Reconsideration of the current models of estimated kidney function-based drug dose adjustment in older adults: The role of biological age.

Human lifespan has increased from a median of 46.5 years in 1950 to 71.7 years in 2022. As people age, one of the inevitable consequences is a decline in kidney function and glomerular filtration rate (GFR) which can have direct or indirect effects on the pharmacokinetic and pharmacodynamic profiles of many drugs. Numerous equations have been developed to generate estimated GFR (eGFR) using the two principal biomarkers: serum creatinine and serum cystatin C. However, the trajectory of changes with aging is dissimilar in these equations. In addition, there is recognition that chronological age (lifespan) often does not reflect biological age (healthspan) as an essential parameter in kidney function equations. In the past decade, there has been an increasing interest in quantifying biological age and new commercially available assays have entered the marketplace. In this narrative review, we illustrate how dominant equations of eGFR model the fractional change in this parameter very differently across chronological age. In addition, we review various biological age indicators (aging clocks) and challenges to their application in clinical practice. Importantly, by comparing vancomycin's mean clearance as a drug with limited metabolism and unchanged elimination between two age milestones in some recent population pharmacokinetic models, we show how efforts to quantify kidney function in older adults optimally remain under-explored, particularly those at the upper end of their lifespan. We also propose considering new models that integrate biological age as a new pathway to improve precision drug dosing in older adults.

Response Surface Study on Molecular Docking Simulations of Citalopram and Donepezil as Potent CNS Drugs.

Computer-aided drug design provides broad structural modifications to evolving bioactive molecules without an immediate requirement to observe synthetic restraints or tedious protocols. Subsequently, the most promising guidelines with regard to synthetic and biological resources may be focused on upcoming steps. Molecular docking is common in-silico drug design techniques since it predicts ligand-receptor interaction modes and associated binding affinities. Current docking simulations suffer serious constraints in estimating accurate ligand-receptor binding affinities despite several advantages and historical results. Response surface method (RSM) is an efficient statistical approach for modeling and optimization of various pharmaceutical systems. With the aim of unveiling the full potential of RSM in optimizing molecular docking simulations, this study particularly focused on binding affinity prediction of citalopram-serotonin transporter (SERT) and donepezil-acetyl cholinesterase (AChE) complexes. For this purpose, Box-Behnken design of experiments (DOE) was used to develop a trial matrix for simultaneous variations of AutoDock4.2 driven binding affinity data with selected factor levels. Responses of all docking trials were considered as estimated protein inhibition constants with regard to validated data for each drug. The output matrix was subjected to statistical analysis and constructing polynomial quadratic models. Numerical optimization steps to attain ideal docking accuracies revealed that more accurate results might be envisaged through the best combination of factor levels and considering factor interactions. Results of the current study indicated that the application of RSM in molecular docking simulations might lead to optimized docking protocols with more stable estimates of ligand-target interactions and hence better correlation of in-silico in-vitro data.

Synthesis and toxicity assessment of 3-oxobutanamides against human lymphocytes and isolated mitochondria.

To reduce costly late-phase compound scrubbing, there has been an increased focus on assessing compounds within in vitro assays that predict properties of human safety liabilities, before preclinical in vivo studies. The aim of our study was to answer the questions that whether the toxicity risk of a series of 3-oxobutanamide derivatives could be predicted by using of human lymphocytes and their isolated mitochondria. Using biochemical and flow cytometry assessments, we demonstrated that exposure of lymphocytes and isolated mitochondria to five 3-oxobutanamide derivatives (1-5) did not exhibit remarkable toxicity at low concentrations (50-500µM) but toxicity could be observed at high concentrations (1000 and 2000µM), particularly for N-(5-(4-bromophenyl)-3-isoxazolyl)-3-oxobutanamide (4) and N-(2-benzothiazolyl)-3-oxo butanamide (5). Compounds 4, 5 and partly N-(5-methyl-3-isoxazol yl)-3-oxo butanamide (1) also showed a marked cellular and mitochondrial toxicity while compound 5 displayed superior toxicity. Compound 5 induced cytotoxicity on human blood lymphocytes which was associated with the generation of intracellular reactive oxygen species (ROS), mitochondrial membrane potential (MMP) collapse, lysosomal membrane injury, lipid peroxidation and depletion of glutathione. Our results suggested that among assessed compounds, increased toxicity of compound 5 compared to other compounds could be likely attributed to the presence of bromine substituent in 5. Finally our findings proposed that using of antioxidants and mitochondrial/lysosomal protective agents could be beneficial in decreasing the toxicity of 5.