Harnessing biodiversity: the Malagasy Institute of Applied Research (IMRA)
Notice bibliographique
Résumé
BACKGROUND: Biopiracy - the use of a people's long-established medical knowledge without acknowledgement or compensation - has been a disturbing historical reality and exacerbates the global rich-poor divide. Bioprospecting, however, describes the commercialization of indigenous medicines in a manner acceptable to the local populace. Challenges facing bioprospectors seeking to develop traditional medicines in a quality-controlled manner include a lack of skilled labor and high-tech infrastructure, adapting Northern R&D protocols to Southern settings, keeping products affordable for the local population, and managing the threat of biopiracy. The Malagasy Institute of Applied Research (IMRA) has employed bioprospecting to develop new health treatments for conditions such as diabetes and burns. Because of its integration of Western science and Malagasy cultural traditions, IMRA may provide a useful example for African and other organizations interested in bioprospecting. DISCUSSION: IMRA's approach to drug development and commercialization was adapted from the outset to Malagasy culture and Southern economic landscapes. It achieved a balance between employing Northern R&D practices and following local cultural norms through four guiding principles. First, IMRA's researchers understood and respected local practices, and sought to use rather than resist them. Second, IMRA engaged the local community early in the drug development process, and ensured that local people had a stake in its success. Third, IMRA actively collaborated with local and international partners to increase its credibility and research capacity. Fourth, IMRA obtained foreign research funds targeting the "diseases of civilization" to cross-fund the development of drugs for conditions that affect the Malagasy population. These principles are illustrated in the development of IMRA products like Madeglucyl, a treatment for diabetes management that was developed from a traditional remedy. SUMMARY: By combining local and international research interests, IMRA has been able to keep its treatments affordable for the Malagasy population. Our analysis of IMRA's history, strategy, and challenges suggests that other developing world institutions seeking to use bioprospecting to address issues of local access to medicines would be well-advised to treat traditional medical knowledge with respect and humility, share its benefits with the local community, and pursue strategic partnerships.
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 | 0,000 | 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 | 0,001 | 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 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 ».