Cancer epidemiologists use data to understand cancer and improve prevention, care, and survivorship. The field of cancer epidemiology continues to evolve such that today's epidemiologists are no longer limited to laborious, time-consuming data mining that demands substantial human input. Instead, they are tapping into Real-World Data (RWD), real-time, real-world multiple datasets drawn from electronic health records, health apps, genetics tests, and more. RWD is becoming a key resource for patients, doctors, and regulators because it reflects what happens in everyday care, not just in clinical trials. This shift is an evolution. RWD gives epidemiologists modern tools to harness the power of ...
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Cancer epidemiologists use data to understand cancer and improve prevention, care, and survivorship. The field of cancer epidemiology continues to evolve such that today's epidemiologists are no longer limited to laborious, time-consuming data mining that demands substantial human input. Instead, they are tapping into Real-World Data (RWD), real-time, real-world multiple datasets drawn from electronic health records, health apps, genetics tests, and more. RWD is becoming a key resource for patients, doctors, and regulators because it reflects what happens in everyday care, not just in clinical trials. This shift is an evolution. RWD gives epidemiologists modern tools to harness the power of digital health records, patient-reported outcomes, and advanced analytics. By pulling together these data sources, we can better understand populations, predict health trends, and design timely, effective interventions. But RWD is complex. It requires strong study design, advanced statistics, and careful interpretation. To handle this, researchers need cutting-edge technologies like artificial intelligence and natural language processing, which make it possible to quickly process large, complicated datasets with accuracy and consistency. Our institution is ready to meet this need. We plan to expand our successful CPRIT training program with a new initiative: the Cancer Epidemiology with Real-World Data Training Program. This 3-year postdoctoral program will train early-career epidemiologists and bioinformaticians how to combine traditional research methods with RWD and modern technology. Each trainee will have a personalized plan and a team of mentors from multiple disciplines. We will recruit motivated PhDs in epidemiology or bioinformatics, and MDs with relevant training, to become independent scientists doing impactful cancer research. Our long-term goal is to build a diverse workforce focused on prevention, clinical, and translational cancer research that benefits Texas.
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