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Updated: Jan 18, 2026

Isolation and Differentiation of Stromal Vascular Cells to Beige/Brite Cells
Published on: March 28, 2013
An in-depth review of PPARγ modulators as anti-diabetes therapeutics
Aryan Jangra1, Basuvan Babu1, Selvaraj Divakar2
1Department of Pharmaceutical Analysis, JSS College of Pharmacy, JSS Academy of Higher Education & Research, Ooty, India.
Abstract:
Drug metabolism and pharmacokinetics (DMPK) plays a crucial role in optimizing peroxisome proliferator-activated receptor gamma (PPARγ) modulators by influencing metabolism, therapeutic efficacy, and safety. Rosiglitazone is primarily metabolized by cytochrome 2C8 (CYP2C8) and CYP2C9, with the CYP2C83 polymorphism increasing clearance, reducing efficacy, and altering fluid retention. Troglitazone metabolism via CYP3A4 and CYP2C8 generates a reactive quinone metabolite, depleting glutathione (GSH), elevating mitochondrial oxidative stress, and inducing hepatotoxicity. Glitazones also undergo GSH conjugation through open-ring formation, influencing detoxification and toxicity. Inflammation downregulates CYP enzymes and transporters, altering drug clearance and increasing drug-drug interaction (DDI) risks. Ketoconazole and troleandomycin inhibit rosiglitazone metabolism by 52% and 40%, respectively, while pioglitazone inhibits CYP2C8-mediated arachidonic acid metabolism, impairing renal function. Gemfibrozil further increases pioglitazone's area under the curve (AUC) threefold by inhibiting CYP2C8. Additionally, rosiglitazone modulates OATP1B1, enhancing pravastatin uptake at low concentrations but inhibiting it at higher levels, affecting plasma levels. Troglitazone inhibits organic anion-transporting polypeptide 1B1 (OATP1B1) mediated rosuvastatin uptake, reducing hepatic delivery and efficacy, necessitating strategic drug combinations. Furthermore, new PPARγ modulators are being developed via selective and partial activation to mitigate toxicity, incorporating non-thiazolidinedione scaffolds and optimizing DMPK properties through nanocarriers such as lipid-based nanoparticles. A deeper understanding of these factors is essential for designing next-generation PPARγ-targeted therapeutics, ensuring improved efficacy, reduced toxicity, and enhanced suitability for personalized medicine.
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