Abstract PR005: Helping academic investigators develop small molecules for the clinic: The NCI Developmental Therapeutics Program and Stepping-Stones
Bibliographic record
Abstract
Abstract Academic researchers working in small molecule drug discovery and development face unique challenges – key among these include limited access to the full range of resources needed, inadequate funding which does not cover costs for routine/iterative product development tasks, and unavailability of expertise for the full range of regulatory critical path steps required for an IND. For academic institutions which lack deep resources, specialized core facilities, or endowments, these challenges are even more dire. In recognition of these realities, the NCI Developmental Therapeutics Program (DTP) expanded its capability through creation of the Stepping-Stones program, which provides resources to academic-based researchers who are working towards advancing their small molecule therapeutic candidates from ‘bench to bedside’. Through the Stepping-Stones program, NCI grant-supported small molecule therapeutics focused projects demonstrating high productivity are eligible to obtain access to NCI/DTP drug development capabilities and resources to fill in ‘gaps’ for specific activities that are not covered through their existing funding, but which are necessary to facilitate advancement along the critical path. Examples of services provided have included molecular profiling for ADME/DMPK studies, screens for secondary pharmacology and in vitro safety, synthesis optimization and chemical synthesis, and formulation development, to name a few. By filling in such discrete ‘gaps’, project teams can ‘de-risk’ a candidate earlier and develop stronger data packages to better position themselves for attracting additional investment for development toward clinical testing, or as the data warrants pursue an earlier re-direction of effort before going too far down the critical path. An overview of Stepping-Stones including details for how to be considered for this program and its interactions with other programs at NCI that support drug discovery and development is described, in addition to an overview of DTP’s discovery and development services which usher R&D programs from discovery through preclinical development and IND-enabling studies to support first-in-human trials. From this presentation, academic based ‘drug hunters’ will obtain knowledge about the Stepping-Stones program as a support mechanism to enable their continued efforts and gain an improved understanding about the ‘ecosystem’ of drug discovery and development programs offered by the NCI for the extramural community of researchers. Citation Format: Sharad Verma, Morgan O' Hayre, Rose Aurigemma. Helping academic investigators develop small molecules for the clinic: The NCI Developmental Therapeutics Program and Stepping-Stones [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr PR005
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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 | 0.031 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.059 | 0.028 |
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".