Kitchen-To-Toilet: Onchain Public Data, Gut Microbiome Testing, and Personalized Nutrition

Title

Kitchen-To-Toilet: Onchain Public Data, Gut Microbiome Testing, and Personalized Nutrition

Team member names

Juan Diosdado and Pauline de Mortain

Short summary

Make it extremely easy to capture data about the precise composition of our meals and to understand their impact on our gut microbiome, so that it becomes a daily habit like washing our hands.

We lack reliable data to make better nutrition choices for our health and for our planet.

Gut-related diseases are on the rise globally, while microbiome testing remains prohibitively expensive. Profit-driven food and drug industries have monopolistic business models that lead to regulatory capture and privatization of public health data, obstructing the development of citizen-led research.

When we go to a restaurant or order food delivery, we cannot know the precise nutritional composition and environmental footprint of our meal. Manually capturing data from nutrition labels of packaged foods is time consuming. Official nutrition recommendations are not personalized, they tend to infantilize consumers, and can be easily biased through conflict of interest dynamics.

What is the existing target protocol you are hoping to improve or enhance?

  • Nutrition data entry.
  • Stool sample collection, transportation, and sequencing processes.

What is the core idea or insight about potential improvement you want to pursue?

  • Onchain attestations about the nutritional composition and environmental footprint of packaged foods and restaurant meals.
  • Quick data entry through QR codes and API integrations.
  • Shared-use toilets as pickup points to optimize the stool sample collection process.

What is your discovery methodology for investigating the current state of the target protocol?

  • Field observation: We have tried microbiome test kits from Le French Gut, Nahibu, and Perfeqt. We have tried nutrition tracking apps like MyFitnessPal.
  • Historical data analysis: We are creating a detailed timeline of events and use it to extrapolate possible future scenarios.
  • Failure event analysis: We have observed lots of friction in the steps of current microbiome test offerings. Manually capturing data from nutrition labels of packaged foods is time consuming. Finding reliable data about restaurant meals is just not possible.

In what form will you prototype your improvement idea?

  • Code
  • Reference design implementation
  • Draft proposal shared with experts for feedback
  • A/B test of ideas with a test audience
  • Hardware prototype

How will you field-test your improvement idea?

  • For nutrition data entry we want to cooperate with a handful of local restaurants or meal prep services that want to highlight the ingredients of their products.
  • For stool sample collection we want to cooperate with a group of people that are regularly present in the same location and that want to participate in a long-term pilot. (e.g., coworking space, gym, medical school, sports team)

Who will be able to judge the quality of your output?

  • Albert Wenger
  • Angela Kreitenweis
  • Anjali Nayar
  • Balaji Srinivasan
  • Brewster Kahle
  • Bryan Johnson
  • David Bollier
  • Don Norman
  • François Taddei
  • Giulia Enders
  • Henri Verdier
  • Paul Duan
  • Sam Williams
  • Simon Wardley
  • Simone Cicero
  • Thomas Landrain
  • Someone from European Citizen Science
  • Someone from Foodwatch International
  • Someone from LabDAO
  • Someone from Learning Planet Institute
  • Someone from MMHP
  • Someone from Open Food Facts
  • Someone from Sulabh International
  • Someone from TRUSTyFOOD
  • Someone from Wikispecies

How will you publish and evangelize your improvement idea?

  • Create memetic content.
  • Publish open-source code and documentation.

What is the success vision for your idea?

Use onchain public data to:

  • Become the lead actors of our personal health.
  • Generate a personalized nutrition and microbiome population journal.
  • Coordinate a marketplace for microbiome sequencing, data interpretation, nutrition recommendation, and meal prep services.
  • Empower researchers with continuous data from the same subjects over a long time frame.
  • Foster the emergence of microbiome testing and data interpretation as free public health services.

This protocol aims to change incentives. The more users know about their own health, the more they will demand better quality food and health services. Doctors, food producers, and restaurants will naturally react to what their customers demand.


Nutrit-Code@2x

PoopNet-Code@2x

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Interesting there is health aspect, as well as apparently an environment aspect in this project. How do they articulate in the form of a protocol?


