By Meg Flippin, Benzinga
Big data is transforming everything from the way we drive to the way we shop or even the way we consume energy. But when it comes to healthcare and fighting diseases, it still takes 10 or more years to bring a drug or treatment to market. Whats more, 90% of drugs in development fail. A big reason is that all the disparate data being collected from doctors, hospitals, clinical trials and patient outcomes reside in silos thus not functioning together, and that only seems poised to get worse. The volume of human molecular data is growing rapidly, but analytic capabilities arent keeping up. That is essentially slowing progress in finding potential cures and more effective treatments.
To overcome this challenge, a platform that can digest, organize and make sense of all the different data types and sources is needed and thats where CytoReason and its Disease Model Platform come in. Founded in 2016 to address this problem, CytoReason created what the company says is the first AI model to map treatments, patient groups and disease mechanisms while constantly evolving and learning.
Bringing It All Together
Researchers of all levels can rely on CytoReasons proprietary data and innovative technology to make data-driven decisions across the drug development life cycle. Scientists can identify potential targets, prioritize indications, and stratify patient populations. Program leaders can compare drugs across multiple diseases or multiple drugs within a single disease. C-level executives can gain valuable tools to manage and optimize entire drug portfolios.
Never before has there been that much data organized and analyzed on one platform, says CytoReason. Similar to how navigation apps provide layers of data about streets, buildings and addresses, CytoReason's Disease Model Platform offers layers of pre-computed data, which can include results from clinical trials, data on proteins and single-cell data. With multiple models for various diseases, users of the platform can identify potential targets, prioritize treatments, stratify patients and find possible drug combinations. User-generated data can also be integrated, and hypotheses across different treatments can be tested. The platform learns with you and can help you understand the cause of the disease and identify potential R&D avenues for prevention.
Giving Pharma An Edge
For drug development companies and researchers, CytoReason says the biggest advantage of its Disease Model Platform is its ability to compare assets across different diseases. With a single standard for all disease models, users can answer critical questions including which patients may benefit most from the drug, what other diseases the drug can be developed for, and how the drug stacks up against the drugs currently available. By answering those questions, decision-makers in pharma and biotech companies can find new opportunities, increase success rates and shorten the drug development cycle.
Sounds too good to be true? The platform is already being used by five of the top ten pharma companies including Sanofi SA (NASDAQ: SNY), Pfizer Inc. (NYSE: PFE).
Sanofi, which tapped CytoReasons AI platform for use in the field of inflammatory bowel disease (IBD) expanded its multiyear collaboration last year. Sanofi is using the platform to identify patient subtypes and pair them with IBD targets. Under the terms of the expanded agreement, Sanofi will pay CytoReason an undisclosed multimillion-dollar amount. Pfizer, which has been working with CytoReason since 2019, also extended its collaboration, announcing in 2022 that it committed a $20 million equity investment, has options to license CytoReasons platform and disease models and fund supplementary project support in a deal potentially worth up to $110 million over the next five years. Since the two began collaborating, Pfizer has used CytoReason's biological models in its research to enhance the understanding of the immune system as it develops innovative drugs for immune-mediated and immuno-oncology diseases. CytoReason's platform has provided Pfizer with multiple insights in its research and development programs across over 20 diseases.
CytoReasons platform has also benefited Poolbeg Pharma, which has been using it to find novel approaches for treating influenza. Poolbegs disease progression data from influenza human challenge trials combined with CytoReasons disease model platform led to the discovery of multiple novel drug targets for the treatment of influenza.
Big data is growing exponentially, particularly in the healthcare field, but getting it under one roof has proven difficult. It's the reason it takes so long to develop drugs and why the majority of them fail. Platforms like CytoReason are working to change that, providing AI-generated insights to understand disease mechanisms and disease progression, as well as potential treatment methods. In a world where data is endless, CytoReason is making sense of it all.
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