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From blood values to a formula: turning a lab result into a follow-up product
A blood value shows how well someone is supplied with a nutrient today – genes only show the predisposition. That is why, at Novogenia, a measured value takes precedence for the nutrient it measures: a low value sets the nutrient to the maximum of the dosing window, an excess removes it from the formula. The window runs from one third to three times the reference intake and ends at EFSA’s upper level at the latest. Abnormal values belong in a physician’s hands, and new measurements flow into the next production run.
One value, five doctors, five doses
A slightly low vitamin D level, five different doctors – and probably five different doses. All five are legitimate. That is how we put it ourselves on our page on gene-based, personalized dosing. The sentence captures what every lab that wants to turn blood values into a follow-up product needs to know: a measured value is not yet a formula. In between sits a rule set.
That rule set decides whether your lab result becomes a transparently calculated product – or a number your customer takes alone to the store shelf. Here you will learn which blood values count for a formula, why the measured value takes precedence, where the medical line runs and why re-testing pays off. The individual calculation steps are covered in Manufacturing personalized supplements in our contract manufacturing guide. This article is about your side: the data.
The climate chart and the view out the window
Three data sources can feed a personalized formula, plus basic data such as age, sex and body weight. Each one answers a different question:
| Data source | What it describes | How often it changes |
|---|---|---|
| Genes | the predisposition: how the body processes certain nutrients | never |
| Questionnaire | diet and lifestyle, such as fruit and vegetables, dairy, a vegan or vegetarian diet, smoking, alcohol, sun exposure and training | with habits |
| Blood values | the current supply of a nutrient | from one measurement to the next |
Think of genes as a climate chart: it tells you whether a place tends to get a lot of rain. The blood value is the view out the window: it shows whether it is raining today. If you are deciding whether to take an umbrella today, you trust the view out the window. The blood value is the only data source that shows the current state – and that is exactly what makes your lab results so valuable for a follow-up product.
Which blood values count for a formula
For a micronutrient formula, what counts are values on micronutrient status: vitamins, minerals and other lab markers that can be mapped to a nutrient. You do not need a full panel. A formula can be calculated from a broad panel just as well as from a focused set of values.
The basic rule is simple: a blood value steers the nutrient it measures. For every nutrient without a measured value, the algorithm works with the other data – the base recommendation by age and sex, body weight, the questionnaire and, if available, genes.
| What you provide | What it means for the formula |
|---|---|
| Broad panel on micronutrient status | Many nutrients follow the current measured value directly. |
| Focused set of individual values | The measured nutrients follow the measured value; the others follow the remaining data. |
| Blood values plus genetic data | The measured value leads for the measured nutrient; genes act wherever no value exists. |
For a clean handover, clarify three things in the project: which values arrive in which units, which reference ranges apply, and how old a value may be at most. How the data reach us technically is covered in Data integration: raw data, interfaces, formats.
The measured value takes precedence – nutrient by nutrient
At Novogenia, every dose is built in several steps: a base recommendation by age and sex, adjustment for body weight and training, genetic weighting, and diet and lifestyle. Then comes the blood value. For its nutrient, it takes precedence over all other inputs:
- Measured low: The nutrient moves to the maximum of the dosing window – regardless of what genes or questionnaire would have suggested.
- Measured excess: The nutrient is removed from the formula entirely.
- No measured value: The other data determine the dose.
Here is the principle in a schematic example: if genes and questionnaire point to a medium requirement for a nutrient but the measured value is low, the nutrient moves to the maximum. If genes point to a high requirement but the measured value shows an excess, the nutrient is removed. That does not make the genes worthless – they steer every nutrient you do not measure, and they help explain why a value may keep coming back low.
The excess case matters just as much as the low value. Personalization does not mean “more of everything.” Where the blood value or genotype points to a lower requirement, a lower dose is the professionally correct result – not an under-dose. For your lab, that is a strong argument: your measurement not only makes the product more targeted, it also keeps people from taking a nutrient they already have enough of.