I am still having issues to really understand what protocols and permissionlessness entails—which may be the whole point of the community here—if it makes sense, do you see ways to expend the project proposal more on the protocol and permissionless sides of it? For example, I do not see how involving onchain public data relates to either protocol or permissionlessness.

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The idea is to connect your individual health to our planet’s health. Understanding what happens on planetary scale is very complex. Impactful actions require coordination between countless actors, and we often have to wait a long time before the results are clear.

But on the individual scale, your body, the feedback loop is very short. When you eat something, within minutes, your insulin will rise, you bacteria will react, your energy and your mood will change. You know how it makes you feel, and nobody can convince you otherwise or force you to eat something else.

If we add reliable data, about the stuff you’re eating and about your microbiome, you’ll be able to experiment, without anyone’s permission! And soon you’ll begin to understand how your nutritional decisions have an impact on your health. The time-to-value feedback loop will be very short, which will motivate you to continue learning.

At this moment, you’ll be in an ideal disposition to further expand your horizons and consider: I now have proof that my behavior has a direct impact in my health. But what impact does it have in my family, my community, my planet? What impact do I want it to have?

We started with nutritional data and microbiome data. But now we can expand the scope to have data about the whole lifecycle of food and our small role in the journey from farm to kitchen to toilet to compost, and so on. The interdependence of everything in nature becomes a little bit more tangible.

Well, I’m no expert in protocols or permissionlessness, but here’s my explanation. Let’s imagine we choose to build on top of a blockchain like Ethereum. Then, we define some rules for interaction between participants that lead towards our desired goal. That is our protocol. And if we build it so that anyone who follows the rules can interact with the other participants, independently of what we builders may think, then we can say that it’s a permissionless protocol. Although permissionlessness, as decentralization, can be better understood as a spectrum.

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I would like to add that onchain public data solves the problem of gatekeeper of truth. For example, the Food and Drug Administration, doctors, research journals, and gut microbiome analysis companies all have in common the centralization and privatization of knowledge. In this protocol, onchain public data, verifiable and anonymized, becomes a common resource allowing everyone to tap into and be an expert of their own health.

I personally asked the “permission” to Nahibu, a company with which I tested my gut microbiome to have access to my raw data, but they refused because it’s not part of their business model.

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When we say that data is onchain, we’re claiming that it’s immutable and verifiable. When we say that data is public, we’re saying that everybody has the right to access it and use it however they want, i.e. permissionlessly.

Wowow, so many good questions! :slight_smile:

It seems that you have a lot of experience in this domain. We would love to learn more details about these bad experiences so we can avoid those pitfalls.

From the services we’ve researched or experienced so far, they tend to fall in two categories:

  • Profit-first startup that sells you a ~200 USD home kit, in exchange of which you receive some vague nutritional recommendations which usually include the offer to buy their supplements. They do not share with you the raw data from your sample.
  • Research project that provides a free home kit, in exchange of which you receive nothing besides the promise that they’ll someday publish the results in a scientific journal. Their objective is to create an average of the population in a specific geographic area, so they only get one sample per individual. They do not share with you the raw data from your sample.

We want to decouple sample sequencing from data interpretation. Onchain the anonymized sample data, in order to preserve it and make it accessible to different data interpretation providers, which may be old school government-funded labs, profit-first startups, autonomous AI agents, or even you, the individual who provided the sample, if you have the technical knowledge to analyze the data.

What I meant was the data of your sample is published onchain, permanent, public domain, CC0. But it’s anonymous, nobody knows your name, you’re the only one who knows the origin of samples #093f20, #a32b72, and #139d4b.

On the other hand, we think the service providers for sample sequencing and data interpretation, should be KYCd and verified. Therefore, the sequencing and interpretation data based on anonymous sample #093f20 come from identifiable entities.

Hope this makes it a bit clearer.

Not sure I understand your two last questions, but we would love to talk more about it.

So many interesting resources on Quantified Self website!

though its use will obviously be limited to people who understand and are willing to accept the risks.

What did you mean exactly by “accepting the risks” in your first question?

(post deleted by author)

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