Project Wonder is a collaboration between clinicians at the Johns Hopkins Myositis Precision Medicine Center of Excellence https://www.hopkinsmyositis.org and data scientists, human factors, and software engineers at the Johns Hopkins Applied Physics Laboratory (APL) https://www.jhuapl.edu in Laurel Md.
Project Wonder Engine is part of the Precision Medicine Analytics Platform, a multiyear project across the Johns Hopkins System, focused on accelerating precision medicine for clinicians and researchers by building a tool to facilitate discovery from data.
The Wonder Engine has been able to aggregate and organize vast amounts of clinical and research data enabling clinicians to explore their data, identify trends, test intuitions, formulate, and validate novel hypotheses.
“The idea behind the Wonder Engine is that we can harness the power of data science to generate moments of wonder for clinicians to enable them to do something unique with their patient data,” said Suma Subbarao, the Project Manager, of the Precision Medicine Analytics Platform (PMAP) https://ictr.johnshopkins.edu/rpgrams_resources/programs-resources/i2cpmap, a multiyear project across the Johns Hopkins system.
The initial goal of Wonder Engine was to validate a hypothesis that there is a strong association of cancer with the onset of myositis, a rare inflammatory autoimmune disease. The goal is to help discover new subgroups of patients using novel data science methods and visualization techniques.
Myositis can afflict multiple organ systems including the lungs, joints, muscles, and skin. A wealth of data was amassed by the Johns Hopkins Myositis Precision Medicine Center of Excellence (PMCoE) pertaining to this disease, but the associated cancer risk is not well characterized.
For example, the highest incidence of cancer diagnosis occurs at the onset of myositis symptoms, however, it is not always understood which patients are at the highest risk. As a result, many patients are screened for cancer at the onset of myositis but it is at great expense and stress to patients.
Certain biomarkers and demographic factors are thought to influence cancer risk, but the associations are not well enough established to be able to differentiate and therefore screen fewer patients for cancer upon myositis diagnosis.
Using the Wonder Engine, clinicians at the PMCoE were able to validate biomarkers that are known to predict cancer diagnosis in their patients within a few hours, that previously has taken years for the myositis research community to realize. Today, the team is able to search for novel patterns and challenging dogmas within the myositis cancer field.
Eventually, the team hopes to turn the Wonder Engine into a tool that can be used in the clinic as well as for research, not just at Johns Hopkins, but nationally and globally. Brant Chee, Project Wonder, Chief Data Scientist said, “ As we expand to partner with other centers of excellence at Johns Hopkins, we will continue to improve the Wonder Engine’s capability to accelerate human creativity with the power of data.”