Federal Grant Award Summary

The National Institute of Child Health and Human Development (NICHD) awarded $562,250 to the University of Melbourne under the Child Health and Human Development Extramural Research program (CFDA 93.865) to develop machine learning (ML) and perturbation study methodologies that de-risk therapeutic medication use during lactation. The project, awarded June 19, 2026, with completion targeted for March 31, 2031, addresses a critical gap in maternal and infant health by creating data-driven tools for assessing medication safety and impacts on milk composition. Current clinical trial limitations and ethical constraints have left lactating mothers and healthcare providers with inadequate safety information, often forcing difficult choices between necessary medication treatment and breastfeeding continuation.

The research leverages advances in ML prediction methods and large perturbation datasets—where cells are treated with pharmaceutical compounds and their transcriptomes profiled—to develop predictive tools applicable during drug discovery and safety assessment processes. By coupling cellular perturbation studies with ML algorithms, the project will generate training datasets and predictive models that anticipate how maternal medications affect lactation biology, milk nutrient composition, and infant health outcomes. This toolset addresses a significant public health need, as millions of lactating women in the United States managing chronic medical conditions currently lack evidence-based guidance on medication safety during breastfeeding.