New sources of drugs for hematologic malignancies
Bibliographic record
Abstract
Advancing novel therapeutic agents for the treatment of malignancy into the marketplace is an increasingly costly and lengthy process. As such, new strategies for drug discovery are needed. Drug repurposing represents an opportunity to rapidly advance new therapeutic strategies into clinical trials at a relatively low cost. Known on-patent or off-patent drugs with unrecognized anticancer activity can be rapidly advanced into clinical testing for this new indication by leveraging their known pharmacology, pharmacokinetics, and toxicology. Using this approach, academic groups can participate in the drug discovery field and smaller biotechnology companies can "de-risk" early-stage drug discovery projects. Here, several scientific approaches used to identify drug repurposing opportunities are highlighted, with a focus on hematologic malignancies. In addition, a discussion of the regulatory issues that are unique to drug repurposing and how they impact developing old drugs for new indications is included. Finally, the mechanisms to enhance drug repurposing through increased collaborations between academia, industry, and nonprofit charitable organizations are discussed.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".