Hanna Sebesi, Erika Bán, László-István Bába, Adrian Man
Integrating pharmacomicrobiomics as the third pillar of drug interactions uncovers an invisible layer of clinical risk. Traditional tools significantly underestimate the burden of interactions by omitting simultaneous interferences and the role of the gut microbiome as a pre-systemic filter. While the scoring system presented here represents a novel proposal that requires future clinical validation, it provides a necessary framework for precise prescribing and enhancing patient safety in vulnerable multimorbid patients.
BACKGROUND: Conventional drug-drug interaction checkers predominantly rely on a two-dimensional approach, including pharmacokinetic and pharmacodynamic mechanisms. Emerging recognition of the gut microbiome is often an overlooked parameter in drug interferences. This study introduces a novel three-pillar risk stratification scoring model, incorporating pharmacomicrobiomics, to help refine the interaction landscape between antibiotics and immunomodulators for safer and more precise patient care.
METHODS: Sixty-four antibiotic-immunomodulator drug pairs were analyzed across eight major drug classes. A standardized Risk Score was developed, assigning weighted values to Pharmacokinetic, PD and PM mechanisms based on pharmacological plausibility and clinical severity. This model's findings were compared against established clinical classifications (Lexicomp®) to identify blind spots in traditional risk assessment.
RESULTS: The three-pillar model revealed 106 mechanistic interactions, representing a 65.5% increase in identified pathways compared to traditional two-dimensional models. The average mechanism per drug pair increased to 1.65. While standard databases categorized most pairings as moderate risk (Category C), our scoring system classified 51.5% (n = 33) as High-Risk (TRS ≥4). The PM pillar was pivotal in explaining metabolic interferences, such as antibiotic-induced dysbiosis, leading to either toxic surges in Tacrolimus levels or therapeutic failure of Mycophenolate mofetil due to disrupted enterohepatic recycling.
CONCLUSION: Integrating pharmacomicrobiomics as the third pillar of drug interactions uncovers an invisible layer of clinical risk. Traditional tools significantly underestimate the burden of interactions by omitting simultaneous interferences and the role of the gut microbiome as a pre-systemic filter. While the scoring system presented here represents a novel proposal that requires future clinical validation, it provides a necessary framework for precise prescribing and enhancing patient safety in vulnerable multimorbid patients.