Precision Medicine: Data and Discovery for Improved Health and Therapy

Abstract

The major goal of precision medicine is to improve human health. A feature that unites much research in the field is the use of large datasets such as genomic data and electronic health records. Research in this field includes examination of variation in the core bases of DNA and their methylation status, through variations in metabolic and signaling molecules, all the way up to broader systems level changes in physiology and disease presentation. Intermediate goals include understanding the individual drivers of disease that differentiate the cause of disease in each individual. To match this development of approaches to physical and activity-based measurements, computational approaches to using these new streams of data to better understand improve human health are being rapidly developed by the thriving biomedical informatics research community. This session of the 2017 Pacific Symposium of Biocomputing presents some of the latest advances in the capture, analysis and use of diverse biomedical data in precision medicine.

Using ncRNAs as Tools in Cancer Diagnosis and Treatment—The Way towards Personalized Medicine to Improve Patients’ Health

“…The European Union has acknowledged the importance of personalized medicine by issuing two policy papers arguing in favor of a broader use of personalized medicine (focusing on cancer diagnostics or therapeutics in particular) [ 335 , 336 ], while remarking that such a goal may be hampered by the still high degree of uncertainty surrounding the outcomes [ 337 ]. The key factor that can enable and unleash the full potential of personalized medicine is, according to the analysis laid out in the EU papers, an effective synergy between health data and new technologies, which is necessary to pave the way for the beneficial development of personalized medicine [ 338 ]. We can rely on its unique potential to confront cancer by means of prevention and treatment strategies enabling patients to receive the therapies that can ultimately work best for them.…”

A system for automatically extracting clinical events with temporal information

“…symptoms over a disease course. The associations are often statistically concluded from the evidence collected from the clinical records [ 1 ]. The medical big data mostly exists in an unstructured form, e.g.…”

Factors Associated With Willingness to Share Health Information: Rapid Review (Preprint)

“…This is done by applying emerging methodologies in epidemiology, biostatistics, and computing systems, including machine learning and artificial intelligence. These concepts often intersect, where clinical guidelines developed from population-level studies are adjusted to an individual patient based on their unique characteristics, leading to optimal care [3].…”