How to Build (and Regulate) A Body Part: Regulating Tissue Engineering in Canada
Notice bibliographique
Résumé
Efforts to replace or repair human tissues go back hundreds of years, but recent developments in biomedical and engineering sciences have made possible a new generation of technologies, creating the multidisciplinary field of “tissue engineering.” Tissue engineered products for skin and cartilage are already on the market, and recent breakthroughs include the successful implantation of engineered bladders and tracheas, as well as progress toward engineering more complex organs like lungs and intestines. Most tissue engineering applications still require years of development and testing before they can be clinically useful, but these recent advances have generated a great deal of excitement. This technology promises great benefits for patients, but also raises some novel ethical, legal, and policy issues. In particular, tissue engineering presents significant challenges for regulatory agencies responsible for overseeing the safety, efficacy, and quality of medical products. Tissue engineered products involve the convergence of several novel technologies, all complex in themselves and interacting in significant and perhaps unpredictable ways with each other and with the human body into which the product will be implanted. The complexity and novelty of these products will make them difficult to classify and will stretch the limits of our existing knowledge about how to assess the safety and efficacy of medical products. It will therefore be important to consider the extent to which our current regulatory framework is adequate to deal with these new types of products, and examine recent developments elsewhere that might provide models for reform. The way that regulatory requirements will be applied under this framework is just as important, however, so we also need to consider the challenges involved in assessing the novel technologies used in tissue engineering and their interactions. Concerns that have been raised about the resources and expertise available to agencies like Health Canada and the U.S. Food and Drug Administration (FDA) are highly relevant in this context, since tissue engineered products will place significant demands on the regulatory agencies charged with reviewing them. After introducing the field of tissue engineering, this article will discuss these challenges, and assess the extent to which Canada’s regulatory framework is prepared to meet them.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».