One more point helps in customer conversations: if two people both have a requirement above the maximum, both receive the same dose – for completely different reasons. That is intended, not an error.
When a measured value belongs in a physician’s hands
Your lab result can open two paths – and it is important to keep them clearly apart. The follow-up product is a food supplement, which means it is a food. It optimizes intake within the healthy range. A genuine deficiency or a disease belongs in medical hands; abnormal blood values need a medical work-up. The food supplement does not replace that.
- Set the threshold: Before launch, define with your medical lead from which values a result goes to a physician first.
- Draw the medical line: With medical conditions, medications, pregnancy and breastfeeding, the question of supplementation belongs in a physician’s hands.
- Get the language right: Whoever orders the follow-up product is a customer, not a patient – the product does not treat anything.
- Cover consent: Using blood values for a product is a separate purpose. How to secure it under data protection law is covered in Data protection and roles between lab and manufacturer.
That way, your lab result remains what it is – a medical document – and the follow-up product is a clearly separate offer alongside it.
Guardrails: the dosing window
Even the strongest measured value cannot push a dose without limit. At Novogenia, every dose lies between about one third and about three times the reference intake, with documented exceptions. For every nutrient with an EFSA tolerable upper intake level, the maximum is at or below that value, and national statutory maximum amounts are complied with as well. A calculated requirement outside the window is set to the minimum or maximum. Where these limits come from and what applies in Germany, Austria and Switzerland is covered in Dosing and safety: limits and rules.
Re-testing: the formula moves with the person
A blood value is a snapshot – and some snapshots are seasonal. How strongly is shown by an analysis of 3.8 million lab results from the United States: vitamin D levels followed a wave over the year, peaking in September and bottoming out in March. The share of people tested who were deficient in vitamin D varied over the year between 21% and 48% (Kroll et al., PLoS One, 2015). Exciting for you as a data owner: this insight comes from exactly the kind of routine data a lab generates anyway.
On top of that, the same intake does not work the same way for everyone. In an analysis of 22,214 measurements from 17,614 healthy adults in a preventive health program, vitamin D levels rose ever more slowly as the dose increased, and people with overweight or obesity had lower levels on average. The authors therefore recommend a two to three times higher intake for people with obesity and a 1.5 times higher intake for people with overweight, compared with normal weight (Ekwaru et al., PLoS One, 2014).
Two practical conclusions follow. First: send the sample date with every value, because a value from March tells a different story than one from September. Second: re-testing shows how a body actually responds – which is why the algorithm takes body data such as weight into account alongside the measured value.
At Novogenia, the formula is recalculated for every production run: at least with the current age, and with new questionnaire answers or new blood values as soon as they are available. One delivery lasts 90 days. Every new measurement thus flows into the next delivery. What that means for your business model is covered in Recurring revenue from follow-up products.
Checklist: what to prepare as a lab
- You know which micronutrient status values you measure and in which units you deliver them.
- Reference ranges and the thresholds for “low” and “excess” are agreed in the project.
- Every value comes with its sample date; the maximum age of a value is agreed.
- The medical pathway for abnormal results is defined before the first product ships.
- Your customers’ consent covers using their blood values for the follow-up product.
- You have decided whether genetic data are added or only the questionnaire and body data.
- A re-testing rhythm is aligned with your offer.
- Your communication promises no cure – authorized claims only; more in Health claims: what you may advertise.
Do you hold genetic data as well as blood values? How a genotype turns into a dose is explained in From genetic data to a formula.
Frequently asked questions
Which blood values do I need for a personalized formula?
Do blood values take precedence over genes?
What happens with an abnormal blood value?
How often should blood values be re-tested?
Can a formula be built from blood values alone?
Related: From genetic data to a formula · Dosing and safety: limits and rules · From lab results to formula
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Request a project →Offer for labsNote: 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.