Abstracts from the 8th International Conference on cGMP Generators, Effectors and Therapeutic Implications
Bibliographic record
Abstract
The nitric oxide (NO)-soluble guanylate cyclase (sGC)-cyclic guanosine monophosphate (cGMP) signalling pathway plays a fundamental role in modulating diverse physiological processes including blood flow, fibrosis, inflammation, and metabolism. sGC stimulators are small-molecule, heme-dependent agonists of sGC that synergize with and enhance endogenous NO signaling. As such, sGC stimulators may provide therapeutic benefits both in diseases associated with impaired NO signaling and in diseases where stimulation of this pathway will restore functional homeostasis. Data from our recent preclinical studies add to the growing body of evidence that sGC stimulators have direct effects on systemic and vascular inflammation, fibrosis, and metabolism. Ironwood is developing IW-1973 and IW-1701 as oral, once-daily sGC stimulators for both cardiovascular and non-cardiovascular systemic disease indications. Phase 1 studies in healthy human subjects demonstrated clear evidence of target engagement, attractive pharmacokinetic properties, and predicted hemodynamic effects, at well-tolerated doses. Phase 2 studies are currently ongoing in patients with achalasia, an esophageal motility disorder, and in patients with diabetes and hypertension. Preclinical characterization of IW-1973 and IW-1701 support the broad therapeutic potential and multi-faceted pharmacology of these compounds. Based on preclinical studies, IW-1973 has extensive distribution into organs including liver, heart, kidney, and lung, which may maximize effects on target organs while limiting systemic hemodynamic effects. The pharmacokinetic profile of IW-1701 has a narrow peak-to-trough ratio, which may provide more consistent pharmacological effect throughout the dosing interval. Ironwood is also developing IW-6463, a novel, CNS-penetrant sGC stimulator that shows target engagement and effects on regional blood flow in the brain. Preclinical data suggest that IW-6463 may be useful in treating CNS disorders including vascular dementia and Alzheimer's disease. We believe that sGC stimulation, alone or in combination with other mechanisms, may afford therapeutic benefit in multiple diseases. Furthermore, there may be an opportunity to provide targeted treatments by selecting compounds that are well-suited for specific diseases based on pharmacological profile, tissue distribution, pharmacokinetics, and route of administration.
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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) | 0.000 | 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".