FCCC LOGO Faculty Publications
Holt K , Ye M , Nagar S , Korzekwa KR
Prediction of tissue - plasma partition coefficients using microsomal partitioning: Incorporation into physiologically-based pharmacokinetic models and steady state volume of distribution predictions
Drug Metab Dispos. 2019 Oct;47(10) :1050-1060
PMID: 31324699    PMCID: PMC6750188    URL: https://www.ncbi.nlm.nih.gov/pubmed/31324699
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Drug distribution is a necessary component of models to predict human pharmacokinetics. A new method (Kp,mem) to predict unbound tissue to plasma partition coefficients (Kpu) was developed using in vitro membrane partitioning (fum ), plasma protein binding (fup), and LogP. The resulting Kp values were used in a physiologically based pharmacokinetic (PBPK) model to predict the steady-state volume of distribution (Vss) and concentration-time (C-t) profiles for 19 drugs. These results were compared with Kp predictions using a standard method (Kp,dPL) that differentiates between acidic and neutral phospholipids. The Kp,mem method was parameterized using published rat Kpu data and tissue lipid composition. The Kpu values were well predicted with R2 = 0.8. When used in a PBPK model, Vss predictions were within 2-fold error for 12 of 19 drugs with Kp,mem versus 11 of 19 for Kp,dPL. With one outlier removed for Kp,mem and two for Kp,dPL, the Vss prediction R2 was 0.80 and 0.79 for the Kp,mem and Kp,dPL methods respectively. C-t profiles were also predicted and compared. Overall, the Kp,mem method predicted Vss and C-t profiles equally or better than the Kp,dPL method. An advantage of using fum to parameterize membrane partitioning is that fum data is used for clearance prediction and is therefore generated early in the discovery/development process. Also, the method provides a mechanistically sound basis for membrane partitioning and permeability for further improving physiologic PK models. SIGNIFICANCE STATEMENT: A new method to predict tissue-plasma partition coefficients was developed. The method provides a more mechanistic basis to model membrane partitioning.
1521-009x Holt, Kimberly Ye, Min Nagar, Swati Korzekwa, Ken R Journal Article United States Drug Metab Dispos. 2019 Oct;47(10):1050-1060. doi: 10.1124/dmd.119.087973. Epub 2019 Jul 19.