Senior Scientist II
Ahmed earned his PhD in Biomedical Sciences from the University of Connecticut. His thesis work revolved around building statistical models to solve problems with super-resolution imaging. Other fields of experience include systems biology and pharmacokinetics. More recently, he focused on developing physiologically-based pharmacokinetic (PBPK) models to get a better mechanistic understanding of drugs’ pharmacokinetics.
July 22, 2025
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.
June 13, 2025
Presented at ASCPT 2025 Annual Meeting. Neural networks can be integrated with traditional pharmacometric models using several free open-source programming languages. Both Julia and R environments are suitable platforms, but there are tradeoffs regarding development speed, built-in capabilities, and documentation. DCM simplifies the covariate modeling process and uncovers complex, non-linear relationships in computationally efficient workflows.
December 6, 2024
Presented at ACoP 2024. The poster introduces a framework for developing physiologically based pharmacokinetic (PBPK) models that incorporate partial differential equations (PDEs) to account for spatial drug distribution, using open-source Julia tools. This approach simplifies the integration of spatial components into PBPK models, demonstrated through a case study on naphthalene diffusion, and is applicable to various pharmacometric models requiring spatial considerations, such as topical, inhaled, and antitumor therapies.