Abstract 4457: Open science medicinal chemistry: Towards a treatment for DIPG
Bibliographic record
Abstract
Abstract Meds4Kids Pharma (M4K)1 is pioneering an open science approach to drug discovery, focussed on the discovery and development of small molecule therapeutics for orphan paediatric cancers. M4K seeks to test the hypothesis that an open science framework can be successfully applied not only to accelerate basic science, using the collective knowledge of the scientific community at large, but also to take an innovative new drug candidate all the way from discovery and clinical proof-of-concept through to product registration, by making use of regulatory data protections and market incentives. Since late 2017, Charles River Early Discovery has been providing in kind drug discovery services to help progress these efforts, including medicinal and synthetic chemistry. The first M4K project aims to generate an orally-available, brain-penetrant therapeutic to treat the diffuse intrinsic pontine glioma (DIPG). DIPG is a rare, aggressive and uniformly fatal childhood brain cancer with a median survival time of 9-12 months and for which there are currently no effective drug treatments. The disease has been shown to be associated with mutations in the ACVR1 gene (activin A receptor, type 1) also known as ALK2 kinase. Early support for the therapeutic hypothesis that an inhibitor of ALK2 kinase would have clinical benefit in DIPG, came from in vivo studies with non-selective ALK2 kinase inhibitors, which both killed DIPG cell lines harbouring the ALK2 mutation and extended lifespan in xenograft mouse models.2 Working collaboratively with M4K and their open science partners, we have made excellent progress towards the identification of potent, selective, brain penetrant ALK2 inhibitors starting from the known inhibitor LDN-214117, previously described for FOP (fibrodysplasia ossificans progressiva).3 Our current lead compound has an excellent in vitro and in vivo profile showing high oral bioavailability and brain penetration in a mouse PK study and is progressing to proof of concept studies. In addition we are progressing with the identification of a back-up series. References: 1. https://m4kpharma.com/ 2. Carvalho et. al. Neuro-Oncology, Volume 18, Issue suppl_6, 1 November 2016, Pages vi154, https://doi.org/10.1093/neuonc/now212.639 3. Mohedas et. al., J. Med Chem, 2014, 57 (19), 7900 Citation Format: Sue Cramp, Nicole Hamblin, Jeff O'Meara, Aled Edwards, Owen Roberts, Alex Bullock, Paul Brennan. Open science medicinal chemistry: Towards a treatment for DIPG [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4457.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".