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Tempus AI, Inc., a leading technology company specializing in precision medicine, has announced a strategic collaboration with the Institute for Follicular Lymphoma Innovation (IFLI) to accelerate the development of targeted therapies for follicular lymphoma (FL).
This partnership will focus on creating a real-world, multimodal, de-identified data library within Tempus’ state-of-the-art data analytics platform, Lens.
Addressing a Critical Need in Follicular Lymphoma Research
Follicular lymphoma, a slow-growing type of non-Hodgkin’s lymphoma, remains a challenging disease to treat due to its heterogeneous nature.
A major concern is the subgroup of patients who experience disease progression within 24 months of initial treatment (POD24), as they face a significantly higher risk of mortality.
By leveraging AI-driven insights and advanced data analytics, this collaboration aims to provide researchers and clinicians with critical data to develop more effective and personalized treatments.
“This collaboration with IFLI represents a significant step toward understanding the complexities of follicular lymphoma at an unprecedented scale,” said Eric Lefkofsky, Founder and CEO of Tempus. “By integrating diverse datasets, we can uncover novel therapeutic targets and improve outcomes for patients who urgently need better treatment options.”
Harnessing AI and Real-World Data for Precision Medicine
Tempus’ Lens platform is a powerful tool that integrates clinical, molecular, and imaging data to generate AI-driven insights for disease management. By incorporating real-world evidence from follicular lymphoma patients, the platform will allow researchers to:
- Identify Biomarkers: Discover predictive markers that indicate disease progression or response to specific therapies.
- Develop Targeted Treatments: Facilitate drug discovery and clinical trial design by identifying patient subgroups with distinct genetic or molecular profiles.
- Improve Personalized Care: Enable oncologists to make data-informed treatment decisions tailored to individual patients.
Dr. Michael Bishop, Chair of the Institute for Follicular Lymphoma Innovation, emphasized the importance of this initiative, stating, “Through this partnership, we aim to bridge the gap between clinical research and real-world patient experiences. The insights gained will allow us to tailor therapies more precisely and ultimately enhance patient survival rates.”
The Broader Implications for Oncology Research
The collaboration between Tempus and IFLI underscores a growing trend in oncology: the integration of artificial intelligence and big data to revolutionize cancer treatment.
By shifting toward a data-driven approach, pharmaceutical companies and research institutions can expedite the discovery of novel therapies, optimize clinical trial designs, and personalize patient care.
Future Initiatives and Next Steps
Moving forward, Tempus and IFLI plan to expand the dataset by incorporating additional real-world patient data, genomic sequencing, and treatment response analytics. The ultimate goal is to establish a robust, AI-powered framework that can be used not only for follicular lymphoma but also as a model for other complex cancers.
As the healthcare industry continues to embrace AI-driven precision medicine, collaborations like this will play a pivotal role in transforming the landscape of cancer treatment, offering new hope to patients and clinicians alike.
About Tempus AI, Inc.
Tempus is a technology company advancing precision medicine through the application of AI and machine learning.
The company provides cutting-edge solutions to connect molecular, clinical, and imaging data, helping physicians make more informed treatment decisions for cancer and other diseases.
About the Institute for Follicular Lymphoma Innovation (IFLI)
IFLI is a non-profit organization dedicated to advancing research and treatment for follicular lymphoma. Through collaboration with leading academic institutions and biotech firms, IFLI seeks to accelerate the development of breakthrough therapies for this complex disease.
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