Traditional medical treatments are designed as a “one-size-fits-all” approach that can be effective for some or many patients, but may not be for others.
The objective of precision medicine is to make diagnosis of disease or illness, treatment therapies, and prevention more personalized, proactive, predictive and precise.
To do so, the field considers individual differences in genes, environments, and lifestyles. Clinicians can select treatments that are most likely to help patients, based on a more complete picture and understanding of their disease or ailment.
This targeted, personalized care relies on Big Data and technological advances — bringing together innovations in fields such as genomics, metabolomics, biomedical data sciences and environmental sciences, and utilizing technologies such as mobile health, imaging, artificial intelligence, and social networking.
In the process, multiple variables that affect health can be studied to draw better treatment conclusions for individuals. Data such as toxic exposure, emotional states, sleep, diet, heart rate, labs and more can be used to inform better care.
Along the way, scientists and society consider and debate the ethical, legal and social implications of the use of these new tools.
Here’s a scenario from Christopher Wang, manager of UC Davis’ Center for Precision Medicine and Data Sciences:
- Different ages
- Different underlying genetics related to gender
- Different microbiomes and gut microbiomes (the bacteria, viruses and other life in the gut)
- environments — perhaps one has been more exposed to stressors such as adverse childhood experiences (ACEs)
- Different behaviors — one uses tobacco, or lives near a freeway
Precision medicine looks at as many of these factors as possible together at once — striving to consider the patient’s whole story from the very beginning, rather than a 10-minute exam-room snapshot.
