Biomarker Endpoints:
accelerate time to results.

Motivated by advancing the pace of therapeutic development, Ozette Endpoints is a cloud-native, clinical trial accelerator that delivers near real-time automated biomarker endpoint analysis for flow cytometry data.

Our platform has been specifically engineered to produce results at speed with no limitation on the number of endpoints stemming from your high dimensional data. We support interim analysis during ongoing studies and quality assurance throughout the engagement.

Human expertise combined with
purpose built computational methods.

Each engagement includes an Ozette domain expert that helps shepherd your flow cytometry data through our platform. We first establish an analysis pipeline using your flow cytometry panel, data, pre-defined endpoints and gating sequences to create a reproducible analysis pipeline. Then we apply this analysis pipeline to your clinical trial data as it becomes available, delivering results in days not months.

Initialization

Quickly capture study information to pre-define endpoints, access raw single cell flow cytometry data, and study metadata. You may also set up a reproducible endpoints pipeline for your clinical flow assay.

Study monitoring

You may leverage your custom analysis pipeline for process study data gathered from your clinical trials.

Gain insights without limits.

Results are available via interactive results pages that allows teams to review, flag and approve preprocessing gates as well as the pre-defined cytometry endpoint gates. Upon approval of the results, teams are able to download/export images from the analysis in addition to a .csv of the summary data for later, additional analysis.

There are no technical limitations on the number of endpoints, the volume of data, the number of analyses or the study timeline.

A higher standard.

The Ozette platform is supported by a robust quality management system (QMS) that meets or exceeds applicable guidelines and regulatory requirements.

View our latest case studies.

Case Study

Going beneath the
surface of skin cancer.

We investigated our AI’s ability to predict treatment response to PD1 inhibiting immunotherapy in Merkel cell carcinoma and melanoma. We benchmarked our algorithmic approach against conventional analysis.

Case Study

Ozette’s AI aids advancement of cancer drug development.

Ozette’s technology, in conjunction with other new methods, reveal a distinct T cell population that suppresses immune effectiveness in the tumor microenvironment and helps inform drug development in immuno-oncology.