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Related Experiment Video

Updated: Mar 27, 2026

Individualized Reconstitution of Human Milk Microbiota: A Feasible Approach in Real-World Settings

Individualized Reconstitution of Human Milk Microbiota: A Feasible Approach in Real-World Settings

Published on: February 7, 2025

Improving the composition of donor milk using machine learning and optimisation techniques.

Jacqueline Muts^1,2, Danée Knevel³, Dick den Hertog³

¹Department of Pediatrics, Emma Children's Hospital. Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

|March 24, 2026

Summary

This summary is machine-generated.

Pooling donor human milk from multiple mothers using machine learning significantly improves macronutrient consistency. This data-driven approach enhances the quality of donor human milk (DHM) for preterm infants.

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Area of Science:

Nutritional Science
Biostatistics
Neonatal Nutrition

Background:

Donor human milk (DHM) macronutrient content varies due to maternal factors.
Consistent DHM is crucial for preterm infant nutrition.
Current pooling methods in human milk banks lack standardization.

Purpose of the Study:

To stabilize DHM macronutrient quality by pooling milk from multiple donors.
To utilize machine learning for predicting and optimizing DHM composition.
To reduce deviations from target protein and energy levels in DHM.

Main Methods:

Compared current single-donor pooling with a new multi-donor pooling strategy (up to 5 donors).
Employed random forest regression models to predict crude protein and energy content.
Used an optimization model to minimize deviations from target macronutrient levels (1.0 g protein/100 mL, 70 kcal/100 mL).

Main Results:

Prediction models were developed using 2236 single-donor pools from 480 donors.
Random forest models achieved the highest accuracy in macronutrient prediction.
The multi-donor pooling strategy reduced average absolute deviation from target values (0.402) compared to single-donor pooling (0.664).

Conclusions:

Data-driven methods, including machine learning, can enhance human milk bank operational efficiency.
The proposed pooling strategy significantly improves the consistency of DHM.
This approach offers a pathway to more reliable nutritional support for vulnerable infants.