SOPHiA GENETICS and The French Kidney Cancer Research Network (UroCCR) Publish Results from Multiyear Collaboration

Rhea-AI Summary

SOPHiA GENETICS and UroCCR collaborate on a study using a multimodal algorithm to predict post-operative outcomes for renal cell carcinoma patients. The AI model outperformed usual prognostic scores, showing the potential of AI in cancer research.

Positive

• Collaboration between SOPHiA GENETICS and UroCCR on a study using a multimodal algorithm for renal cell carcinoma patients.
• AI model co-constructed by SOPHiA GENETICS and UroCCR provided strong predictions for post-operative outcomes.
• Results published in npj Precision Oncology showed AI model outperformed common risk scores.
• UroCCR database with data from over 3,300 patients utilized for the study.
• SOPHiA GENETICS' AI technology analyzed data to provide reliable predictions.
• Study demonstrates the potential of AI to support clinical treatment decision-making in kidney cancer patients.

Negative

• None.

Insights

Medical Research Analyst

The study's implications for precision medicine and oncology are significant. By leveraging AI, clinicians can potentially refine their prognostic capabilities, which is essential for tailoring patient care. The AI model's ability to outperform common risk scores suggests that it could lead to more accurate predictions of post-operative outcomes for renal cell carcinoma patients. This could translate into better treatment plans and potentially improved survival rates.

Moreover, the use of real-world data is a burgeoning trend in medical research, as it reflects a broader patient population and everyday clinical practice. The collaboration between SOPHiA GENETICS and UroCCR highlights the potential for AI to harness this type of data, which may lead to more generalizable and robust findings compared to those derived from more controlled but less representative clinical trial settings.

From a business perspective, the adoption of such AI models could position SOPHiA GENETICS favorably in the precision medicine market. The company's ability to integrate multimodal data and provide actionable insights could attract partnerships with healthcare providers and research institutions, potentially leading to increased market share and revenue growth.

Oncology Doctor

The study's findings are promising for the field of oncology, particularly in the management of kidney cancer. As a clinician, the prospect of an AI tool that offers superior predictive capabilities is exciting. It means we could better identify patients at higher risk of disease progression post-surgery and adjust our surveillance or treatment strategies accordingly. This is particularly relevant for renal cell carcinoma, where treatment decisions post-surgery can significantly impact patient outcomes.

Furthermore, the ability of the AI model to analyze complex multimodal data is a step forward in advancing personalized medicine. It underscores the potential of AI to synthesize vast amounts of data—from radiological images to clinical and biological markers—into a coherent predictive tool that can inform clinical decision-making. This could lead to more nuanced and individualized patient care, potentially improving quality of life and outcomes.

Healthcare Technology Market Analyst

The collaboration between SOPHiA GENETICS and UroCCR is a noteworthy development within the healthcare technology sector. The demonstrated predictive benefit of AI in cancer research could spur further investment and innovation in the field. As healthcare continues to move towards data-driven approaches, companies that can provide sophisticated analytics and real-world evidence will likely be at a competitive advantage.

From a market perspective, this study may signal a growing demand for AI-driven precision medicine solutions. As healthcare providers seek to improve patient outcomes while managing costs, tools that can provide accurate predictions and guide treatment decisions will be increasingly valuable. SOPHiA GENETICS' success in this study could lead to greater adoption of their platform, influencing the company's stock performance as investors recognize the potential for growth in this area.

New Multimodal Algorithm Highlights Predictive Benefit Of Artificial Intelligence (AI) for Cancer Research

BOSTON and ROLLE, Switzerland, March 15, 2024 /PRNewswire/ -- SOPHiA GENETICS (Nasdaq: SOPH), a cloud-native software company and a leader in data-driven medicine, and the French Kidney Cancer Research Network (UroCCR) collaborated on a study using a multimodal algorithm to help predict post-operative outcomes for those facing renal cell carcinoma (RCC), with the results recently published in npj Precision Oncology. The findings of the study showed the artificial intelligence (AI) model co-constructed by SOPHiA GENETICS and UroCCR provided a strong prediction for post-operative outcomes when compared to usual prognostic scores. This publication follows a prior collaboration that demonstrated the value of multimodal analysis on pre-operative kidney cancer upstaging.

UroCCR is one of the world's largest collaborative kidney cancer networks with 51 multidisciplinary clinical teams across France. In close relationship with the French Association of Urology (AFU), the goal of UroCCR is to connect a national, multidisciplinary network of medical and scientific professionals who focus on therapeutic management and applied research into kidney cancer. In 2021, UroCCR partnered with SOPHiA GENETICS to develop an AI-based model to predict whether kidney cancer will progress from a localized tumor after surgery.

The UroCCR database provided multimodal, real-world data, including radiological, clinical, and biological data from more than 3,300 patients across France operated between May 2000 and January 2020. Researchers applied SOPHiA GENETICS' proprietary AI offering to analyze the data into easily visualized, reliable predictions that were measured against, and outperformed most common risk scores.

