Project Orbis: Global Collaborative Review Program
Bibliographic record
Abstract
Abstract In 2019, the FDA Oncology Center of Excellence launched Project Orbis, a global collaborative review program to facilitate faster patient access to innovative cancer therapies across multiple countries. Project Orbis aims for concurrent submission, review, and regulatory action for high-impact clinically significant marketing applications among the participating partner countries. Current Project Orbis partners (POP) include the regulatory health authorities (RHA) of Australia, Brazil, Canada, Singapore, and Switzerland. Project Orbis leverages the existing scientific and regulatory partnerships between the various RHA under mutual confidentiality agreements. While FDA serves as the primary coordinator for application selection and review, each country remains fully independent on their final regulatory decision. In the first year of Project Orbis (June 2019 to June 2020), a total of 60 oncology marketing applications were received, representing 16 unique projects, and resulting in 38 approvals. New molecular entities, also known as new active substances, comprised 28% of the received marketing applications. The median time gap between FDA and Orbis submission dates was 0.6 months with a range of −0.8 to 9.0 months. Across the program, the median time-to-approval was similar between FDA (4.2 months, range 0.9–6.9, N = 18) and the POP (4.4 months, range 1.7–6.8, N = 20). Participating countries have signified a strong commitment for continuation and growth of the program. Project Orbis expansion considerations include the addition of more countries and management of more complex applications.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.208 | 0.161 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.006 | 0.016 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.107 | 0.061 |
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 source (direct Gemma or distilled Codex), 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".