Research Spotlight: Fatma Kir, PhD, Postdoctoral Pharmacometrician

A Familiar Drug with an Unfinished Story

When a drug has been in use for more than half a century, it is easy to assume we already understand everything there is to know about it. Metronidazole, a widely used antimicrobial prescribed to treat infections caused by anaerobic bacteria and protozoa in both animals and humans, is one such compound. Despite being studied extensively across species, much of what we know about its pharmacokinetics (PK) exists in isolation rather than as a unified picture.

In a recent publication in The AAPS Journal, Fatma Kir, PhD, Postdoctoral Pharmacometrician at A2-Ai, takes on the challenge of bringing this scattered literature together. Her study, “Metronidazole Pharmacokinetics Across Species: Meta-Analysis Integrating Allometric Scaling and Minimal Physiologically-Based Pharmacokinetic Modeling,” applies a rigorous, physiology-driven modeling framework to evaluate metronidazole disposition across more than 20 species including mice, birds, cattle, horses, and humans.

A Unifying Modeling Framework

Rather than relying on traditional compartmental approaches, Dr. Kir used a minimal physiologically-based pharmacokinetic (mPBPK) model integrated with allometric scaling to preserve biological meaning while enabling cross-species comparison. This approach, referred to as mPBPK Allometric Meta-Analysis (MAMA), allows parameters like blood volume and cardiac output to scale with body weight, while drug-specific parameters like clearance, tissue distribution, and bioavailability are estimated directly from existing data.

Consistency Across Species

The analysis revealed a striking degree of consistency in metronidazole disposition across species. Clearance and volume of distribution scaled predictably with body weight, and a relatively simple mPBPK structure was sufficient to capture both intravenous and oral PK profiles across mammals and birds. However, differences did emerge, such as reduced oral bioavailability in ruminants like cows, sheep, goats. The modeling framework helped place these findings in a physiological context, pointing to species-specific gastrointestinal and metabolic factors rather than unexplained variability.

Why This Matters

Together, these results highlight the power of mechanistically grounded pharmacometric modeling to synthesize decades of data into a coherent framework. By bridging species, study designs, and experimental conditions, Dr. Kir’s work strengthens translational understanding and supports more informed dosing decisions across both human and veterinary medicine.

Dr. Kir’s work reflects the modeling rigor that underpins A2-Ai’s pharmacometric practice. Through data evaluation and mechanistic modeling approaches, A2-Ai helps translate complex and heterogeneous data into coherent insight, enabling more informed dose selection, cross-species translation, and decision-making throughout drug development.

Read the Full Article Here: https://link.springer.com/article/10.1208/s12248-025-01191-x