Compilation of patient-specific parabolic response surfaces, which are the keys to personalized medicine. They represent responses to combination therapy for individual patients for liver-transplant immunosuppression.
The researchers, from the UCLA schools of medicine, dentistry and engineering and applied science, developed a revolutionary technology platform called phenotypic personalized medicine (PPM), which can accurately identify a person’s optimal drug and dose combinations throughout an entire course of treatment without the need for complex, time-consuming analysis of a patient’s genetic information or of the disease’s cellular makeup.
Dean Ho, PhD, professor in the Division of Oral Biology and Medicine in the UCLA School of Dentistry, says one of the platform’s significant capabilities is producing graphs that are personalized for individual patients and represent precisely how they respond to treatment.
Remarkably, Dr. Ho says, every person produces a graph in the shape of a curve called a parabola — picture a “U” either right-side up or upside down — and that parabola dictates how doctors should proceed with treatment. Each person’s unique curve provides doctors with a visual guide to determine the exact doses of medicine they should prescribe as the treatment continues, which, Dr. Ho says, is the key to achieving truly personalized medicine.
“This study demonstrated the ability to use a patient’s phenotype to personalize their treatment in an actionable manner without the need for genome profiling,” Dr. Ho says. “We also have shown that PPM can be extended to optimize combination therapy for a wide spectrum of diseases.”
Revealing that every patient’s response to medical treatment produces a parabola-shaped graph is a landmark advance. Among other things, Dr. Ho says, the approach will allow doctors to prescribe the precise amount of medicine needed to shrink a tumor or ensure the body doesn’t reject an organ, for example, as opposed to using a higher “standard” dose that’s recommended based on an average of how all patients have responded previously.
“Individualizing Liver Transplant Immunosuppression Using a Phenotypic Personalized Medicine Platform,” Science Translational Medicine, April 6, 2016