Researchers warn AI and data rules alone won’t fix microbiome reproducibility problems

Researchers at the HHS Microbiome Subcommittee identified methodological inconsistency and data fragmentation as major obstacles to translating microbiome research into reliable interventions. Dr. Rob Knight said the field has moved toward causal and translational work but cautioned that "methodological inconsistency where, you will get different results if you if you apply different methods to the same biological specimens"—a gap that undermines cross‑study comparison and AI model training.