Opportunities and Challenges for the Cellular Immunotherapy Sector: A Global Landscape of Clinical Trials
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
Global investments in cellular immunotherapies reflect their curative potential. Our landscape of clinical trials will aid developers, investors, adopters and payers in planning for adoption and implementation along realistic time horizons. Trend data enable stakeholders to adapt their business models and capacity to bring immunotherapies to the clinic. For cancer, trends suggest a shift from cancer vaccines to adoptive cellular transfer, alongside a focus on solid tumors. Academic centers, mainly in the USA, lead in early-phase clinical trials and target identification; but industry involvement has increased fourfold over the past two decades. Trends indicate an increasingly personalized approach to onco-immunology, which raises challenges for cost-effective manufacturing and delivery models. Overcoming these challenges provides opportunities for innovative biotechnology firms.
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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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