Results 51 to 60 of about 22,128,804 (198)

In silico prediction of novel effective combinational treatment of chronic pain in individual patients: A joint white paper of the H2020 QSPainRelief consortium

open access: yesBritish Journal of Pharmacology, EarlyView.
Abstract Opioids are prescribed widely for chronic pain despite well‐recognised risks and variable long‐term benefit, reflecting the lack of effective alternatives for many patients. Combination therapies offer a promising strategy to enhance efficacy whilst reducing side effects.
André Mouraux   +26 more
wiley   +1 more source

QSPR Using MOLGEN-QSPR:  The Example of Haloalkane Boiling Points

open access: yes, 2019
MOLGEN-QSPR is a software newly developed for use in quantitative structure property relationships (QSPR) work. It allows to import, to manually edit, or to generate chemical structures, to detect duplicate structures, to import or to manually input ...
Christoph Rücker (6549539)   +2 more
core   +1 more source

Design Considerations for Polymer–Deep Eutectic Solvent Hybrid Systems for Transdermal Drug Delivery

open access: yesJournal of Applied Polymer Science, Volume 143, Issue 40, October 20, 2026.
Deep eutectic solvents (DESs) act as tunable, green excipients that modulate polymer structure–property relationships to enhance drug solubility, skin permeation, stability, and controlled release. Through hydrogen‐bond interactions, DES–polymer hybrid systems enable improved transdermal performance, offering a rational, design‐driven platform for ...
Madhavi Kailas Kapale   +3 more
wiley   +1 more source

Simplex representation of molecular structure as universal QSAR/QSPR tool.  [PDF]

open access: yes, 2021
We review the development and application of the Simplex approach for the solution of various QSAR/QSPR problems. The general concept of the simplex method and its varieties are described.
Artemenko, A.   +7 more
core   +1 more source

Nanostructured Deep Eutectic Systems in Healthcare: From Bioactive Solvents to Intelligent Biointerfaces, Wearables, and AI‐Driven Design

open access: yesAdvanced NanoBiomed Research, Volume 6, Issue 10, October 2026.
Beyond the green solvent paradigm, this review redefines Deep Eutectic Systems (DES) as programmable supramolecular nanoassemblies. We survey their biomedical convergence: stabilizing thermolabile mRNA to enable cold chain‐free logistics, reshaping transdermal microneedle delivery, enabling long‐term wearables via eutectogels, and utilizing Generative ...
Jeesu Moon, Min Seo Kim, Jae‐Seung Lee
wiley   +1 more source

Leap Zagreb indices of certain chemical structures: a topological analysis

open access: yesMain Group Metal Chemistry
Topological indices serve as important molecular descriptors in quantitative structure–property relationship (QSPR) and quantitative structure–activity relationship (QSAR) studies.
Rehman Masood Ur   +3 more
doaj   +1 more source

QSPR-driven prediction of analyte permeability for advancing CP-MIMS applications

open access: yesGreen Analytical Chemistry
Condensed Phase-Membrane Introduction Mass Spectrometry (CP-MIMS) is a sustainable and highly versatile approach within the framework of Direct Mass Spectrometry techniques, which enables real-time determination of target analytes by integrating sampling,
Enmanuel Cruz Muñoz   +4 more
doaj   +1 more source

Optical Basicity of Glasses: Review and Application in Nuclear Glass Formulation

open access: yesInternational Journal of Applied Glass Science, Volume 17, Issue 4, October 2026.
A self‐consistent set of optical basicity (OB) values was compiled and evaluated for 95 binary oxides using electronegativity, ionic–covalent, and optical‐property approaches, providing a robust basis for estimating the basicity of complex compounds and glasses.
John McCloy, John Bussey, Wyatt Kiff
wiley   +1 more source

Estudo da correlação quantitativa entre estrutura e propriedade (QSPR) usando descritores topológicos para compostos carbonílicos alifáticos [PDF]

open access: yes, 2001
Tese (doutorado) - Universidade Federal de Santa Catarina, Centro de Ciências Físicas e Matemáticas. Curso de Pós-Graduação em QuímicaNeste trabalho foi aplicada a relação quantitativa entre estrutura e atividade, empregando-se diferentes descritores ...
Amboni, Renata Dias de Mello Castanho
core  

Machine Learning Enabled Prediction and Interpretation of the Initial Dissolution Rates of Nuclear Waste Glasses

open access: yesInternational Journal of Applied Glass Science, Volume 17, Issue 4, October 2026.
ABSTRACT Accurate prediction of chemical durability, such as dissolution rate, is crucial for glass materials used in diverse applications, including pharmaceutical packaging and nuclear waste disposal. In this work, machine learning‐based prediction models were developed using structural descriptors derived from molecular dynamics (MD) simulations and
Wenqing Xie   +11 more
wiley   +1 more source

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