Neladalkib (NVL-655), a highly selective anaplastic lymphoma kinase (ALK) inhibitor, compared to alectinib in first-line treatment of patients with ALK-positive advanced non-small cell lung cancer: The phase 3 ALKAZAR study.
Bibliographic record
Abstract
TPS8666 Background: Oncogenic ALK gene fusions are detected in ~5% of advanced non-small cell lung cancer (NSCLC) cases. Among these patients, the incidence of brain metastases at diagnosis is ~40%. Prior generations of ALK tyrosine kinase inhibitors (TKIs) present limitations that may influence efficacy and tolerability, such as inadequate control of brain metastases, treatment-emergent drug-resistant ALK mutations, or off-target adverse events, particularly neurological events associated with inhibition of the structurally related TRK kinases. Neladalkib is a potent, brain-penetrant, ALK-selective TKI with preclinical activity against diverse ALK fusions and resistance mutations (Lin et al., Cancer Discovery 2024). In the Phase 1/2 ALKOVE-1 study, neladalkib showed encouraging preliminary efficacy in patients with heavily pretreated ALK+ NSCLC, including in those with ALK single or compound resistance mutations and brain metastases (Drilon et al., ESMO 2024). It also exhibited a favorable safety profile consistent with its ALK-selective, TRK-sparing design. The Phase 3 ALKAZAR study aims to demonstrate the superiority of neladalkib over a current standard of care, alectinib, in TKI-naïve patients with advanced ALK+ NSCLC. Methods: ALKAZAR (NCT06765109) is a global, Phase 3, randomized, controlled, open-label study in adult patients with locally advanced or metastatic NSCLC harboring an ALK rearrangement per local testing of tissue or blood. Prior systemic anticancer treatment for metastatic disease is not allowed. Patients who received prior alectinib in the adjuvant setting are not eligible. Patients are required to have measurable disease by RECIST. Patients with untreated central nervous system (CNS) disease without progressive neurological symptoms or increasing corticosteroid doses are eligible. Patients with non-ALK oncogenic driver alterations are excluded. Approximately 450 patients will be randomized in a 1:1 ratio to receive either oral neladalkib (150 mg once daily) or oral alectinib (600 mg twice daily), stratified by brain metastases, ethnic origin (Asian vs. non-Asian), and Eastern Cooperative Oncology Group (ECOG) performance status (PS) score (0 vs.1 vs. 2). The primary endpoint is progression-free survival by blinded independent central review. Secondary endpoints include intracranial activity, objective response rate, duration of response, overall survival, safety and tolerability, and patient-reported outcomes. Additional analyses will be conducted to investigate candidate biomarkers and molecular mechanisms of response and resistance to neladalkib and alectinib. The study is open to accrual. Clinical trial information: NCT06765109 .
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".