Turning science into health solutions: KEMRI’s challenges as Kenya’s health product pathfinder
Notice bibliographique
Résumé
BACKGROUND: A traditional pathway for developing new health products begins with public research institutes generating new knowledge, and ends with the private sector translating this knowledge into new ventures. But while public research institutes are key drivers of basic research in sub-Saharan Africa, the private sector is inadequately prepared to commercialize ideas that emerge from these institutes, resulting in these institutes taking on the role of product development themselves to alleviate the local disease burden. In this article, the case study method is used to analyze the experience of one such public research institute: the Kenya Medical Research Institute (KEMRI). DISCUSSION: Our analysis indicates that KEMRI's product development efforts began modestly, and a manufacturing facility was constructed with a strategy for the facility's product output which was not very successful. The intended products, HIV and Hepatitis B diagnostic kits, had a short product life cycle, and an abrupt change in regulatory requirements left KEMRI with an inactive facility. These problems were the result of poor innovation management capacity, variability in domestic markets, lack of capital to scale up technologies, and an institutional culture that lacked innovation as a priority.However, KEMRI appears to have adapted by diversifying its product line to mitigate risk and ensure continued use of its manufacturing facility. It adopted an open innovation business model which linked it with investors, research partnerships, licensing opportunities, and revenue from contract manufacturing. Other activities that KEMRI has put in place over several years to enhance product development include the establishment of a marketing division, development of an institutional IP policy, and training of its scientists on innovation management. SUMMARY: KEMRI faced many challenges in its attempt at health product development, including shifting markets, lack of infrastructure, inadequate financing, and weak human capital with respect to innovation. However, it overcame them through diversification, partnerships and changes in culture. The findings could have implications for other research institutes in Sub-Saharan Africa seeking to develop health products. Such institutes must analyze potential demand and uptake, yet be prepared to face the unexpected and develop appropriate risk-mitigating strategies.
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 | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 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 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 ».