Phase I Study of ONT-380, a HER2 Inhibitor, in Patients with HER2+-Advanced Solid Tumors, with an Expansion Cohort in HER2+ Metastatic Breast Cancer (MBC)
Bibliographic record
Abstract
Abstract Purpose: ONT-380 (ARRY-380) is a potent and selective oral HER2 inhibitor. This Phase I study determined the MTD, pharmacokinetics (PK) and antitumor activity of ONT-380 in HER2-positive advanced solid tumors, with an expansion cohort of patients with HER2+ MBC. Experimental Design: ONT-380 was administered twice daily (BID) in continuous 28-day cycles. After a modified 3+3 dose-escalation design determined the MTD, the expansion cohort was enrolled. PK properties of ONT-380 and a metabolite were determined. Response was evaluated by Response Evaluation Criteria in Solid Tumors (RECIST). Results: Fifty patients received ONT-380 (escalation = 33; expansion = 17); 43 patients had HER2+ MBC. Median prior anticancer regimens = 5. Dose-limiting toxicities of increased transaminases occurred at 800 mg BID, thus 600 mg BID was the MTD. Common AEs were usually Grade 1/2 in severity and included nausea (56%), diarrhea (52%), fatigue (50%), vomiting (40%) constipation, pain in extremity and cough (20% each). 5 patients (19%) treated at MTD had grade 3 AEs (increased transaminases, rash, night sweats, anemia, and hypokalemia). The half-life of ONT-380 was 5.38 hours and increases in exposure were approximately dose proportional. In evaluable HER2+ MBC (n = 22) treated at doses ≥ MTD, the response rate was 14% [all partial response (PR)] and the clinical benefit rate (PR + stable disease ≥ 24 weeks) was 27%. Conclusions: ONT-380 had a lower incidence and severity of diarrhea and rash than that typically associated with current dual HER2/EGFR inhibitors and showed notable antitumor activity in heavily pretreated HER2+ MBC patients, supporting its continued development. Clin Cancer Res; 23(14); 3529–36. ©2017 AACR.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".