A Phase I Study of a Novel Antimycotic Vaginal Pessary Formulation (Econazole Nitrate 150 mg + Benzydamine HCl 6 mg) Administered Once Daily for 3 Days to Healthy Women

The primary objective of the study is to evaluate the local tolerability of the new Econazole/Benzydamine pessary, in comparison with Econazole and Benzydamine stand-alone products and placebo. Pharmacokinetics of the study products after single and multiple applications o.d. for 3 days, overall local and general tolerability, safety and comfort of use will also be evaluated.

开始日期2016-03-04

申办/合作机构

Aziende Chimiche Riunite Angelini Francesco - A.C.R.A.F. - SpA

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100 项与 CYP2C9 x COX 相关的临床结果

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100 项与 CYP2C9 x COX 相关的转化医学

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0 项与 CYP2C9 x COX 相关的专利（医药）

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项与 CYP2C9 x COX 相关的文献（医药）

2024-07-29·Drug Metabolism and Personalized Therapy

Clinical and pharmacogenetic features of patients with upper gastrointestinal lesions at a multidisciplinary hospital: the role of nonsteroidal anti-inflammatory drugs

Article

作者: Vakulenko, Olga Y ; Averkov, Oleg V ; Sychev, Dmitry A ; Tuchkova, Svetlana N ; Vechorko, Valery I ; Kryukov, Alexander V ; Sychev, Ivan V ; Denisenko, Natalia P ; Zhiryakova, Anna S ; Mirzaev, Karin B

AbstractObjectivesNonsteroidal anti-inflammatory drugs (NSAIDs) are among the most commonly prescribed medications, but their use can be associated with a number of adverse reactions, including upper gastrointestinal lesions. The aim of the study was to identify clinical and pharmacogenetic factors associated with upper gastrointestinal lesions, including those linked to NSAIDs, in patients at a multidisciplinary hospital.MethodsThe study included 92 patients (mean age 59.4±16.5 years; 47 women), who underwent esophagogastroduodenoscopy during inpatient treatment. Patients’ intake of NSAIDs and gastroprotectors during the year before hospitalization was considered. Demographic, clinical, laboratory data of patients were compared between groups, including genotyping for CYP2C9*2 rs179985, CYP2C9*3 rs1057910, CYP2C8*3 rs11572080, CYP2C8*3 rs10509681, PTGS-1 rs10306135, PTGS-1 rs12353214, and PTGS-2 rs20417 using real-time PCR.ResultsIn NSAIDs+ patients, PTGS1 rs10306135 AT+TT genotypes increased the chance of developing gastrointestinal complications by 5.4 times (95 % CI=1.30–22.27). In total sample, smoking (OR=3.12, 95 % CI=1.15–8.46), and alcohol intake (OR=4.09, 95 % CI=1.05–15.87) increased odds of gastrointestinal damage. In NSAIDs+ patients omeprazole, famotidine and both famotidine and omeprazole during the last year were as ineffective as not taking gastroprotectors; in total sample famotidine (OR=0.19, 95 % CI=0.04–0.93) and two gastroprotectors (OR=0.13, 95 % CI=0.02–0.75) reduced the chance of upper gastrointestinal lesions.ConclusionsPharmacogenetic features of patients may significantly contribute to the development NSAIDs-induced upper gastrointestinal injuries.

2024-06-01·Biomedical Chromatography

Investigation of the mechanism of nephrotoxicity of nux‐vomica by PTGS2/CYP2C9‐mediated arachidonic acid pathway and Jian Pi Tong Luo compound's protective effect

Article

作者: Zhang, Na ; Zhao, Liangyou ; Lv, Bochuan ; Liu, Shumin ; Zhao, Dapeng ; An, Baisong

AbstractThe clinical effectiveness of nux‐vomica in treating rheumatism and arthralgia is noteworthy; however, its nephrotoxicity has sparked global concerns. Hence, there is value in conducting studies on detoxification methods based on traditional Chinese medicine compatibility theory. Blood biochemistry, enzyme‐linked immunosorbent assay, and pathological sections were used to evaluate both the nephrotoxicity of nux‐vomica and the efficacy of the Jian Pi Tong Luo (JPTL) compound in mitigating this toxicity. Kidney metabolomics, using ultra‐high‐performance liquid chromatography–quadrupole‐time‐of‐flight–MS (UPLC–Q‐TOF–MS), was applied to elucidate the alterations in small‐molecule metabolites in vivo. In addition, network pharmacology analysis was used to verify the mechanism and pathways underlying the nephrotoxicity associated with nux‐vomica. Finally, essential targets were validated through molecular docking and western blotting. The findings indicated significant nephrotoxicity associated with nux‐vomica, while the JPTL compound demonstrated the ability to alleviate this toxicity. The mechanism potentially involves nux‐vomica activating the “PTGS2/CYP2C9–phosphatidylcholine–arachidonic acid metabolic pathway.” This study establishes a scientific foundation for the clinical use of nux‐vomica and lays groundwork for further research and safety assessment of toxic Chinese herbal medicines.

2023-07-17·Chemical research in toxicology

AI/ML Models to Predict the Severity of Drug-Induced Liver Injury for Small Molecules.

Article

作者: Will, Yvonne ; Aleo, Michael D ; Nassiri, Vahid ; Geys, Helena ; Rao, Mohan ; Alhambra, Cristóbal ; Irrechukwu, Onyi ; Snoeys, Jan ; Van Goethem, Freddy ; Mitra, Kaushik

Drug-induced liver injury (DILI), believed to be a multifactorial toxicity, has been a leading cause of attrition of small molecules during discovery, clinical development, and postmarketing. Identification of DILI risk early reduces the costs and cycle times associated with drug development. In recent years, several groups have reported predictive models that use physicochemical properties or in vitro and in vivo assay endpoints; however, these approaches have not accounted for liver-expressed proteins and drug molecules. To address this gap, we have developed an integrated artificial intelligence/machine learning (AI/ML) model to predict DILI severity for small molecules using a combination of physicochemical properties and off-target interactions predicted in silico. We compiled a data set of 603 diverse compounds from public databases. Among them, 164 were categorized as Most DILI (M-DILI), 245 as Less DILI (L-DILI), and 194 as No DILI (N-DILI) by the FDA. Six machine learning methods were used to create a consensus model for predicting the DILI potential. These methods include k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF), Naïve Bayes (NB), artificial neural network (ANN), logistic regression (LR), weighted average ensemble learning (WA) and penalized logistic regression (PLR). Among the analyzed ML methods, SVM, RF, LR, WA, and PLR identified M-DILI and N-DILI compounds, achieving a receiver operating characteristic area under the curve of 0.88, sensitivity of 0.73, and specificity of 0.9. Approximately 43 off-targets, along with physicochemical properties (fsp³, log S, basicity, reactive functional groups, and predicted metabolites), were identified as significant factors in distinguishing between M-DILI and N-DILI compounds. The key off-targets that we identified include: PTGS1, PTGS2, SLC22A12, PPARγ, RXRA, CYP2C9, AKR1C3, MGLL, RET, AR, and ABCC4. The present AI/ML computational approach therefore demonstrates that the integration of physicochemical properties and predicted on- and off-target biological interactions can significantly improve DILI predictivity compared to chemical properties alone.