Turning science into health solutions: KEMRI’s challenges as Kenya’s health product pathfinder
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".