Abstract
Purpose
Copanlisib, a pan-PI3K inhibitor, has previously shown clinical efficacy and a tolerable safety profile in patients with indolent non-Hodgkin lymphoma. However, the pharmacokinetics, safety, tolerability, and efficacy of copanlisib in Chinese patients have not been reported.
Methods
This was a single-arm, open-label, phase I study of copanlisib in Chinese patients with relapsed or refractory indolent non-Hodgkin lymphoma (iNHL). Patients received a single intravenous 60 mg infusion of copanlisib over 1 h on days 1, 8, and 15 of a 28-day cycle, with 1 week of rest. Safety was monitored throughout the study, and plasma copanlisib levels were measured for pharmacokinetic analysis. Tumor response was determined by independent central radiologic review.
Results
Sixteen patients were enrolled and 13 were treated with 60 mg of copanlisib for a median of 15.0 weeks. With a Cmax of 566 μg/L and a AUC (0–24) of 1880 μg·h/L following single intravenous infusion, the pharmacokinetic parameters of copanlisib were consistent with that in previous studies, and no accumulation in plasma was observed. Treatment-emergent adverse events were reported for all 13 patients, the most common of which were hyperglycemia (100.0%), hypertension (76.9%), decreased neutrophil count (76.9%), and decreased white blood cell count (69.2%). Seven out of 12 evaluated patients achieved partial response, resulting in an overall response rate of 58.3%
Conclusions
Copanlisib was well tolerated in Chinese patients with relapsed or refractory iNHL at the dose of 60 mg and demonstrated encouraging disease control, thus warranting further clinical investigation.
Clinical trial registration number
NCT03498430 (April 13, 2018).
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Acknowledgements
The authors would like to thank the patients, their families, and all investigators involved in this study. The trial was supported by Bayer Healthcare. Aurexel Life Sciences Ltd. (www.aurexel.com) is acknowledged for editorial support funded by Bayer AG. We also thank Camille Granvil and Joachim Grevel for their contributions to data analyses.
