Use of Real-world Data for New Drug Applications and Line Extensions
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
PURPOSE: For this article, the authors compiled, summarized, and analyzed data from 27 cases in which real-world data (RWD) were applied in regulatory approval. The aims were to provide an overview of RWD, based on classifications per therapeutic area, age group, drivers of acceptability, utility, data sources, and timelines, and to present insights on how it has been applied in regulatory decision making to date. METHODS: Clarivate Analytics was commissioned to collect data from cases in which RWD was used for new drug applications and line extensions submitted to the European Medicines Agency (EMA), the US Food and Drug Administration (FDA), Health Canada, and Japan's Pharmaceuticals and Medical Devices Agency. The query resulted in 27 cases in which regulatory approval was associated with RWD. The data were then categorized and elaborated with supporting information gathered from public databases and company websites. FINDINGS: There were 17 identified cases in which RWD were used for new drug applications, and 10 for line extensions, between the years 1998 and 2019. Approvals were spread across regulatory bodies: the EMA alone (6 cases), the FDA alone (4 cases), or jointly between the EMA and FDA or other regulatory bodies. The applications were also distributed across age groups and therapeutic areas but were mostly applied in oncology and metabolism. The new drug applications of all 17 products were approved, with drugs from new drug applications initially marketed as orphan drugs. In most cases, RWD were used either as primary data, when noncomparative data were available to demonstrate tolerability and efficacy, or as supportive data when validating findings. Common sources of RWD have been health or medical records (16 cases) and registries (8 cases). Review timelines in which RWD were applied were than 1 year for new drug applications and between 3 and 10 months for line extensions. IMPLICATIONS: The analysis of this study was limited in that the data were gathered from the commissioned query and may therefore have been nonexhaustive. Nonetheless, we recognize that the use of RWD has been gaining attention across the community and is expected to expand as a result of the various initiatives and efforts carried out in the sector. While the current application of RWD has been limited to specific cases, there is a potential to further explore and develop its application. Further refinements in the analytical processes, methodologies, and techniques would need to be established to achieve similar effects observed in randomized controlled trials.
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.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 découle