Presentation
Programmatic Innovations in Cancer Team Data Science
DescriptionInnovation in cancer care and research come about in many ways. High performance computing (HPC) has expanded the frontier for innovation in cancer and promises accelerated impact on the massive challenge of cancer. Yet even with visionary inspiration, vast quantities of data, and a growing capacity in HPC, there are many key technical, scientific, organizational and cultural challenges that remain in realizing impactful patient outcomes.
The volume of real-world patient data at The University of Texas MD Anderson Cancer Center is tremendous with 1.6 million outpatient patient visits per year, 14 million pathology and laboratory procedures, and over 600,000 diagnostic imaging procedures each year. Harnessing and leveraging this information, however, requires more than HPC and computational algorithms. Ultimately, it requires building a data and data science ecosystem to enable interdisciplinary teams to effectively communicate around the data. To formulate actionable questions for cancer discovery and clinical data, teams must appreciate the importance of the context of the data and embrace the complexity of the data, cancer, and the surrounding healthcare system.
MD Anderson Cancer Center has taken a particularly innovative approach in creating the Institute for Data Science in Oncology (IDSO) as part of an overall institutional strategy to tackle these challenges and accelerate translational impact for data science. While not a traditional computational approach for cancer focusing on algorithms, methods, technologies, and implementations, the IDSO programmatic approach is addressing key challenges of creating an organizational ecosystem and culture that readily embraces, innovates, advances, and adopts computational and data science approaches to cancer.
Building on a decade of formative efforts and formally launched in 2023, the IDSO approach is anchored with three pillars of team data science, translational impact, and continuous learning and innovation, all with a direction for improving patient care. The IDSO serves as a hub with defined programs in education and culture, collaboration (both internal and external), and five co-led team data science focus areas emphasizing translational impact in domains of quantitative imaging, single cell spatial analytics, computational modeling for precision medicine, decision analytics for health, and safety, quality, and access.
Already, IDSO is having key impacts, opening avenues for innovation in computational approaches, data flows and growing demand for HPC in meeting cancer challenges. A collaboration with the University of Texas at Austin, the Texas Advanced Computing Center and MD Anderson co-led with IDSO has led to over 20 new collaborative projects involving HPC. The Tumor Measurement Initiative, which heavily uses HPC to train AI models using MD Anderson’s vast image resources has prepared hundreds of imaging datasets utilizing tens of thousands of images and developed an initial library of model algorithms. The IDSO affiliates program now includes more than 50 individuals from across the institution. And in just two short years, the fellowship training program has trained more than 38 personnel in data science.
The presentation will provide useful insights including lessons learned in forming, launching and establishing the IDSO, perspectives on challenges that require communities to solve, and thoughts on future directions.
The volume of real-world patient data at The University of Texas MD Anderson Cancer Center is tremendous with 1.6 million outpatient patient visits per year, 14 million pathology and laboratory procedures, and over 600,000 diagnostic imaging procedures each year. Harnessing and leveraging this information, however, requires more than HPC and computational algorithms. Ultimately, it requires building a data and data science ecosystem to enable interdisciplinary teams to effectively communicate around the data. To formulate actionable questions for cancer discovery and clinical data, teams must appreciate the importance of the context of the data and embrace the complexity of the data, cancer, and the surrounding healthcare system.
MD Anderson Cancer Center has taken a particularly innovative approach in creating the Institute for Data Science in Oncology (IDSO) as part of an overall institutional strategy to tackle these challenges and accelerate translational impact for data science. While not a traditional computational approach for cancer focusing on algorithms, methods, technologies, and implementations, the IDSO programmatic approach is addressing key challenges of creating an organizational ecosystem and culture that readily embraces, innovates, advances, and adopts computational and data science approaches to cancer.
Building on a decade of formative efforts and formally launched in 2023, the IDSO approach is anchored with three pillars of team data science, translational impact, and continuous learning and innovation, all with a direction for improving patient care. The IDSO serves as a hub with defined programs in education and culture, collaboration (both internal and external), and five co-led team data science focus areas emphasizing translational impact in domains of quantitative imaging, single cell spatial analytics, computational modeling for precision medicine, decision analytics for health, and safety, quality, and access.
Already, IDSO is having key impacts, opening avenues for innovation in computational approaches, data flows and growing demand for HPC in meeting cancer challenges. A collaboration with the University of Texas at Austin, the Texas Advanced Computing Center and MD Anderson co-led with IDSO has led to over 20 new collaborative projects involving HPC. The Tumor Measurement Initiative, which heavily uses HPC to train AI models using MD Anderson’s vast image resources has prepared hundreds of imaging datasets utilizing tens of thousands of images and developed an initial library of model algorithms. The IDSO affiliates program now includes more than 50 individuals from across the institution. And in just two short years, the fellowship training program has trained more than 38 personnel in data science.
The presentation will provide useful insights including lessons learned in forming, launching and establishing the IDSO, perspectives on challenges that require communities to solve, and thoughts on future directions.
Event Type
Workshop
TimeMonday, 17 November 202511:35am - 11:55am CST
Location241