With the recent expansion of precision medicine, predictive biomarkers will help illuminate new therapeutic pathways, especially in the field on oncology.

Predictive biomarkers in oncology can include a variety of factors ranging from activating oncogenic mutations and deletion of tumor suppressors, to complex changes in genes expression signatures and alterations in serum protein levels, all of which predict response to therapy.

Artificial intelligence, Deep Learning and related technologies promise to be a large part of the expansion of precision medicine given the exploding amount of predictive data.

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Meet Sabrina Bellisario, Head of Operations, Veri and Dr. Mark Gramling, Director - Oncology discussing how technology is helping them to bring precision medicine “back from the future” into today’s clinical research and drug development in this podcast in association with DIA.

Sabrina is the Director of Operations and responsible for overseeing daily operations for the Veri biomarker group and leading LARVOL View, an oncology social listening platform.

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“Our goal is to create a detailed real-time platform that could provide reliable insights on biomarkers and biomarker activity.”

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As Director of Oncology, Mark is leveraging his 15 years of experience in research, technology development, and healthcare industry to examine novel pathways ranging from the impact of coagulation factors on breast cancer to modulators of Ras and Myc signaling in lymphoma. He handles strategy, software development, text mining, natural language processing, data management and curation, at LARVOL.

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“Veri is really the sort of structural foundation upon which we're building a number of different solutions so we're trying to leverage that foundation that backbone of new solutions expected very soon in this space.”

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Listen to the speakers and discover some of the upcoming LARVOL applications:

Care – Coding to the level of patient profile to yield the applicable drug –potentially both clinical and patient level facing.

View – New level of the rocket for pharma, which is sentiment analysis that folds into the needs of MSLs for KOL tracking.

RXXO – Primarily physician facing, focusing right now in a very specific area of immune-oncology, and the key player drug Pembro to create based on outcomes data a predictive model based on patient profile.

Clin – multiple target audiences, from physician to research to the combinatorial interest of pharma to bring the total and history of clinical trial data under one space not just for outcomes but also adverse events, and other data and bring together like a google images proposition to find all.

VR – Perhaps not to a specific target audience, but a way for multiple audiences to view the data across cancer types beyond Boolean search terms, to find and select data in 3D/4D.

Chefs – For research purposes to predict new ventures in research.

To discover the first solution being described as the “Google for cancer”, try Veri today to explore the newest data platform for predictive biomarkers and drug response in oncology.

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Listen to the full podcast discussion below.

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About the Podcast Host, DIA

DIA is a global association that mobilizes life science professionals from across all areas of expertise to engage with patients, peers and thought leaders in a neutral environment on the issues of today and the possibilities for tomorrow.

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About LARVOL VERI

An innovative solution in the predictive biomarker space, Veri is an intuitive cancer biomarker database. The tool provides interactive visual analytics and insights on biomarkers and biomarker activity to help understand the landscape of predictive biomarkers across a wide array of tumor types and interventions. Additionally, Veri provides coverage of over 200+ clinical diagnostic tests, including companion and complimentary diagnostics. Try Veri today here.