Proceedings of the biosimilars workshop at the International Symposium on Oncology Pharmacy Practice 2019
Bibliographic record
Abstract
The International Society of Oncology Pharmacy Practitioners organized a workshop to create learning opportunities on biosimilars in pharmacy practice on 10 October 2019. The topics that were covered included (i) the development and testing of biosimilars, (ii) the challenges of bringing biosimilars to market, and (iii) real-world data on patient safety and perceptions during biosimilar implementation. The development of biosimilars can take up to eight years and the extensiveness of the process depends on several factors, such as the complexity of the production process and regulatory requirements. Compared to generic products of small-molecule drugs, there is a higher barrier to market entry for biosimilars, explaining the small number of biosimilars in the market. Appraisal of biosimilars for inclusion in hospital formularies is also different from the review process of originator biologics, where the former is usually institution-led and has fewer restrictions on use. When several biosimilar products are available, factors that should be considered besides cost are licensed indications, supply chain confidence, clinical data, and product attributes. Real-world data have shown that biosimilars are well-tolerated and have safety data that are comparable to that of the originator product. Oncology pharmacists from the United Kingdom, Kenya, and Canada also presented their respective experiences with biosimilar use. Different countries at varying stages of biosimilar implementation faced distinct challenges. Nevertheless, resources to assist biosimilar implementation can potentially be shared between different regions. International Society of Oncology Pharmacy Practitioners is well-positioned to foster professional cooperation at an international level to drive biosimilar implementation.
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 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 | 0.004 | 0.009 |
| 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 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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 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".