AI for nutritionists: personalised plans with nutrigenomics
Manually cross-referencing medical history, genetic profile and nutraceutical guidance takes time for every single patient. A support tool can do it in minutes, always leaving the final word to the professional.
September 19, 2026 · 7 min read · by the aimybusiness team
What nutrigenomics is, briefly
Nutrigenomics studies how individual genetic variation affects a person's response to specific nutrients: two people on the same diet can metabolise fats, sugars or certain micronutrients differently. Cross-referencing this information with clinical history and nutraceutical guidance (the targeted use of supplements alongside diet) can, in principle, produce more precise meal plans than a standardised approach.
In practice, doing this by hand for every patient, reading a genetic report, cross-checking it against clinical history, verifying interactions with any supplements already in use, takes time that most nutrition practices simply do not have.
What this kind of software does
A support platform gathers medical history, any available nutrigenomic profile, and any nutraceutical guidance already in use, and returns a proposed personalised meal plan, together with the reasoning behind each choice. The professional reviews it, corrects it if needed, and approves the plan before it reaches the patient.
What it does not do (and should not do)
It does not replace the consultation, does not make diagnoses, and does not decide on treatment on its own: it remains a decision-support tool. The final decision, at every stage, stays with the licensed professional, who retains full clinical responsibility for the plan.
Why it isn't "a diet app"
Consumer diet apps talk directly to the individual, with no professional in the loop. A system built for a nutrition practice instead always operates within an existing clinical relationship: the patient remains under the care of their practitioner, and the software is a tool the professional uses, not a substitute for them.
How health data is handled
Health data is a special category of personal data under the GDPR and requires specific safeguards: an appropriate legal basis, data minimisation, limited retention, and on-premise or private/European cloud infrastructure that is GDPR-compliant. In projects involving health data, clinical decisions remain, as a matter of principle, with the professional.
A real case
For a nutrition practice we built a platform that cross-references medical history, nutrigenomic profile and nutraceutical guidance to propose personalised meal plans, always leaving the final decision to the professional. The full case study also covers how it started, with a free pre-analysis.
Who it makes sense for
The most natural fit is nutrition practices, individual practitioners and specialised centres that want to offer deeper personalisation without a proportional increase in time spent per patient. It is also relevant for nutraceutical and supplement companies that want to offer their end customers a more solid guidance service.
Frequently asked questions
Q.1Does it replace the consultation with a nutritionist?
No. It is a support tool the professional uses during and after the consultation: the clinical assessment and the final decision always remain theirs.
Q.2Is a genetic test required to use it?
No: the system works with clinical history alone. A nutrigenomic profile, when available, enriches personalisation but is not a requirement to get started.
Q.3Is patient data safe?
We work on-premise or with GDPR-compliant European cloud providers, handling health data with the safeguards required for this category of information.
Sources
- Regulation (EU) 2024/1689 (AI Act), EUR-Lex
- Italian Law No. 132 of 23 September 2025, Official Gazette No. 223 of 25 September 2025
This article is for general information only and does not replace a professional nutritional or medical assessment.
Written with the support of artificial intelligence and reviewed by the aimybusiness team, which holds editorial responsibility.
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