Notice bibliographique
Résumé
Personalized medicine is an emerging field with a goal of applying genomic information as a predictor of disease risk as well as individualization of drug therapy. For optimization of drug therapy, significant progress has been made in the past decade in linking genetic variation in genes associated with drug disposition to prediction of drug response and adverse reactions. For most drugs in clinical use, the interplay of many factors, including genetics, demographics, drug-drug interactions, disease states and the environment, result in the interindividual variability observed during drug therapy. Broadly speaking, such determinants of drug response are mediated through modulation of drug concentrations reflective of pharmacokinetic factors, as well as drug targets, often referred to as pharmacodynamics. It is clear that for personalized medicine to become clinically meaningful, genomic as well as clinical and environmental influences must be considered together. We show, for a number of drugs in clinical use, that genomics-guided treatment options not only are becoming feasible but are also on the cusp of showing superiority in terms of clinical outcomes as well as cost-benefit. One of the most widely studied drugs with regard to genomics-guided dosing options is the oral anticoagulant, warfarin. Genetic polymorphisms in the gene encoding cytochrome P450 2C9 (CYP2C9) and those in the target gene responsible for the warfarin anticoagulant effect, vitamin K epoxide reductase (VKORC1), account for much of the variability in the warfarin maintenance dose; however, routine genotyping in warfarin therapy remains controversial. We will outline the importance of understanding all of the variables that mediate warfarin response as the prerequisite to successful utilization of genotype-guided warfarin therapy. Similarly, HMG Co-A reductase inhibitors, commonly known as statins, also display wide interindividual variability in plasma concentration, response and toxicity due in part to polymorphisms in transporter genes, including SLCO1B1 and ABCG2. Genetic factors are also important considerations in treatment with other therapeutic agents discussed, including clopidogrel and tamoxifen. Implementation of personalized medicine-based treatment options for these and other drugs, the pharmacokinetics or pharmacodynamics of which are impacted by functional genetic variations, will require overcoming a number of challenges, including cost, turnaround time, and demonstration of clinical benefit, as well as better training of health care professionals about genomics in general, and pharmacogenomics in particular.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,039 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,001 |
| Bibliométrie | 0,000 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,009 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».