Facing the Facts of Altered Plasma Protein Binding: Do Current Models Correctly Predict Changes in Fraction Unbound in Special Populations?

• DOI: 10.1016/j.xphs.2024.02.024
• Publication Date: 2024-02-28T09:15:46Z
• Authors: Jokha Al-Qassabi; Shawn Pei Feng Tan; Patcharapan Phonboon; Aleksandra Galetin; Amin Rostami-Hodj...; Daniel Scotcher
• Keywords: Fraction (chemistry)

Accounting for variability in plasma protein binding of drugs is an essential input to physiologically-based pharmacokinetic (PBPK) models special populations. Prediction fraction unbound (fu) such populations typically considers changes concentration while assuming that the affinity remains unchanged. A good correlation between predicted vs observed fu data reported various a given population often used as justification predictive methods. However, none these analyses evaluated prediction fold-change relative reference population. This would be more appropriate assessment predictivity, analogous drug-drug interactions. In this study, performance single was assessed by predicting alpha-1-acid glycoprotein and albumin bound hepatic impairment, renal paediatric, elderly, patients with inflammatory disease, different ethnic groups dataset >200 drugs. For models, concordance coefficients were >0.90 16 out 17 sub-groups, indicating strong agreement values. contrast, same <0.38 all sub-groups. Trends similar models. Accordingly, predictions solely based on concentrations cannot explain values some We recommend further consideration impact endogenous substances competitively bind proteins, structure due posttranslational modifications. PBPK highly should preferably use measured ensure reliable drug exposure or compare knowing will not sensitive fu.