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Unlocking the Power of Cancer Databases

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LARVOL is a SaaS business intelligence company with a mission to improve human health. The team is driven by the possibility of facilitating discoveries that impact cancer carediscoveries that otherwise may have been missed.

An interview with LARVOL’s Sabrina Bellisario, head of operations, and Dr. Mark Gramling, director of oncology, helps provide insights into the importance of precision medicine databases and how LARVOL is providing access to the information pharma and biotech companies need as they develop cancer treatments.

How is LARVOL bringing the latest in pre-clinical and clinical trials into focus?

Mark Gramling (MG):
We’re currently working with two key sets of data that are critical to cancer research and drug development.

The first is biomarker data.

LARVOL’s database, 
VERI, occupies a specific functional space for biopharma companies, providing focused information on predictive biomarkers for oncology drugs, including modern targeted therapies. VERI's core focus is helping users understand whether a given biomarker influences response to a drug. Specifically, does it predict sensitivity or resistance to that therapy of interest? This information is valuable for assessing genomic alterations in everything from cell lines to FDA-approved therapies.

This information has many potential applications in today’s drug development landscape. One example is in the design of clinical trials. With an easy search of the VERI database, biopharma companies can learn which biomarkers may influence treatment response, based on insights ranging from news sources to scientific conference abstracts.

The second key data set we’re dealing with also surrounds clinical trials in oncology.

For years, drug development teams have tried to piece together a complete picture of the clinical trial landscape in oncology from disparate data sources. ClinicalTrials.gov set out to be a central source of information but has simply not been able to fulfil that promise.

CLIN, we’re picking up where ClinicalTrials.gov left off. Our expert team is pulling trial details from every available data source – publications, conferences, and other data releases – and putting them in front of biopharma teams in a format they can use. On top of that, we’re adding color and context by sharing the reactions of verified oncologists on Twitter to each clinical trial. We are further digitizing public outcomes data for easy access to trial comparisons and enabling meta-analysis. This is proving to be a powerful combination for drug and trial development teams.

How does LARVOL oncology data help biopharma companies stay competitive?

Sabrina Bellisario (SB):
For biopharma companies, commercial success is not just about drug approvals. To stay competitive, they need up-to-date information on trends and activity in the field. As drugs advance in the development pipeline, accurate competitive intelligence becomes more and more important, especially in the design of clinical trials.

Both VERI and CLIN present complex competitive intelligence in a streamlined, actionable format.

CLIN allows those involved in clinical trial protocol design to focus in on the key areas of optimization and refinement. By easily accessing all available data on similar trials, these teams can understand the relevancy of their trial to the marketplace and compare both structured and unstructured data. The result is a real strategic advantage: an accurate picture of the landscape they are attempting to enter.

VERI helps these companies look even deeper into the predictive biomarker data, and perhaps further into the future of treatment possibilities. If a biomarker confers resistance to the therapy, then the individuals expressing the gene, alteration, or fusion can be excluded from the trial. If a biomarker increases sensitivity to a drug, that patient population may be the focus. This is the foundation of the VERI database – but it’s just the beginning. The next step is to encourage novel approaches for analyzing and visualizing biomarkers and therapies.

How is technology amplifying what LARVOL can do?

LARVOL data solutions employ a combination of natural-language processing technology, manual curation by experts, and the beginnings of new approaches like data visualization and artificial intelligence. Together, these technologies help LARVOL deliver reliable competitive intelligence that biopharma companies can use to find strategic, actionable insights. 

A great example of this is found in the interactive Kaplan Meier Curves and Forest Plots in CLIN. Here, we are employing new technologies to present data in novel and actionable ways. Our team is re-digitizing KM curves and Forest plots enabling quick cross-comparison of outcomes from separate trials and sub-groups within trials. Digitized outcomes data for overall and progression free survival creates a quick tool for oncologists or a foundation for a meta-analysis for physicians and research scientists. 

LARVOL’s CLIN database allows pharma teams and researchers to compare multiple re-digitized Kaplan-Meier curves from across published clinical trial data.

What’s next for LARVOL?

LARVOL is determined to develop the most complete knowledgebase of cancer data available, combining the efforts of CLIN and VERI we’ve been discussing. We’re also exploring additional avenues from social networking in the cancer community to 3D modeling of biomarker data.

With the acceleration of precision medicine there is a growing wealth of both patient data and public data on targeted therapeutics and biomarkers in oncology. For public data in oncology, there is a new opportunity to combine technology and curation to make this data accessible, findable, and comparable in an easy-to-use software interface. At LARVOL, we endeavor to bring the wealth of public oncology data in precision medicine to you directly.