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INTRODUCTION: Janus kinase (JAK) inhibitors were recently identified as promising drug candidates for repurposing in Alzheimer's disease (AD) due to their capacity to suppress inflammation via modulation of JAK/STAT signaling pathways. Besides interaction with primary therapeutic targets, JAK inhibitor drugs frequently interact with unintended, often unknown, biological off-targets, leading to associated effects. Nevertheless, the relevance of JAK inhibitors' off-target interactions in the context of AD remains unclear. METHODS: Putative off-targets of baricitinib and tofacitinib were predicted using a machine learning (ML) approach. After screening scientific literature, off-targets were filtered based on their relevance to AD. Targets that had not been previously identified as off-targets of baricitinib or tofacitinib were subsequently tested using biochemical or cell-based assays. From those, active concentrations were compared to bioavailable concentrations in the brain predicted by physiologically based pharmacokinetic (PBPK) modeling. RESULTS: With the aid of ML and in vitro activity assays, we identified two enzymes previously unknown to be inhibited by baricitinib, namely casein kinase 2 subunit alpha 2 (CK2-α2) and dual leucine zipper kinase (MAP3K12), both with binding constant (K d) values of 5.8 µM. Predicted maximum concentrations of baricitinib in brain tissue using PBPK modeling range from 1.3 to 23 nM, which is two to three orders of magnitude below the corresponding binding constant. CONCLUSION: In this study, we extended the list of baricitinib off-targets that are potentially relevant for AD progression and predicted drug distribution in the brain. The results suggest a low likelihood of successful repurposing in AD due to low brain permeability, even at the maximum recommended daily dose. While additional research is needed to evaluate the potential impact of the off-target interaction on AD, the combined approach of ML-based target prediction, in vitro confirmation, and PBPK modeling may help prioritize drugs with a high likelihood of being effectively repurposed for AD. Highlights: This study explored JAK inhibitors' off-targets in AD using a multidisciplinary approach.We combined machine learning, in vitro tests, and PBPK modelling to predict and validate new off-target interactions of tofacitinib and baricitinib in AD.Previously unknown inhibition of two enzymes (CK2-a2 and MAP3K12) by baricitinib were confirmed using in vitro experiments.Our PBPK model indicates that baricitinib low brain permeability limits AD repurposing.The proposed multidisciplinary approach optimizes drug repurposing efforts in AD research.
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Identifying critical attributes for complex locally acting ophthalmic formulations and establishing in vitro-in vivo correlations can facilitate selection of appropriate thresholds for formulation changes that reflect lack of impact on in vivo performance. In this study the marketed antiglaucoma product Azopt® (1% brinzolamide suspension) and five other brinzolamide formulations varying in particle size distributions and apparent viscosities were topically administered in rabbits, and their ocular pharmacokinetics was determined in multiple ocular tissues. Statistical evaluation with ANOVA showed no significant differences between the formulations in the peak drug concentration (Cmax) in the aqueous humor and iris-ciliary body. As a post-hoc analysis, the within animal and total variability was determined for Cmax in the aqueous humor and iris-ciliary body. Based on the observed variability, we investigated the sample size needed for two types of study designs to observe statistically significant differences in Cmax. For the sample size calculations, assuming both 25% and 50% true differences in Cmax between two formulations, two study designs were compared: paired-eye dosing design (one formulation in one eye and another formulation in the other eye of the same animal at the same time) versus parallel-group design. The number of rabbits needed in the paired-eye dosing design are much lower than in the parallel-group design. For example, when the true difference in aqueous humor Cmax is 25%, nine rabbits are required in the paired-eye design versus seventy rabbits (35 per treatment) in the parallel-group design to observe a statistically significant difference with a power of 80%. Therefore, the proposed paired-eye dosing design is a viable option for the design of pharmacokinetic studies comparing ophthalmic products to determine the impact of formulation differences.