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!. Baptiste and . Canault!-!-développement!d'une!plateforme!de!prédiction!in#silico#des!propriétés!adme>tox-résumé&, Elimination&(ADME)&et&la&Toxicité&(Tox)&sont&cruciales&pour&le&succès&des&phases&cliniques&lors& de& la& conception& de& nouveaux& médicaments.& Durant& ce& processus,& la& chémoinformatique& est& régulièrement& utilisée& afin& de& prédire& le& profil& ADMEFTox& des& molécules& bioactives& et& d'améliorer& leurs& propriétés& pharmacocinétiques.& Ces& modèles& de& prédiction,& basés& sur& la& quantification& des& & relations& structureFactivité& (QSAR),&ne&sont&pas&toujours&efficaces&à&cause&du&faible&nombre&de&données&ADMEFTox&disponibles&et&de&leur& hétérogénéité&induite&par&des&différences&dans&les&protocoles&expérimentaux,&ou&encore&de&certaines&erreurs& expérimentales.&Au&cours&de&cette&thèse,&nous&avons&d'abord&constitué&une&base&de&données&contenant&150& 000&mesures&pour&une&cinquantaine&de&propriétés&ADMEFTox.&Afin&de&valoriser&l'ensemble&de&ces&données,& nous& avons& dans& un& deuxième& temps& proposé& une& plateforme& automatique& de& création& de& modèles& de& prédiction&QSAR.&Cette&plateforme,&nommée&MetaPredict,&a&été&conçue&afin&d'optimiser&chacune&des&étapes& de&création&d'un&modèle&statistique,&dans&le&but&d'améliorer&leur&qualité&et&leur&robustesse.&Nous&avons&dans& un& troisième& temps& valorisé& les& modèles& obtenus& grâce& à& la& plateforme& MetaPredict& en& proposant& une& application& en& ligne.& Cette& application& a& été& développée& pour& faciliter& l'utilisation& des& modèles,& apporter& une& interprétation& simplifiée& des& résultats& et& moduler& les& observations& obtenues& en&fonction& des&spécificités& d'un& projet& de& recherche.& Finalement,& MetaPredict& permet& de& rendre& les& modèles& ADMEFTox& accessibles& à& l'ensemble&des&chercheurs, Dans& le& cadre& de& la& recherche& pharmaceutique,& les& propriétés& relatives& à& l'Absorption,& la& Distribution,& le& Métabolisme,&l

, Tox)& properties& are& crucial& for& the& success&of&clinical&trials&of&a&drug&candidate.&During&this&process,&chemoinformatics&is&regularly&used&to&predict& the& ADMEFTox& profile& of& bioactive& compounds& and& to& improve& their& pharmacokinetic& properties.& In# silico# approaches&have&already&been&developed&to&improve&poor&pharmacokinetics&and&toxicity&of&lead&compounds.& These&predictive&models,&based&on&the&quantification&of&structureFactivity&relationships&(QSAR),&were&not&always& efficient& enough& due& to& the& low& number& of& accessible&biological& data& and& their& heterogeneity& induced& by& the& differences&in&experimental&assays&or&the&significant&experimental&error.&In&this&thesis,&we&first&built&a&database& containing&150,000&data&points&for&about&50&ADMEFTox&properties.&In&order&to&valorize&all&this&data,&we&then& proposed& an& automatic& platform& for& creating& predictive& models, This& platform,& called& MetaPredict,& has& been& designed&to&optimize&each&step&of&model&development,&in&order&to&improve&their&quality&and&robustness.&Third,& we&promoted&the&statistical&models&using&the&online&application&of&MetaPredict&platform.&This&application&has& been&developed&to&facilitate&the&use&of&newly&built&models,&to&provide&a&simplified&interpretation&of&the&results& and& to&modulate& the& obtained& observations& according& to& the& needs& of& the& researchers.& Finally,& this& platform& provides&an&easy&access&to&the&ADMEFTox&models&for&the&scientific&community.& Keywords&:&chemoinformatics,&ADMEFTox,&QSAR,&bioactive&molecules& & Institut!de!Chimie!Organique!et!Analytique!UMR!