A Proof-of-Concept Evaluation of JTPc and Tp-Tec as Proarrhythmia Biomarkers in Preclinical Species: A Retrospective Analysis by an HESI-Sponsored Consortium
Bibliographic record
Abstract
Introduction: Based on the ICH S7B and E14 guidance documents, QT interval (QTc) is used as the primary in vivo biomarker to assess the risk of drug-induced torsades de pointes (TdP). Clinical and nonclinical data suggest that drugs that prolong the corrected QTc with balanced multiple ion channel inhibition (most importantly the l-type calcium, Cav1.2, and persistent or late inward sodium current, Nav1.5, in addition to human Ether-à-go-go-Related Gene [hERG] I Kr or Kv11.1) may have limited proarrhythmic liability. The heart rate-corrected J to T-peak (JTpc) measurement in particular may be considered to discriminate selective hERG blockers from multi-ion channel blockers. Methods: Telemetry data from Beagle dogs given dofetilide (0.3 mg/kg), sotalol (32 mg/kg), and verapamil (30 mg/kg) orally and Cynomolgus monkeys given medetomidine (0.4 mg/kg) orally were retrospectively analyzed for effects on QTca, JTpca, and T-peak to T-end covariate adjusted (Tpeca) interval using individual rate correction and super intervals (calculated from 0-6, 6-12, 12-18, and 18-24 hours postdose). Results: Dofetilide and cisapride (I Kr or Kv11.1 blockers) were associated with significant increases in QTca and JTpca, while sotalol was associated with significant increases in QTca, JTpca, and Tpeca. Verapamil (a Kv11.1 and Cav1.2 blocker) resulted in a reduction in QTca and JTpca, however, and increased Tpeca. Medetomidine was associated with a reduction in Tpeca and increase in JTpca. Discussion: Results from this limited retrospective electrocardiogram analysis suggest that JTpca and Tpeca may discriminate selective I Kr blockers and multichannel blockers and could be considered in the context of an integrated comprehensive proarrhythmic risk assessment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".