"The volume and complexity of available health data continues to increase, and while this can assist in personalized diagnostics and treatment, it is most effective when paired with AI," said Thierry Colin, VP, Multimodal Research and Development, SOPHiA GENETICS. "Our work with UroCCR over the last three years has significantly advanced its research of RCC and shown the power of AI to provide insights from real-world multimodal data. We are extremely pleased with the findings from this study and look forward to continued collaboration with UroCCR." 

SOPHiA GENETICS' technology and global decentralized network are designed to break data silos and empower researchers with data-driven insights to drive the use of precision medicine. The study from UroCCR and SOPHiA GENETICS shows that an AI-based prediction model has the potential to support clinical treatment decision-making and provide an indication of which patients may potentially benefit from adjuvant systemic therapy, versus those that can sustain with surveillance.

"At UroCCR, our research is centered on the idea that a shared database helps facilitate and expand the use of precision medicine for patients facing kidney cancer," said Pr Jean-Christophe Bernhard, M.D., PhD., Urologic Surgeon at CHU Bordeaux and head of the UroCCR. "Our work with SOPHiA GENETICS and the results of our latest study demonstrated the benefits of using AI to analyze real-world multimodal data. SOPHiA GENETICS' technology and network have been key to the success of our research and will be imperative as we continue progressing with increased data inputs."

UroCCR was created in 2011 and was funded and labeled by the French National Cancer Institute (INCa) as one of the fourteen official nationwide clinical and biological databases (BCB). The network makes it possible to identify and document clinical, biological, and radiological data – in a shared database – for all newly diagnosed patients in participating centers. The network has been referenced in 2023 by the High Authority on Health (HAS) as real-life data provider of interest. For more information connect on X and LinkedIn.

The SOPHiA DDM™ Platform has the ability to analyze multimodal data due to its cloud-based AI-driven environment that integrates and standardizes diverse data modalities to fuel the development of predictive models capable of addressing research questions. For more information on the collaboration between SOPHiA GENETICS and UroCCR, visit SOPHiAGENETICS.com and UroCCR.fr. 

About SOPHiA GENETICS 
SOPHiA GENETICS (Nasdaq: SOPH) is a software company dedicated to establishing the practice of data-driven medicine as the standard of care and for life sciences research. It is the creator of the SOPHiA DDM™ Platform, a cloud-native platform capable of analyzing data and generating insights from complex multimodal data sets and different diagnostic modalities. The SOPHiA DDM™ Platform and related solutions, products, and services are currently used by a broad network of hospital, laboratory, and biopharma institutions globally. For more information, visit SOPHiAGENETICS.COM, or connect on X, LinkedIn, Facebook, and Instagram. Where others see data, we see answers. 

SOPHiA GENETICS products are for Research Use Only and not for use in diagnostic procedures, unless specified otherwise. The information in this press release is about products that may or may not be available in different countries and, if applicable, may or may not have received approval or market clearance by a governmental regulatory body for different indications for use. Please contact support@sophiagenetics.com to obtain the appropriate product information for your country of residence.

SOPHiA GENETICS Forward-Looking Statements: 
This press release contains statements that constitute forward-looking statements. All statements other than statements of historical facts contained in this press release, including statements regarding our future results of operations and financial position, business strategy, products, and technology, as well as plans and objectives of management for future operations, are forward-looking statements. Forward-looking statements are based on our management's beliefs and assumptions and on information currently available to our management. Such statements are subject to risks and uncertainties, and actual results may differ materially from those expressed or implied in the forward-looking statements due to various factors, including those described in our filings with the U.S. Securities and Exchange Commission. No assurance can be given that such future results will be achieved. Such forward-looking statements contained in this press release speak only as of the date hereof. We expressly disclaim any obligation or undertaking to update these forward-looking statements contained in this press release to reflect any change in our expectations or any change in events, conditions, or circumstances on which such statements are based, unless required to do so by applicable law. No representations or warranties (expressed or implied) are made about the accuracy of any such forward-looking statements.

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FAQ

What is the focus of the collaboration between SOPHiA GENETICS and UroCCR?

The collaboration focuses on using a multimodal algorithm to predict post-operative outcomes for renal cell carcinoma patients.

How did the AI model co-constructed by SOPHiA GENETICS and UroCCR perform in the study?

The AI model provided strong predictions for post-operative outcomes and outperformed common risk scores.

What type of data was included in the UroCCR database for the study?

The UroCCR database included radiological, clinical, and biological data from over 3,300 patients operated between May 2000 and January 2020.

What is the goal of UroCCR in collaborating with SOPHiA GENETICS?

The goal is to connect a national network of medical professionals focusing on therapeutic management and research into kidney cancer using AI technology.

How does SOPHiA GENETICS' technology empower researchers in the study?

SOPHiA GENETICS' technology breaks data silos and provides data-driven insights to drive precision medicine in cancer research.