A First-in-Human Study of ATM Inhibitor Lartesertib as Monotherapy in Patients with Advanced Solid Tumors
Bibliographic record
Abstract
PURPOSE: This first-in-human phase I, open-label study (NCT04882917) evaluated the safety, tolerability, pharmacokinetics (PK), pharmacodynamics (PD), and maximum tolerated dose (MTD) of the highly potent and selective oral ataxia-telangiectasia-mutated kinase inhibitor lartesertib. PATIENTS AND METHODS: Patients with advanced solid tumors received oral doses of lartesertib for a dose range of 100 to 400 mg once daily. Dose escalation was based on PK, PD, and safety data guided by a Bayesian two-parameter logistic regression model. Molecular responses were assessed in ctDNA samples. RESULTS: Twenty-two patients received lartesertib at doses of 100 mg (n = 2), 200 mg (n = 7), 300 mg (n = 9), and 400 mg (n = 4) once daily. Maculopapular rash was the most common dose-limiting toxicity (four events in four patients). The MTD was 300 mg once daily. The most common grade ≥3 treatment-emergent adverse event was anemia (four patients). Five patients experienced ≥1 treatment-related adverse events of grade ≥3 (including one grade 4 event of hypersensitivity). Exposure increased in a dose-related manner, with median time to maximum plasma concentration ranging from 1 to 2 hours and mean elimination half-life from 5 to 7 hours across the dose range. PD analysis showed a trend of reduction of γ-H2AX levels, with highest target inhibition of 80% to 100%. Best overall response was stable disease in two patients. Molecular responses were observed in four patients of 21 evaluable patients. CONCLUSIONS: Lartesertib achieved target exposure and engagement without significant hematological toxicity. Further clinical evaluation of lartesertib in combination therapy is ongoing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".