Dissertation/ Thesis
Identification of drug-target interactions and genetic variations leading to adverse drug reactions by using computational approaches ; Identification des interactions médicamenteuses délétères et des variations génomiques structurales entraînant des effets secondaires chez l'homme à l'aide d'outils d'apprentissage automatique
| العنوان: | Identification of drug-target interactions and genetic variations leading to adverse drug reactions by using computational approaches ; Identification des interactions médicamenteuses délétères et des variations génomiques structurales entraînant des effets secondaires chez l'homme à l'aide d'outils d'apprentissage automatique |
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| المؤلفون: | Dafniet, Bryan |
| المساهمون: | Unité de Biologie Fonctionnelle et Adaptative (BFA (UMR_8251 / U1133)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université Paris Cité, Olivier Taboureau |
| المصدر: | https://theses.hal.science/tel-04746890 ; Bio-informatique [q-bio.QM]. Université Paris Cité, 2022. Français. ⟨NNT : 2022UNIP5218⟩. |
| بيانات النشر: | HAL CCSD |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Adverse drug reactions, Drugs, Network sciences, Databases creation, Deep neural networks, Mutations, Phenotypes, Data integration, Effets indésirables, Médicaments, Science des réseaux, Bases de données, Réseaux de neurones profonds, Phénotypes, Intégrations de données, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] |
| الوصف: | The development of a drug is an expensive and time-consuming process that could take more than 10 years and cost around a billion euros. Although the drug’s target is usually known (primary target), it is also established that a drug interacts with multiple additional proteins (secondary targets) that can be responsible for side effects. These effects can be beneficial (repurposing) or noxious (adverse drug reaction). These secondary targets are not always identified and would cause 200 000 deaths/year, leading to a cost reaching a billion euros in Europe and USA. Moreover, it has been shown that genetic variations might also impact the efficacy of a drug and could contribute to adverse drug reactions. In these circumstances, the objective of the thesis was to develop computational methods allowing us to 1) integrate pharmacology data from multiple sources into one database and then select 5100 compounds with their biological activity on all of the human proteome with information from phenotypic screening. Compound-Target information was then linked to phenotypic screening information, and enrichment calculations were performed to assess the role of proteins on biological functions and diseases. Then 2) proteins frequently associated with adverse drug reactions have been determined based on known drug-target and adverse drug reaction information. By implementing a scoring function, the possible contribution of a protein in the apparition of adverse drug reactions has been assessed. In addition, the impact of Copy Number Variations (CNVs) on the apparition of such reactions has been analyzed. Finally in 3), predictive models have been developed allowing us to suggest if a drug would induce adverse drug reactions, based on the SOC nomenclature (System Organ Class) and Single Nucleotide Polymorphisms (SNPs), to overall analyze adverse drug reactions due to genetic variations on these drug targets. ; Le développement d’un médicament est un processus long et couteux pouvant durer plus de 10 ans et ayant un cout ... |
| نوع الوثيقة: | doctoral or postdoctoral thesis |
| اللغة: | French |
| Relation: | NNT: 2022UNIP5218 |
| الاتاحة: | https://theses.hal.science/tel-04746890 https://theses.hal.science/tel-04746890v1/document https://theses.hal.science/tel-04746890v1/file/Dafniet_Bryan_vd.pdf |
| Rights: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.48E7F814 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |