Tag: M.W=350-400

Wang, Dongdong published the artcilePopulation pharmacokinetics of tacrolimus in pediatric refractory nephrotic syndrome and a summary of other pediatric disease models, Quality Control of 72509-76-3, the main research area is tacrolimus pediatric refractory nephrotic syndrome pharmacokinetics; nonlinear mixed-effects modeling; pediatric refractory nephrotic syndrome; population pharmacokinetics; tacrolimus; therapeutic drug monitoring.

Different tacrolimus (TAC) population pharmacokinetic (PPK) models have been established in various pediatric disease populations. However, a TAC PPK model for pediatric refractory nephrotic syndrome (PRNS) has not been well characterized. The current study aimed to establish a TAC PPK model in Chinese PRNS and provide a summary of previous literature concerning TAC PPK models in different pediatric diseases. A total of 147 TAC conventional therapeutic drug monitoring (TDM) data from multiple blood samples obtained from 65 Chinese patients with PRNS were characterized using nonlinear mixed-effects modeling. The impacts of demog. features, biol. characteristics and drug combination were evaluated. Model validation was assessed using the bootstrap method. A one-compartment model with first-order absorption and elimination was determined to be the most suitable model for TDM data in PRNS. The absorption rate constant (Ka) was set at 4.48 h-1. The typical values of apparent oral clearance (CL/F) and apparent volume of distribution (V/F) in the final model were 5.46 l/h and 57.1 l, resp. The inter-individual variability of CL/F and V/F were 22.2 and 0.2%, resp. The PPK equation for TAC was: CL/F = 5.46 × exponential function (EXP)(0.0323 × age) × EXP(-0.359 × cystatin-C) × EXP(0.148 × daily dose of TAC). No significant effects of covariates on V/F were observed In conclusion, the current study developed and validated the first TAC PPK model for patients with PRNS. The study also provided a summary of previous literature concerning other TAC PPK models in different pediatric diseases.

Experimental and Therapeutic Medicine published new progress about Homo sapiens. 72509-76-3 belongs to class pyridine-derivatives, name is 3-Ethyl 5-methyl 4-(2,3-dichlorophenyl)-2,6-dimethyl-1,4-dihydropyridine-3,5-dicarboxylate, and the molecular formula is C18H19Cl2NO4, Quality Control of 72509-76-3.

Referemce:
Pyridine – Wikipedia,
Pyridine | C5H5N – PubChem

Lee, A. Reum published the artcileLercanidipine synergistically enhances bortezomib cytotoxicity in cancer cells via enhanced endoplasmic reticulum stress and mitochondrial Ca2+ overload, Application of 3-Ethyl 5-methyl 4-(2,3-dichlorophenyl)-2,6-dimethyl-1,4-dihydropyridine-3,5-dicarboxylate, the main research area is breast cancer lercanidipine bortezomib cytotoxicity endoplasmic reticulum mitochondria calcium; ER stress; bortezomib; lercanidipine; mitochondrial Ca2+ overload; paraptosis.

The proteasome inhibitor (PI), bortezomib (Btz), is effective in treating multiple myeloma and mantle cell lymphoma, but not solid tumors. In this study, we show for the first time that lercanidipine (Ler), an antihypertensive drug, enhances the cytotoxicity of various PIs, including Btz, carfilzomib, and ixazomib, in many solid tumor cell lines by inducing paraptosis, which is accompanied by severe vacuolation derived from the endoplasmic reticulum (ER) and mitochondria. We found that Ler potentiates Btz-mediated ER stress and ER dilation, possibly due to misfolded protein accumulation, in MDA-MB 435S cells. In addition, the combination of Btz and Ler triggers mitochondrial Ca2+ overload, critically contributing to mitochondrial dilation and subsequent paraptotic events, including mitochondrial membrane potential loss and ER dilation. Taken together, our results suggest that a combined regimen of PI and Ler may effectively kill cancer cells via structural and functional perturbations of the ER and mitochondria.

International Journal of Molecular Sciences published new progress about Antitumor agents. 72509-76-3 belongs to class pyridine-derivatives, name is 3-Ethyl 5-methyl 4-(2,3-dichlorophenyl)-2,6-dimethyl-1,4-dihydropyridine-3,5-dicarboxylate, and the molecular formula is C18H19Cl2NO4, Application of 3-Ethyl 5-methyl 4-(2,3-dichlorophenyl)-2,6-dimethyl-1,4-dihydropyridine-3,5-dicarboxylate.

Referemce:
Pyridine – Wikipedia,
Pyridine | C5H5N – PubChem

Williams, Dominic P. published the artcilePredicting Drug-Induced Liver Injury with Bayesian Machine Learning, HPLC of Formula: 72509-76-3, the main research area is machine learning drug liver toxicity prediction risk assessment.

