Commercialization of Regenerative Medicine: Learning from Spin-Outs
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
Abstract The meeting "Commercialization of Your Regenerative Medicine Research: Lessons from Spin Out Successes" was hosted by the Oxbridge Biotech Roundtable (OBR) (Oxford, UK) at the University of Oxford in February, 2013, and attracted a multi-stakeholder audience spanning academia and industry. The event featured case studies from Gregg Sando, CEO, Cell Medica (London, UK), John Sinden, CSO, Reneuron (Guilford, UK), and Paul Kemp, CEO and CSO, Intercytex (Manchester, UK). OBR is a student-led initiative with over 7000 members across eight different UK and US locations with a mission to foster a conversation about the healthcare and life sciences industry. Here we review the main themes of the meeting and the major questions facing the regenerative medicine industry and its rapidly emerging subsets of cellular and gene therapies. Notably, we discuss the compatibility of regenerative therapies to the existing healthcare infrastructure, biomanufacturing challenges (including scalability and comparability), and the amenability of regenerative therapies to existing reimbursement and investment models. Furthermore, we reiterate key words of advice from seasoned industry leaders intended to accelerate the translation path from lab bench to the marketplace.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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