Open Access Databases and Datasets for Computer‐Aided Drug Design. A Short List Used in the Molecular Modelling Group of the
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Daina, Antoine; Ojeda‐Montes, María José; Bragina, Maiia E.; Cuozzo, Alessandro; Röhrig, Ute F.; Perez, Marta A.S.; Zoete, Vincent

doi:10.1002/9783527830497.ch1

Cited by 1 publication

(1 citation statement)

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“…Currently, many researchers are working intensively to replenish and systematize information on the biological activity of chemical compounds, both by developing existing databases and forming new specialized information resources on drugs. Thus, Daina, A. et al systematized open-access databases and datasets for computer drug design [ 25 ].…”

Section: Discussionmentioning

confidence: 99%

Digital Technology Applications in the Management of Adverse Drug Reactions: Bibliometric Analysis

Litvinova,

Yeung,

Hammerle

et al. 2024

Pharmaceuticals

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Adverse drug reactions continue to be not only one of the most urgent problems in clinical medicine, but also a social problem. The aim of this study was a bibliometric analysis of the use of digital technologies to prevent adverse drug reactions and an overview of their main applications to improve the safety of pharmacotherapy. The search was conducted using the Web of Science database for the period 1991–2023. A positive trend in publications in the field of using digital technologies in the management of adverse drug reactions was revealed. A total of 72% of all relevant publications come from the following countries: the USA, China, England, India, and Germany. Among the organizations most active in the field of drug side effect management using digital technologies, American and Chinese universities dominate. Visualization of publication keywords using VOSviewer software 1.6.18 revealed four clusters: “preclinical studies”, “clinical trials”, “pharmacovigilance”, and “reduction of adverse drug reactions in order to improve the patient’s quality of life”. Molecular design technologies, virtual models for toxicity modeling, data integration, and drug repurposing are among the key digital tools used in the preclinical research phase. Integrating the application of machine learning algorithms for data analysis, monitoring of electronic databases of spontaneous messages, electronic medical records, scientific databases, social networks, and analysis of digital device data into clinical trials and pharmacovigilance systems, can significantly improve the efficiency and safety of drug development, implementation, and monitoring processes. The result of combining all these technologies is a huge synergistic provision of up-to-date and valuable information to healthcare professionals, patients, and health authorities.

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Section: Discussionmentioning

confidence: 99%