meals. Using this data, we have been able to characterize and unravel what determines the huge variability in human responses to food. 

The first results from PREDICT have been published in the leading medical journal Nature Medicine in June 2020. These results have been used to create personalized “ZOE Scores” for individuals who use the ZOE product. More details about the PREDICT program can be found here.

Rethinking the future of nutrition

For many years, medication has been used as the first line of therapy for treating NCDs, yet dietary approaches have the potential to be more effective7,8,9. Nutritional science is now advancing at a rapid pace. However, due to the complexity of our bodies (with our thousands of biochemical pathways) and of foods (over 26,000 chemicals have been identified in our food10), we are only starting to scratch the surface in understanding how food impacts our health at an individual level.

In addition, recent research has highlighted the multiple interacting pathways linking diet, microbiome and health11,12,13,14. This has revealed how our microbiome can modulate the impact of food to transform our long term health and weight.

A key focus of ZOE’s PREDICT research program has been to explore and untangle the many interrelated and multidirectional determinants of our responses to food. This has allowed us, for the first time, to combine highly detailed analysis of thousands of gut metagenomes (all of the genes found in our gut microbes combined), with a detailed understanding of the individual’s characteristics (e.g. genetics, circulating blood metabolites), their metabolic responses to foods and health measures1.

A complex chain of unhealthy metabolic effects can be triggered after we eat. (Figure 2). Eating typical meals (which include protein, carbohydrates and fat) elicits short-term changes in blood fat and glucose levels (postprandial lipemia/ glycemia), as well as other circulating metabolites. Excessive lipemia and glycemia can overwhelm the body's normal, healthy regulatory responses, triggering a wide variety of unfavourable responses in blood lipids, rebound hypo-glycaemia, immune measures and hunger. Repeated often enough, these can lead to long-term inflammation, weight gain and chronic diseases such as diabetes and heart disease15,16,17,18.

Figure 2: Dietary inflammation involves a complex chain of unhealthy metabolic effects that can be triggered after we eat which, over months and years, can contributes to unfavorable health outcomes

Weight gain has typically been attributed to a failure to maintain energy balance (i.e. calories in = calories out)19. However, we now know that energy expenditure is highly dynamic and individual, and that both our microbiome and the food we eat can impact our metabolism. This explains, in part, why calorie reduction diets tend to fail for most individuals and is where personalized food guidance focused on quality for each individual rather than calories could have a big impact20.

Key learnings from our research

The key messages from ZOE’s research so far can be summarized in six areas:

Figure 3: Individual triglyceride, glucose and insulin responses varied widely between 1,102 healthy individuals in the PREDICT 1 study

Our research has shown that there is huge inter-individual variability in our responses to food which is mainly determined by non-genetic factors including the gut microbiome. Our ongoing ambition at ZOE is to take the latest discoveries from our research and make these available to everyone. We will do this by providing tests and personalized ZOE scores that reflect our latest research findings, using AI models to make precision nutrition a reality.

Get into the detail

Download the full white paper to get an in-depth understanding of how ZOE's science works

Download white paper (10MB)

*due to be updated soon with further scientific updates.


