Therapy Areas: Vaccines
Neon Therapeutics Treats First Patient in Clinical Trial of NEO-PV-01 Cancer Vaccine in Combination with Keytruda and Chemotherapy
10 May 2018 - - Cambridge, Massachusetts-based immuno-oncology company Neon Therapeutics has treated the first patient in a clinical trial evaluating its proprietary personal neoantigen vaccine, NEO-PV-01, in combination with Merck's anti-PD-1 therapy, Keytruda (pembrolizumab), along with chemotherapy, the company said.
NEO-PV-01 is Neon Therapeutics' most advanced product candidate and is a personal cancer vaccine designed specifically for each patient based on DNA mutations from that patient's tumor.
This Phase 1b clinical trial, being conducted in collaboration with Merck, also known as MSD outside of the US and Canada, is designed to evaluate the safety, tolerability, and preliminary efficacy of NEO-PV-01 in combination with Keytruda and a chemotherapy regimen of pemetrexed and carboplatin in patients with untreated or advanced metastatic nonsquamous non-small cell lung cancer (NSCLC).
Additionally, the trial will assess neoantigen-specific immune responses in peripheral blood and tumor tissue, and other markers of immune response. This open-label clinical trial is anticipated to enroll a total of 15 patients, with possible expansion.
Enrolled patients will undergo an initial biopsy and receive treatment with chemotherapy and Keytruda. Neon Therapeutics will then manufacture a personal vaccine for each patient, based on an analysis of tumor neoantigen mutations. At week 12 of treatment, patients receive the NEO-PV-01 vaccine while continuing therapy with Keytruda.
Neon Therapeutics, a clinical-stage immuno-oncology company developing neoantigen-based therapeutics, is dedicated to transforming the treatment of cancer by directing the immune system towards neoantigens.
The company's proprietary neoantigen platform uses two distinct approaches. In Neon/One, these neoantigens are specific to each individual. In Neon/Select, these neoantigens are shared across subsets of patients and tumor types.
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