Canadian Legal Oversight of Pharmacogenomics and Nutrigenomics
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Notice bibliographique
Résumé
Equipped with the knowledge that the Human Genome Project yielded, (1) biomedical researchers and clinicians are looking to enhance human health. Research to understand both the interaction between genes and pharmaceutical drugs and the interaction between genes and nutrients is quickly helping to develop new genomic applications. Is Canadian law well prepared to handle these advances? An examination of federal law addresses pharmacogenomics (2) and (3) may help provide an answer. This comparison is particularly compelling in light of growing anticipation that a new era of personalized medicine has dawned. (4) Indeed, both pharmacogenomics and aim to personalize (5) medicine and nutrition, and ultimately health, by tailoring drugs or foods to individual genotypes. (6) Specifically, through pharmacogenomics, it will become possible to individualize therapies, (7) adapting a patient's treatment by selecting optimal drugs, adjusting dosage, or managing potential adverse effects. (8) Similarly, personalized nutrition will entail decisions about nutrition and overall health based on an individual's knowledge of nutrition and of their genetic make-up, informed either by means of genetic testing or indirectly through family history or personal experience. (9) Moreover, as both pharmacogenomics and explore how whether naturally occurring or manufactured, alter and regulate biological processes and individual genetic variation influences the responses to those chemicals, (10) some researchers have suggested that nutrigenomics and pharmacogenomics may best be viewed not only as a continuum but also as inseparable in clinical applications. Indeed, the emerging knowledge of nutrient-gene interactions shows that certain chemicals in food directly alter the same molecular pathways targeted by drugs, or alter interacting pathways that may influence drug efficacy. (11) In 2000, the pharmaceutical company Novartis and the food manufacturer Quaker Oats formed Altus Food to develop functional foods and beverages offering scientifically proven health benefits beyond basic nutrition. (12) Although the joint venture did not survive a subsequent merger between Pepsi-Co and Quaker, (13) it remains an indication of potential genomic-based corporate convergences. This article does not pretend to assess fully whether Canadian law is compatible with or supportive of genomic advances. Rather, it points to many legal considerations that would need careful examination to derive a definitive answer. This overview begins with a brief discussion of the research and development challenges that confront both the pharmaceutical and food sectors, and the leverage genomic technologies may bring. It also reviews the regulation of clinical trials with a focus on relevant genomic aspects. Finally, it points to potential liability risks that manufacturers or health care professionals may encounter once genomic products and services become more widely available. Food and Drug Research & Development During the research and development phases, new drugs and new food products face significant challenges, even though they go through markedly different channels: one commentator noted that the pharmaceutical industry operates in the world of rational drug design and clinical trials where physicians ultimately intervene in decisions regarding patients and medication, whereas the food industry operates in the world of taste and convenience where trials are limited and products are promoted directly to consumers. (14) However, using genomics, it is possible the two worlds will move closer together, a trend already started with the scientifically based health claims made in relation to certain foods. The challenges of pharmaceutical companies are well known: in the US, the number of new drug applications for major drug products or of biological license applications for new molecular entities submitted to the Food and Drug Administration (FDA) has steadily decreased over the past 15-20 years. …
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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 | 0,000 | 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 | 0,000 |
| 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