SUMMARY
Lauren E. Haydu, Ph.D., collaborates and develops her research expertise in biostatistics, clinical trials, and cancer informatics to study melanoma, breast cancer, neurology, and neuro-oncology. She is enthusiastic about the convergence of personalized medicine, artificial intelligence, and machine learning to revolutionize public health outcomes, particularly in the context of early detection and risk assessment. Dr. Haydu actively engages in investigator-initiated clinical trials and radiation oncology clinical trials at Mayo Clinic's Florida campus. She also provides direct consultation, teaching, and oversight on clinical trial design and analysis for the Alliance for Clinical Trials in Oncology in the upper GI section.
Focus areas
- Predictive models and clinical staging systems to improve outcomes for patients with melanoma. Dr. Haydu develops, refines, and integrates clinical, pathological, molecular, immune, and imaging data. Her areas of interest include personalizing prognostic assessment, improving staging guidelines, and developing tools for precision oncology to aid in patient management and treatment decision-making. Dr. Haydu's ongoing work focuses on improving survival predictions and understanding risk factors associated with central nervous system metastasis.
- Harnessing machine learning and personalized medicine. Dr. Haydu harnesses machine learning and personalized medicine to innovate public health approaches. By using large multi-institutional datasets, her research aims to intercept illnesses at earlier stages and tailor treatment strategies. The goal is to reduce disease burden and improve healthcare outcomes on a population scale, particularly through the application of biotechnology and machine learning to refine risk prediction and enhance clinical decision-making.
- Neurodegenerative illnesses and cancers in the brain. Dr. Haydu advances the understanding of neurodegenerative conditions and cancers in the brain through clinical trials and retrospective data analysis. This research aims to use biostatistical methods and leverage large clinical datasets to advance understanding of and enhance treatment strategies for rapid progression, particularly in Alzheimer's disease and related dementias. Her focus is on improving diagnosis, prognosis, and management for patients with brain tumors.
- Improving outcomes for people with breast cancer and other illnesses. Dr. Haydu strives to improve outcomes for individuals with breast cancer and other illnesses by integrating molecular biology with clinical data using new approaches. This research investigates factors that influence patient prognosis and treatment responses, with the goal of personalizing therapy. Recent efforts focus on the prompt detection of early-onset breast cancer using new imaging and liquid biopsy technologies.
Significance to patient care
Improving care through research focuses on developing tailored treatment plans to deal with unmet needs in cancer and neurodegenerative conditions. Improving ways of finding out why these illnesses advance and react to treatments allows for precision therapy. This approach aims to tailor treatment based on each patient's history, including sociodemographic, genetic, molecular, and clinical factors. This research also looks at early-detection methods and new treatments. Dr. Haydu strives to offer targeted therapies that improve outcomes while decreasing side effects and ultimately improving patient care and quality of life.
Professional highlights
- Associate editor, statistics, British Journal of Dermatology, 2024-present.
- Data core director, Alzheimer's Disease Research Consortium, Mayo Clinic in Florida, 2024-present.
- Scientific director, Clinical Research Design and Analysis Unit, Department of Quantitative Health Sciences, Mayo Clinic in Florida, 2024-present.
- Co-director, Department of Quantitative Health Sciences Grand Rounds, Mayo Clinic in Florida, 2024-2026.