Abstract 2503: Rational design of small-molecule immune checkpoints' inhibitors
Bibliographic record
Abstract
Abstract Blocking the PD-1/PD-L1 and CTLA-4 pathways recently emerged as a ‘game changer' in cancer immunotherapy, leading to the selection of monoclonal-antibodies (MABs) targeting PD-1 as ‘drug of the year' for 2013. Although these antibodies restored exhausted T cells' function to recognize and kill tumor cells, these MABs have numerous disadvantages. These include their very high cost and very severe side effects. Our team has been focused on designing small molecule inhibitors for this pathway. Compared to available MAB therapies, our small molecules may offer a more affordable, more easily administered and better controlled treatment for a variety of cancers. Here, we demonstrate our efforts toward this goal and summarize our data on our promising compounds targeting the PD-1/PD-L1 and CTLA-4 pathways. Citation Format: Khaled Barakat. Rational design of small-molecule immune checkpoints' inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2503.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".