Presented at the PGRN 2025 Scientific Meeting, held in collaboration with ClinPGx, September 10–12, 2025 at the University of Montana in Missoula, where together leaders in pharmacogenomics and clinical pharmacology came together to advance the science and practice of precision medicine.

Pharmacogenetics (PGx) provides critical insights into how genetic variability influences drug metabolism, disposition, and response. This presentation highlights how when incorporated into population PK models, PGx information can:

• Identify subgroups with distinct pharmacokinetic profiles
• Improve predictions of individual dose–response relationships
• Support precision dosing strategies that optimize efficacy while minimizing toxicity

Integrating PGx into quantitative modeling is a powerful step toward making personalized medicine a clinical reality.

This study presents a validated whole-body PBPK model characterizing drug-drug interactions (DDIs) involving posaconazole, a broad-spectrum antifungal, in individuals with normal weight and obesity. Findings highlight a prolonged half-life and irreversible CYP3A4 inhibition in patients with BMI ≥35 kg/m², underscoring the increased risk of DDIs even after discontinuation. The model supports optimized dosing and risk assessment for co-administered CYP3A4-sensitive drugs.

This work illustrates how integrated population PK modeling of antibody-conjugated payload and free payload analytes for an ADC can inform development strategies for targeted therapies—particularly in complex oncology settings.

A companion poster to the ASCPT print copy, this visual presentation emphasizes the simulation approach used to evaluate individualized dosing strategies and their economic implications. Results underscore the importance of reducing discontinuation rates to enhance value.

This study uses pharmacometric and pharmacoeconomic modeling to explore the cost effectiveness of individualized dosing for a hypothetical new atopic dermatitis drug compared to dupilumab. Simulation scenarios tested the impact of treatment discontinuation rates, efficacy variability, and pricing on cost utility outcomes.