Aim: Microbiota-host-xenobiotics interactions in humans become of prime interest when clinical pharmacogenomics is to be implemented. Despite the advent of technology, information still needs to be translated into knowledge for optimum patient stratification and disease management. Material & methods: Herein, we mined metagenomic, pharmacometagenomic and pharmacomicrobiomic datasets to map microbiota-host-drugs networks. Results: Datasets were multifaceted and voluminous. Interoperability, data sparsity and scarcity remain a challenge. Mapping microbiota-host-drugs networks allowed the prediction of drug response/toxicity and modulation of the microbiota-host-drugs interplay. Conclusion: Our approach triangulated microbiota, host and drug networks revealing the need for contextual data and open science via microattribution to accelerate knowledge growth. Our findings may serve as a data storehouse for a user-friendly query system, coupled with databanks and databases.
Keywords: contextual data; metagenomics; microbiota–host–xenobiotics networks; open science; pharmacogenomics; pharmacometagenomics; pharmacomicrobiomics.