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  • Menke A, Casagrande S, Geiss L, Cowie CC. Prevalence of and Trends in Diabetes Among Adults in the United States, 1988-2012. JAMA. 2015 Sep 8;314(10):1021-9. doi:10.1001/jama.2015.10029
  • Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity and severe obesity among adults: United States, 2017-2018. NCHS Data Brief, no 360. Hyattsville, MD: National Center for Health Statistics, 2020. Available from: https://www.cdc.gov/nchs/data/databriefs/db360-h.pdf
  • GBD 2015 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388(10053):1659-1724. doi:10.1016/S0140-6736(16)31679-8
  • GBD 2017 Diet Collaborators. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;393:1958-72. doi:10.1016/S0140-6736(19)30041-8
  • Bygbjerg IC. Double Burden of Noncommunicable and Infectious Diseases in Developing Countries. Science. 2012 Sep;337:1499-501. doi:10.1126/science.1223466
  • Galani C, Schneider H. Prevention and treatment of obesity with lifestyle interventions: review and meta-analysis. Int J Public Health. 2007;52:348-59. doi:10.1007/s00038-007-7015-8
  • Slawson DL, Fitzgerald N, Morgan KT. Position of the Academy of Nutrition and Dietetics: The Role of Nutrition in Health Promotion and Chronic Disease Prevention. J Acad Nutr Diet. 2013 Jul;113(7):972-9. doi:10.1016/j.jand.2013.05.005
  • Schulze MB, Martínez-González MA, Fung TT et al. Food based dietary patterns and chronic disease prevention. BMJ. 2018;361:k2396. doi:10.1136/bmj.k2396
  • Barabási A, Menichetti G & Loscalzo J. The unmapped chemical complexity of our diet. Nat Food. 2020;1:33–37. doi:10.1038/s43016-019-0005-1
  • Zmora N, Suez J & Elinav E. You are what you eat: diet, health and the gut microbiota. Nat Rev Gastroenterol Hepatol. 2019;16:35-56. doi:10.1038/s41575-018-0061-2
  • Menni C, Jackson MA, Pallister T et al. Gut Microbiome Diversity and High-Fibre Intake Are Related to Lower Long-Term Weight Gain. Int J Obes. 2017 Jul;41(7):1099-105. doi:10.1038/ijo.2017.66
  • Singh RK, Chang H-W, Yan D et al. Influence of diet on the gut microbiome and implications for human health. J Transl Med. 2017;15:73. doi:10.1186%2Fs12967-017-1175-y
  • Telle-Hansen VH, Holven KB & Ulven SM. Impact of a Healthy Dietary Pattern on Gut Microbiota and Systemic Inflammation in Humans. Nutrients. 2018 Nov;10(11):1783. doi:10.3390%2Fnu10111783
  • Kolovou GD, Mikhailidis DP, Kovar J et al. Assessment and clinical relevance of non-fasting and postprandial triglycerides: an expert panel statement. Curr Vasc Pharmacol. 2011;9(3):258–270. doi:10.2174/157016111795495549
  • Astley CM, Todd JN, Salem RM et al. Genetic evidence that carbohydrate-stimulated insulin secretion leads to obesity. Clin Chem. 2018;64(1):192–200. doi:10.1373%2Fclinchem.2017.280727
  • Blaak EE, Antoine J-M, Benton D et al. Impact of postprandial glycaemia on health and prevention of disease. Obes Rev. 2012;13(10):923-84. doi:10.1111%2Fj.1467-789X.2012.01011.x
  • DECODE Study Group, European Diabetes Epidemiology Group. Glucose tolerance and cardiovascular mortality: comparison of fasting and 2-hour diagnostic criteria. Arch Intern Med. 2001;161:397-405. doi:10.1001/archinte.161.3.397
  • Hill JO, Wyatt HR & Peters JC. Energy Balance and Obesity. Circulation. 2012;126:126-32. doi:10.1161/CIRCULATIONAHA.111.087213
  • Spector T & Gardner C. Challenges and opportunities for better nutrition science—an essay by Tim Spector and Christopher Gardner. BMJ. 2020;369:m2470. doi:10.1136/bmj.m2470
  • Spector T, Asnicar F, Berry S et al. Microbiome Signatures of Nutrients, Foods and Dietary Patterns: Potential for Personalized Nutrition from The PREDICT 1 Study. Curr Dev Nutr. 2020 May;4(2):1587. doi:10.1093/cdn/nzaa062_044
  • Berry S, Ordovas J, Asnicar F et al. Influence of Gut Microbial Communities on Fasting and Postprandial Lipids and Circulating Metabolites: The PREDICT 1 Study. Curr Dev Nutr. 2020 May;4(2):1547. doi:10.1093/cdn/nzaa062_004
  • Berry S, Mazidi M, Franks P et al. Impact of Postprandial Lipemia and Glycemia on Inflammatory Factors in over 1,000 individuals in the US and UK:  Insights from the PREDICT 1 and InterCardio studies. Curr Dev Nutr. 2020 Jun;4(2):1518. doi:10.1093/cdn/nzaa068_003
  • Berry S, Wyatt P, Franks P et al. Effect of Postprandial Glucose Dips on Hunger and Energy Intake in 1102 Subjects in US and UK: The PREDICT 1 Study. Curr Dev Nutr. 2020 Jun;4(2):1161. doi:10.1093/cdn/nzaa063_009

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