AI-Driven Pharmacomicrobiomics: Microbial Drug Metabolism, Multi-Omics & Precision Therapeutics

The gut microbiome is emerging as an important determinant of drug metabolism, therapeutic efficacy, toxicity, and inter-individual variability in treatment response. This 3-day hands-on workshop introduces participants to the rapidly evolving field of pharmacomicrobiomics, combining microbiome analysis, pharmacometabolomics, biomarker discovery, and computational drug-response prediction. Participants will explore how microbial communities and their metabolites influence drug biotransformation and PK/PD, and learn how microbiome, metabolomics, and clinical features can be integrated to identify therapeutic-response biomarkers and develop interpretable predictive models. Each day includes a practical Google Colab-based hands-on session, enabling participants to translate research concepts into reproducible computational workflows.

To provide participants with a practical understanding of gut microbiome–drug interactions and equip them with computational skills to investigate microbial drug metabolism, pharmacometabolomics, therapeutic-response biomarkers, and microbiome-informed precision pharmacotherapy.

• Understand the principles ofpharmacomicrobiomics and microbiome–drug interactions
• Explore microbial mechanisms influencingdrug metabolism, efficacy and toxicity
• Understand microbiome-mediated changes inpharmacokinetics and pharmacodynamics
• Analyze microbiome and metabolomics datasets associated with therapeutic response
• Identifymicrobial and metabolic biomarkerslinked to drug efficacy and adverse response
• Integrate microbiome, metabolite and clinical features for patient stratification
• Build machine-learning models fordrug-response prediction
• Apply explainable AI approaches such asSHAPto interpret predictive biomarkers
• Understand the principles and emerging applications ofprecision pharmacotherapy and model-informed precision dosing

📅 Day 1: Pharmacomicrobiomics & Microbial Drug Metabolism

• Gut microbiome as a determinant of drug efficacy, toxicity and inter-individual variability Bidirectional drug–microbiome interactions Microbial drug biotransformation: activation, inactivation and toxic metabolite formation Microbial enzymes and pathways affecting drug absorption, metabolism and bioavailability Microbiome effects on pharmacokinetics (PK) and pharmacodynamics (PD) Research case studies: metformin, irinotecan, levodopa, tacrolimus and cancer immunotherapy Identifying microbiome signatures associated with responders vs non-responders

📅 Day 2: Pharmacometabolomics & Multi-Omics Biomarker Discovery

• Introduction to pharmacometabolomics for precision medicine Linking microbial taxa → metabolic pathways → metabolites → drug response Key microbiome-derived metabolites: Short-chain fatty acids Secondary bile acids Indole derivatives Aromatic microbial metabolites Metabolomics data preprocessing: missing values, normalization and transformation PCA and differential metabolite analysis Microbiome–metabolome correlation analysis Identifying metabolic biomarkers of drug efficacy and toxicity Integrating microbiome + metabolomics for patient stratification

📅 Day 3: AI-Driven Drug Response Prediction & Precision Dosing

• From microbiome biomarkers to precision pharmacotherapy Integrating: Microbiome + Metabolites + Clinical Variables Feature selection for drug-response modeling Machine learning for predicting: Responders vs non-responders Drug efficacy Adverse-response/toxicity risk Random Forest / XGBoost-based prediction Model validation: ROC-AUC, sensitivity, specificity and cross-validation SHAP explainability for identifying microbiome/metabolite drivers Introduction to Model-Informed Precision Dosing (MIPD) Connecting microbiome signatures with PK/exposure and dosing scenarios Current limitations and clinical translation of microbiome-guided dosing

• Pharmacomicrobiomics and microbial drug biotransformation
• Microbiome–drug interaction analysis
• Pharmacometabolomics data analysis
• Microbiome–metabolome integration
• Drug-response biomarker discovery
• Patient stratification
• Machine-learning-based therapeutic-response prediction
• Model validation and performance interpretation
• Explainable AI for identifying microbial and metabolic drivers
• Translating multi-omics biomarkers toward precision medicine and individualized therapy

This workshop is suitable for: PhD Scholars & Research Scholars Academicians & Faculty Members Microbiome Researchers Bioinformatics & Computational Biology Researchers Pharmacology & Pharmaceutical Science Researchers Clinical Pharmacology Researchers Metabolomics & Multi-Omics Researchers Drug Discovery & Development Scientists Precision Medicine Researchers Biotechnology & Life Science Professionals Clinical Research Professionals Pharmaceutical and Biotechnology Industry Professionals