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Data integration: raw data, interfaces, formats – what the lab and the manufacturer need to clarify up front

Reviewed by Dr. Daniel Wallerstorfer, molecular biologist and founder of Novogenia · Updated: 13 October 2026 · Reading time: 10 min

In short

For lab and genetic data to become a follow-up product, they have to reach the manufacturer cleanly. Before you start, clarify five things: which data are needed (genes, blood values, questionnaire, body data), how good they are, how your data fields match up (mapping), how the data travel securely, and what comes back. At Novogenia, around 50 genes feed into the formula, and blood values take precedence for the nutrient concerned. We agree on the transfer route and data format with you at the start of the project.

The baton: why the handover decides everything

A lab value speaks in units and reference ranges. A genotype speaks in letters. A formula speaks in micrograms. For your data to become a follow-up product, these three languages have to come together – for every single customer.

Think of the data handover as a relay race. Your lab or platform runs the first leg: sample, analysis, result. The manufacturer runs the second: interpretation, formula, production, shipping. Races are often decided not on the straightaway but in the exchange zone. Drop the baton there, and even the fastest runner cannot save you.

This article shows what to clarify before the first handover: which data are needed, how good they need to be, how your data fields match up, how the data travel securely, and what comes back. You and your partner agree on technical details such as file format or transfer route during the project – but the questions behind them are always the same.

Which data can feed into a formula

A personalized formula can be based on several data sources, alone or combined. At Novogenia, there are four:

Data source	What it describes	What to clarify
Genetics: raw genotype, SNP panel, DNA test results	predisposition; at Novogenia, around 50 genes with three possible genotypes each	Does your panel cover the genes needed? How was the genotyping done?
Blood values: for example vitamins, minerals and other lab markers	current nutrient status; they take precedence for the nutrient concerned	Unit, reference range, date of the blood draw
Questionnaire	diet and lifestyle, such as fruit and vegetables, dairy products, a vegan or vegetarian diet, smoking, alcohol, sun exposure and training	Who collects it, and how is it updated?
Body data	sex, age, body weight	Age is recalculated for every production run – which requires the date of birth.

A full panel is not required: a formula can be built from many blood values or from a few targeted lab results. How blood values and genes shift the dose is explained in From blood values to a formula and From genetic data to a formula. This article covers the question that comes first: how do the data reach the manufacturer cleanly?

Raw genetic data: coverage, quality, assignment

Many DNA testing companies and genetic labs hold genotypes that were measured long ago. Novogenia can interpret such raw genotype or SNP data. For that to work, four questions should be answered:

Coverage: Around 50 genes feed into the formula. Whether your panel or chip covers them is checked at the start of the project.
Quality: Which method was used for genotyping, and under which quality rules? Document how missing or uncertain values are flagged – an empty field must never be read as a result.
Assignment: Every data record must belong unambiguously to one person. A pseudonym instead of the name links the two without the name traveling along with the genetic data.
Scope: If your data contain far more than the markers needed, for example medically relevant variants, agree up front on what is transferred at all. The General Data Protection Regulation (GDPR) requires data to be limited to what is necessary for the purpose (Art. 5(1)(c)). Medical analyses belong in a physician’s hands wherever national law requires it.

No genetic data yet? Then the chain starts one step earlier. Novogenia supplies saliva kits, in your design on request, and runs the genetic analysis in its own lab; it takes 4 days. Intermediate routes are possible too: some partners already supply extracted DNA and only need the genotyping, while others hand over saliva samples. More on the contract genetic analysis page.

Blood values: unit, reference range, date

Blood values are the snapshot in the chain. They show current nutrient status and therefore take precedence over genetics for the nutrient concerned. That is exactly why every detail of the handover counts:

Which values: Micronutrient and biomarker status, such as vitamins and minerals, can be translated into concrete nutrient recommendations. Agree together on which of your parameters are transferred.
Unit: The same value may be reported in different units depending on the lab. So every value travels with its unit – never as a bare number.
Reference range and method: What counts as “low” or “high” also depends on the lab. Send the reference range along, or agree on which one applies.
Date: A blood value describes one point in time. The date of the blood draw belongs with every value, and you define how old a value may be at most.
Abnormal values: Abnormal blood values need a medical work-up – a food supplement is not a treatment. Agree on who informs the customer in that case.

One advantage of blood values: they can be repeated. At Novogenia, the formula is recalculated for every new production run. When new blood values come in, the current status feeds into the next production run.

Mapping: turning your fields into formula data

Every lab and every platform has its own field names, codes and habits. Mapping means agreeing once on which of your fields corresponds to which field at the manufacturer – and putting it in writing. Typical points:

Area	What you define
Person ID	a pseudonym that stays the same in both systems – including for reorders and a new test
Genetic markers	marker names, such as rs numbers, how genotypes are written, how missing values are flagged
Blood values	parameter, unit, reference range, date of the blood draw
Body data and questionnaire	date of birth, sex, body weight, answers in the agreed format
Production and shipping	text for the two lines on the stick pack (up to 25 characters each), delivery address, product and pack size
Versions	which version of the mapping applies and how changes are announced

A pseudonym protects, but it does not make data anonymous. Pseudonymized data that could be attributed to a person by using additional information remain personal data (Recital 26 GDPR). So every data protection rule still applies to them.

