Identifying and understanding the relationships between drug intake and adverse effects that can occur due to inadvertent molecular interactions between drugs and targets is a difficult task, especially considering the numerous variables that can influence the onset of such events. The ability to predict these side effects in advance would help physicians develop strategies to avoid or counteract them. In this article, we review the main computational methods for predicting side effects caused by drug molecules, highlighting their performance, limitations and application cases. Furthermore, we provide an overall view of resources, such as databases and tools, useful for building side effect prediction analyses.
Network medicine and systems pharmacology approaches to predicting adverse drug effects / Funari, Alessio; Fiscon, Giulia; Paci, Paola. - In: BRITISH JOURNAL OF PHARMACOLOGY. - ISSN 0007-1188. - (2024), pp. 1-13. [10.1111/bph.17330]
Network medicine and systems pharmacology approaches to predicting adverse drug effects
Funari, AlessioPrimo
;Fiscon, GiuliaSecondo
;Paci, Paola
Ultimo
2024
Abstract
Identifying and understanding the relationships between drug intake and adverse effects that can occur due to inadvertent molecular interactions between drugs and targets is a difficult task, especially considering the numerous variables that can influence the onset of such events. The ability to predict these side effects in advance would help physicians develop strategies to avoid or counteract them. In this article, we review the main computational methods for predicting side effects caused by drug molecules, highlighting their performance, limitations and application cases. Furthermore, we provide an overall view of resources, such as databases and tools, useful for building side effect prediction analyses.File | Dimensione | Formato | |
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Funari_Network_2024.pdf
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Note: https://doi.org/10.1111/bph.17330
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