Drug induced liver injury (DILI) can require significant risk management in drug development, and on occasion can cause morbidity or mortality, leading to drug attrition. Optimizing candidates preclinically can minimise hepatotoxicity risk but it is difficult to predict due to multiple etiologies encompassing DILI, often with multifactorial and overlapping mechanisms. In addition to epidemiol. risk factors, physicochem. properties, dose, disposition, lipophilicity, and hepatic metabolic function are also relevant for DILI risk. Better human relevant, predictive models are required to improve hepatotoxicity risk assessment in drug discovery. The authors’ hypothesis is that integrating mechanistically relevant hepatic safety assays with Bayesian machine learning will improve hepatic safety risk prediction. The authors present a quant. and mechanistic risk assessment for candidate nomination using data from in vitro assays (hepatic spheroids, BSEP, mitochondrial toxicity and bioactivation), together with physicochem. (cLogP) and exposure (Cmaxtotal) variables from a chem. diverse compound set (33 no/low-, 40 medium- and 23 high-severity DILI compounds). The Bayesian model predicts the continuous underlying DILI severity and uses a data-driven prior distribution over the parameters to prevent overfitting. The model quantifies the probability that a compound falls into either no/low, medium, or high-severity categories, with a balanced accuracy of 63% on held-out samples, and a continuous prediction of DILI severity along with uncertainty in the prediction. For a binary yes/no DILI prediction, the model has a balanced accuracy of 86%, a sensitivity of 87%, a specificity of 85%, a pos. predictive value of 92%, and a neg. predictive value of 78%. Combining physiol. relevant assays, improved alignment with FDA recommendations, and optimal statistical integration of assay data, leads to improved DILI risk prediction.

Chemical Research in Toxicology published new progress about Biotransformation. 72509-76-3 belongs to class pyridine-derivatives, name is 3-Ethyl 5-methyl 4-(2,3-dichlorophenyl)-2,6-dimethyl-1,4-dihydropyridine-3,5-dicarboxylate, and the molecular formula is C18H19Cl2NO4, HPLC of Formula: 72509-76-3.

Referemce:
Pyridine – Wikipedia,
Pyridine | C5H5N – PubChem

Johnson, Ted W. published the artcileDiscovery of (10R)-7-Amino-12-fluoro-2,10,16-trimethyl-15-oxo-10,15,16,17-tetrahydro-2H-8,4-(metheno)pyrazolo[4,3-h][2,5,11]-benzoxadiazacyclotetradecine-3-carbonitrile (PF-06463922), a Macrocyclic Inhibitor of Anaplastic Lymphoma Kinase (ALK) and c-ros Oncogene 1 (ROS1) with Preclinical Brain Exposure and Broad-Spectrum Potency against ALK-Resistant Mutations, Related Products of pyridine-derivatives, the publication is Journal of Medicinal Chemistry (2014), 57(11), 4720-4744, database is CAplus and MEDLINE.

Although crizotinib demonstrates robust efficacy in anaplastic lymphoma kinase (ALK)-pos. non-small-cell lung carcinoma patients, progression during treatment eventually develops. Resistant patient samples revealed a variety of point mutations in the kinase domain of ALK, including the L1196M gatekeeper mutation. In addition, some patients progress due to cancer metastasis in the brain. Using structure-based drug design, lipophilic efficiency, and phys.-property-based optimization, highly potent macrocyclic ALK inhibitors were prepared with good absorption, distribution, metabolism, and excretion (ADME), low propensity for p-glycoprotein 1-mediated efflux, and good passive permeability. These structurally unusual macrocyclic inhibitors were potent against wild-type ALK and clin. reported ALK kinase domain mutations. Significant synthetic challenges were overcome, utilizing novel transformations to enable the use of these macrocycles in drug discovery paradigms. This work led to the discovery of 8k (PF-06463922), combining broad-spectrum potency, central nervous system ADME, and a high degree of kinase selectivity.

Journal of Medicinal Chemistry published new progress about 1454848-00-0. 1454848-00-0 belongs to pyridine-derivatives, auxiliary class Aromatic Fluorinated Building Blocks, name is (R)-Methyl 2-(1-((2-amino-5-bromopyridin-3-yl)oxy)ethyl)-4-fluorobenzoate, and the molecular formula is C15H14BrFN2O3, Related Products of pyridine-derivatives.

Referemce:
https://en.wikipedia.org/wiki/Pyridine,
Pyridine | C5H5N – PubChem

Rayder, Thomas M. published the artcileA Bioinspired Multicomponent Catalytic System for Converting Carbon Dioxide into Methanol Autocatalytically, Computed Properties of 338800-13-8, the publication is Chem (2020), 6(7), 1742-1754, database is CAplus.

Nature utilizes multicomponent catalyst systems to convert simple, abundant starting materials into complex mols. that are essential for life. In contrast, synthetic chem. transformations rarely adopt this strategy because it is difficult to replicate the sophisticated supramol. assemblies used by biol. for active-site separation and substrate trafficking. Here, we describe a method for multicomponent catalyst separation that involves encapsulating transition-metal complexes in nanoporous materials called metal-organic frameworks. The multicomponent catalyst system was highly active for converting hydrogen and carbon dioxide to methanol, and it could be formulated to be readily recyclable. Moreover, we uncovered an autocatalytic feature that was possible only when we utilized the multicomponent catalyst strategy. These results open avenues for obtaining fuel from abundant and renewable resources.

Chem published new progress about 338800-13-8. 338800-13-8 belongs to pyridine-derivatives, auxiliary class Bis-phosphine Ligands, name is 2,6-Bis((di-tert-butylphosphino)methyl)pyridine, and the molecular formula is C23H43NP2, Computed Properties of 338800-13-8.

Referemce:
https://en.wikipedia.org/wiki/Pyridine,
Pyridine | C5H5N – PubChem