Test the mapping with test records before real customer data flow. An error in a unit or an assignment shows up immediately in a test delivery – in a running production, it shows up much later.

Transfer: secure, traceable, lean

How the data travel depends on volume and workflow and is agreed during the project. The law sets the frame: controllers and processors implement appropriate technical and organizational measures, and the GDPR expressly names pseudonymization and encryption as examples (Art. 32(1)(a)). In practice, this means:

Transfer data encrypted, never as an unprotected email attachment.
Keep genetic and health data separate from names and addresses, linked only by the pseudonym.
Have every delivery acknowledged: what arrived, and what was incomplete?
Give access only to the people who really need it.
Agree on who informs whom in the event of a data breach: a processor notifies the controller without undue delay, and the controller notifies the supervisory authority, where feasible, within 72 hours (Art. 33(1) and (2)).

Whether an exchange by file, through a portal or via an interface makes sense is something you decide based on volume. For health projects with high case volumes, Novogenia sets up sample kits, shipping routes and interfaces and standardizes the workflows. For a pilot, what matters most is that the route is secure and every delivery stays traceable.

Technology is one half of the handover; law is the other. Genetic data and health data belong to the special categories of personal data (Art. 9(1) GDPR). And data may not be further processed in a manner that is incompatible with the original purpose (Art. 5(1)(b)). If the data were collected for a lab analysis, check whether your customers’ consent also covers the follow-up product and the transfer to the manufacturer.

Who has which role in the team of lab and manufacturer, who informs the customers and what is different in Switzerland is explained in Data protection and roles between lab and manufacturer.

What comes back: product, feedback, reports

At the end of the chain is the product: one formula per person, filled into daily servings and shipped directly to your customers under your brand. Which data flow back to you in addition is agreed during the project. These points belong on the list:

Confirmations: receipt of data, production, shipping.
Queries: missing or implausible values that need to be clarified before production.
Reports: If the genetic analysis runs through Novogenia, the report is delivered digitally via a secure portal, printed on request and available in up to 18 languages. You decide whether you see your customers’ reports.
Formula data: Whether and in what form the calculated formula comes back to you is part of the project agreement.

Plan the reverse direction from the start, too. New blood values, an updated questionnaire or a new delivery address have to reach the manufacturer before the next production run starts. A subscription is not a one-time data exchange but a cycle – more in Recurring revenue from follow-up products.

Checklist: data integration before the pilot

The data sources are defined: genetics, blood values, questionnaire, body data – or a combination.
Your panel’s coverage has been checked; the route for missing genes is clear, such as a new saliva sample.
Quality rules and the flagging of missing or uncertain values are documented.
Every blood value travels with its unit, reference range and date of the blood draw.
The mapping is in writing and has been tested with test records.
A pseudonym links the records; health data and address data are kept separate.
The transfer route is secure, deliveries are acknowledged, and the data breach process is defined.
Consent, purpose and roles are settled before real data flow.
It is agreed what comes back and how new values are supplied before each production run.

How we do it at Novogenia

How we work with our partners’ data at Novogenia:

Existing data: We interpret raw genotype and SNP data, DNA test results and blood values that you already hold.
Fresh analysis: If genetic data are missing, we supply saliva kits, in your design on request, and analyze them in our own lab in Eugendorf near Salzburg, Austria. The analysis takes 4 days.
Data basis of the formula: around 50 genes, sex, age, body weight, a diet and lifestyle questionnaire and, where available, blood values.
Interpretation as a service: Interpretation is a service, not software that we hand over for you to run on your own.
Always up to date: The formula is recalculated for every production run – with the current age and new questionnaire, blood or genetic results.
Agreed per project: We agree on the transfer route, data format and feedback with you at the start of the project.

Frequently asked questions

Which data formats does Novogenia work with?

We define this per project. Usable inputs are raw genotype or SNP data, DNA test results and blood values. At the start of the project, we check whether your panel covers the genes needed and agree with you on the form and route of the data transfer.

What happens if my panel does not cover all the genes?

Around 50 genes feed into the formula. Whether your panel covers them is checked during the project. If important genes are missing, a new saliva sample with a genetic analysis in our own lab is one possible route; the analysis takes 4 days.

Do I need a technical interface to get started?

Which transfer route fits depends on data volume and workflow and is agreed during the project. What matters is that it is secure – the GDPR names pseudonymization and encryption as appropriate measures (Art. 32) – and that every delivery can be clearly assigned to one person.

How recent do blood values need to be?

Blood values describe nutrient status at a specific point in time. That is why the date of the blood draw belongs with every value, and you define during the project how old a value may be at most. When new values come in, they feed into the next production run, because the formula is recalculated every time.

Will Novogenia give me software to do the interpretation?

No. At Novogenia, interpreting genetic and blood data is a service, not a standalone software product. You supply the data or have the analysis done by us; we calculate the formula and manufacture the follow-up product.

Follow-up products for your data?

Tell us which data you hold and who your customers are – we will show you which follow-up product fits.

Request a project →Offer for labs

Note: This guide is general information for businesses and professionals and does not replace medical or legal advice. The genetic traits determined in a genetic analysis are well documented (each gene included is backed by at least three independent studies); recommendations derived from them are logical conclusions, not scientifically proven. Regulations can change; errors and changes excepted.