Clinical translation of neuro-regenerative medicine in India: A study on barriers and enabling strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We present the findings of a study of barriers and enabling strategies to clinical translation of Neuro-Regenerative Medicine (Neuro-RM) technologies in India. Twenty-three people were included in this qualitative study, including researchers, clinicians, firm representatives and policy makers working in Neuro-RM. The study has identified barriers that may arise at each stage of translation and how these are being addressed. Understanding of the molecular and cellular basis of Neuro-RM is being supported through government investment in existing neuroscience centres and the creation of new centres with regenerative medicine expertise. Clinical trials benefit from the support of clinicians who partner with researchers in study design and data collection. Government agencies have developed guidelines to inform best practices in preclinical and clinical studies. Addressing the barriers to Neuro-RM translation identified in this study can be achieved through continued support for capacity building and priority setting in preclinical studies, international efforts to achieve clinical trial protocol standardization, and multidisciplinary collaborations between clinicians, researchers, government and industry.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 it