AIMC Topic: Anti-Inflammatory Agents, Non-Steroidal

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Targeting CXCL8 in post-traumatic stress disorder and Alzheimer's disease: insights from cross-disorder molecular analysis.

Annals of medicine
BACKGROUND: Emerging clinical evidence indicates that post-traumatic stress disorder (PTSD) may accelerate Alzheimer's disease progression, yet the molecular mechanisms linking these disorders remain poorly understood.

Leading predictors and their associations with combination opioid pain therapy in older adults with cancer: Application of machine learning approaches.

PloS one
Combined use of opioids and other pharmacological therapies used for pain management, such as non-steroidal anti-inflammatory drugs (NSAIDs), benzodiazepines, gabapentinoids, and/or skeletal muscle relaxants (SMRs), in older adult cancer survivors ca...

Integrated experimental, computational and machine learning approaches for the development of Apremilast-Aceclofenac coamorphous systems.

International journal of pharmaceutics
Understanding the molecular mechanisms of drug coamorphization remains a key challenge in solid-state pharmaceutics. This study presents a molecular level strategy for designing drug-drug coamorphous systems (CAMs) of apremilast (APR) and aceclofenac...

Ratiometric Determination and Discrimination of Oxicams via Dual-Excitation Carbon Dots Assisted by Machine Learning.

Analytical chemistry
Oxicams, a major category of nonsteroidal anti-inflammatory drugs, are widely used in daily life. However, excessive consumption of oxicams can pose significant risks to human health. Herein, we introduce an innovative and highly sensitive fluorescen...

Combating Counterfeit Drugs via Machine Learning-Enabled Array Screening of Multilayer Evolutionary Combinatorial Libraries.

ACS applied materials & interfaces
Counterfeit drugs are a global issue that has a serious impact on patient morbidity and mortality. Driven by nonspecific cross-reactivity, sensor arrays enable the concurrent discrimination of structurally related drug molecules. Nevertheless, rapidl...

Advanced QSPR modeling of profens using machine learning and molecular descriptors for NSAID analysis.

Scientific reports
In this paper, we present a predictive model based on artificial neural network (ANN) to evaluate principal physicochemical properties of a set of anti-inflammatory drugs based on chosen topological indices. The molecular descriptors were calculated ...

Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique.

Scientific reports
This study develops and evaluates advanced hybrid machine learning models-ADA-ARD (AdaBoost on ARD Regression), ADA-BRR (AdaBoost on Bayesian Ridge Regression), and ADA-GPR (AdaBoost on Gaussian Process Regression)-optimized via the Black Widow Optim...

Testing on continuous production of mefenamic acids-Design of experiment through simulation and process optimisation.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
In the pharmaceutical manufacturing industry, continuous production methods have been recognised as providing several benefits compared to traditional batch production. These benefits include increased flexibility, higher product output, enhanced qua...

Machine Learning-Assisted Chemical Tongues Based on Dual-channel Inclusion Complexes for Rapid Identification of Nonsteroidal Anti-inflammatory Drugs in Food.

ACS sensors
The improper application of nonsteroidal anti-inflammatory drugs (NSAIDs) presents significant health hazards via vector food contamination. A critical limitation of these traditional existing approaches is their inability to concurrently discern and...

Machine Learning-Driven Prediction, Preparation, and Evaluation of Functional Nanomedicines Via Drug-Drug Self-Assembly.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Small molecules as nanomedicine carriers offer advantages in drug loading and preparation. Selecting effective small molecules for stable nanomedicines is challenging. This study used artificial intelligence (AI) to screen drug combinations for self-...