Vysioneer Announces Data Sharing Agreement with Pfizer to Augment Oncology Clinical Trials with Artificial Intelligence
Agreement centered around the use of artificial intelligence (AI) to advance cancer drug efficacy assessment.
Vysioneer, a pioneer in AI for Oncology,announced a data sharing agreement with Pfizer, a global leader in pharmaceuticals. The agreement aims to lay the foundation for the application of AI in oncology clinical trials. Vysioneer’s AI technology provides objective tumor response assessments and unlocks novel biomarkers that cannot be derived by human readers due to time and resources constraints, to predict patient outcomes at earliest timepoints.
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As part of the agreement, Vysioneer gains access to one of Pfizer’s oncology clinical trial datasets to apply Vysioneer’s advanced machine learning techniques to facilitate the drug efficacy assessment process, thereby allowing Pfizer to assess drug efficacy with greater granularity and explore advanced biomarkers and novel endpoints.
The current standard to measure how well a cancer patient responds to treatment, such as response evaluation criteria in solid tumors (RECIST) is labor-intensive and prone to intra- and inter-reader variability by human readers. The use of AI has the potential to markedly improve clinical trial image reading processes as well as enhance the ability to provide more granular insights down to every single tumor. Through successful use of this valuable technology, Vysioneer and Pfizer hope it will lead to expanded clinical trial use cases, and ultimately, better patient care.
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“We are thrilled to collaborate with Pfizer on this data sharing agreement. Pfizer has continually led the biopharma industry into the next wave of innovation, and we look forward to offering our AI technology to support their efforts,” said Jen-Tang Lu, Chief Executive Officer of Vysioneer. “By objectively assessing drug efficacy on a large scale and uncovering new endpoints that more accurately reflect patient outcomes, we have a strong opportunity to significantly de-risk clinical trials and ensure that cancer patients receive the right treatment promptly.”
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