Predictive modeling of aspirin‐triggered resolvin D1 pharmacokinetics for the study of Sjögren's syndrome - Venkata Kashyap Yellepeddi; Olga J. Baker (Wiley, 2020)
Abstract Objectives Sjögren's syndrome (SS) is an autoimmune disease that causes chronic inflammation of the salivary glands leading to secretory dysfunction. Previous studies demonstrated that aspirin‐triggered resolvin D1 (AT‐RvD1) reduces inflammation and restores tissue integrity in salivary glands. Specifically, progression of SS‐like features in NOD/ShiLtJ mice can be systemically halted using AT‐RvD1 prior or after disease onset to downregulate proinflammatory cytokines, upregulate anti‐inflammatory molecules, and restore saliva production. Therefore, the goal of this paper was to create a physiologically based pharmacokinetic (PBPK) model to offer a reasonable starting point for required total AT‐RvD1 dosage to be administered in future mice and humans thereby eliminating the need for excessive use of animals and humans in preclinical and clinical trials, respectively. Likewise, PBPK modeling was employed to increase the range of testable scenarios for elucidating the mechanisms under consideration. Materials and methods Pharmacokinetics following intravenous administration of a 0.1 mg/kg dose of AT‐RvD1 in NOD/ShiLtJ were predicted in both plasma and saliva using PBPK modeling with PK‐Sim® and MoBi® Version 7.4 software. Results The model provides high‐value pathways for future validation via in vivo studies in NOD/ShiLtJ to corroborate the findings themselves while also establishing this method as a means to better target drug development and clinical study design. Conclusions Clinical and basic research would benefit from knowledge of the potential offered by computer modeling. Specifically, short‐term utility of these pharmacokinetic modeling findings involves improved targeting of in vivo studies as well as longer term prospects for drug development and/or better designs for clinical trials.