Cited by Machine Learning based Modeling of Drugs using Virtual Screening and in Silico Approach

Integrating Quantitative Methods & Modeling and Analytical Techniques in Reverse Engineering; A Cutting-Edge Strategy in Complex Generic Development DOI

Ashok Kumar Rajput,

Megha Pillai,

Jinal Ajabiya

et al.

AAPS PharmSciTech, Journal Year: 2025, Volume and Issue: 26(4)

Published: March 26, 2025

Language: Английский

Citations

Particle size matters: The impact of particle size on properties and performance of long-acting injectable crystalline aqueous suspensions DOI

Jiaying Liu, Feng Xu, Di Wu

et al.

Journal of Controlled Release, Journal Year: 2025, Volume and Issue: unknown, P. 113793 - 113793

Published: April 1, 2025

Language: Английский

Citations

Computational Modelling for Formulation Design DOI

Teja Kumar Ponduri,

Roja Rani Budha,

Deepika Paliwal

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

Characterization of Pediatric Rectal Absorption, Drug Disposition, and Sedation Level for Midazolam Gel Using Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling DOI

Jinying Zhu,

Sufeng Zhou,

Lu Wang

et al.

Molecular Pharmaceutics, Journal Year: 2024, Volume and Issue: 21(5), P. 2187 - 2197

Published: March 29, 2024

This study aims to explore and characterize the role of pediatric sedation via rectal route. A physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) model midazolam gel was built validated support dose selection for clinical trials. Before developing PBPK model, an intravenous developed determine drug disposition, specifically by describing ontogeny metabolic enzyme. Pediatric absorption on adults. The improved Weibull function with permeability, surface area, fluid volume parameters used extrapolate absorption. logistic regression relationship between free concentrations probability sedation. All models successfully described PK profiles absolute average fold error (AAFE) < 2, especially our that extended predicted age preterm. simulation results PD showed when ranged from 3.9 18.4 ng/mL, "Sedation" greater than "Not-sedation" states. Combined recommended doses were in ranges 0.44-2.08 mg/kg children aged 2-3 years, 0.35-1.65 4-7 0.24-1.27 8-12 0.20-1.10 adolescents 13-18 years. Overall, this mechanistically quantified disposition effect population, accurately observed data, simulated exposure will inform following

Language: Английский

Citations

Molecular Docking Analysis of Flavonoid Compounds from <em>Glycyrrhiza glabra</em> on the Interleukin – 1 Receptor (IL-1R) as a Candidate for Anti-Inflammatory Drug in Periodontitis DOI

Elza Ibrahim Auerkari,

Samantha Ruth Andriawan,

Pertti Auerkari

et al.

Published: Nov. 24, 2023

Periodontitis is a disease that originates from gingival tissue, and if left untreated, can cause inflammation to spread deeper tissues, altering bone homeostasis, even leading tooth loss. When the bacteria in plaque reach sufficient numbers, immune system responds by activating cells will produce cytokines, including interleukin-1 (IL-1), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α). These signaling molecules coordinate inflammatory responses. IL-1 binds receptor (IL-1R) on surface of target cells, initiating an response intracellular signalling pathways. Inhibition IL-1R prevent interaction with this receptor, thereby halting activation pathway. By substituting connection active anti-inflammatory substances, it possible contact between IL-1R. The licorice plant, Glycyrrhiza glabra, includes eight types flavonoids significant potential, namely isoliquiritigenin, glyzaglabrin, prunetin, shinpterocarpin, licochalcone A, glabridin, glisoflavone, isoangustone A. This study aims assess potential such as candidates for periodontitis treatment through molecular docking, using AutoDock Tools v.1.5.6. All tested compounds showed highly stable bonds IL-1R, binding affinity values below -7 kcal/mol. Van der Waals forces, hydrogen bonds, hydrophobic all contribute stability these interactions. Among compounds, which has Ki value 90.89 nM ΔG -9.61 kcal/mol, highest

Language: Английский

Citations

Machine Learning based Modeling of Drugs using Virtual Screening and in Silico Approach DOI

K S Balamurugan,

K Appathurai,

P J Sathish Kumar

et al.

Published: Sept. 18, 2024

Language: Английский

Citations