Amplion’s Machine Learning Platform Accelerates Precision Medicine Collaboration

BEND, Ore., Oct. 16, 2019 /PRNewswire/ — Amplion, a leading precision medicine intelligence company, has released Dx:Revenue, a groundbreaking software solution that enables test providers to identify ideal pharmaceutical partnership opportunities at the right time to advance precision medicine collaboration.

Dx: Revenue is an extension of Amplion’s core business intelligence platform that leverages proprietary machine learning to deliver tailored insights into pharma and test developer activities. The platform draws from more than 34 million evidence sources such as clinical trials, scientific publications, conference abstracts, FDA cleared and approved tests, lab developed tests, diagnostic and drug pipelines and more in real time, producing prioritized and timely partnering opportunities that are a precise match between a test provider’s capabilities and pharma’s specific needs.

“Precision medicine has a problem,” says Chris Capdevila, CEO, Amplion. “There is an insurmountable volume of information with the potential to drive the realization of precision medicine for patients, but accessing that information strategically, effectively and quickly to make the best pharma partnering decisions is beyond human scale. Our company was founded to address this issue by providing critical evidence-based intelligence that supports the strategic decisions pharmaceutical and test developers need to make to be successful.”

The rise of precision medicine, an approach to patient care that allows a doctor to select a therapy most likely to succeed based on the underlying biological drivers of a patient’s disease, has drastically improved health outcomes in recent years but has also ushered in a new set of challenges. Prior to Amplion’s launch, drug and test developers creating new treatments were forced to comb through millions of uncategorized publications and other sources in search of relevant drug and clinical development and biomarker activity, a time-consuming effort that often comes up with non-relevant findings. 

Amplion solves this problem by applying sophisticated machine learning models to the entire biomedical landscape to identify those opportunities that precisely match test developers’ capabilities and needs. Amplion’s proprietary models understand the context within which a medical term is being used, for example, whether a specific biomarker is actually being measured within a study or simply being mentioned, with a high degree of accuracy. This allows drug and test developers to efficiently identify research and development initiatives and find relevant partners aligned to their program goals. 

“Precision medicine holds the promise of driving down drug development costs through shorter, more successful trials and reducing time to market for valuable drugs,” says Will Szczerbiak, Principal at Greycroft, “As investors, we believe in Amplion’s potential to reduce inefficiency in the critical partnering phases and add real value to the industry.”

The release of Amplion’s Dx:Revenue product comes just months after the company received new funding from Greycroft, Revolution’s Rise of the Rest Seed Fund and Imagen Capital Partners. In the coming months, the company plans to release a number of additional solutions on top of its core intelligence platform targeting additional organizational roles with critical insights.

About Amplion
Amplion is a business intelligence platform company leveraging proprietary machine learning and biomedical domain expertise to help accelerate precision medicine. By harnessing the world’s largest and fastest-growing corpus of biomedical evidence, the company’s solutions deliver timely, targeted, and actionable insights to enable confident, strategic decisions in drug and diagnostic development. Amplion has established trusted partnerships with leaders in precision medicine that leverage the platform to discover new opportunities and realize strategic objectives. Learn more at Amplion.com.

 

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SOURCE Amplion

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