Some scientists and physicians have long predicted that personalized medicine, tailoring drug doses and combinations to people’s specific diseases and body chemistry, would be an important part of future health care. A team of UCLA bioengineers, scientists, and physicians has taken a major step toward that reality.
The PPD relies on algebraic equations to relate phenotype (in this case, trough level of an immunosuppressant, tacrolimus) to input (tacrolimus concentration). By mapping patient response over the course of treatment, the equation produces a two-dimensional (2D) parabola that indicates the next dose that the patient should receive. The parabola shifts as drugs are added or taken away, or as the patient undergoes additional clinical procedures, such as hemodialysis, which can interfere with drug distribution within the body. The PPD approach was tested in four patients and compared to the standard of care, physician guidance. The PPD patients were out of trough range less frequently and for shorter periods of time than controls, suggesting that the equation was predicting next doses accurately.
The PPD approach may have broad applicability beyond transplant medicine, because it is independent of disease mechanism or drug of choice and may therefore personalize regimens for many types of patients.
After organ transplant, patients are on a merry-go-round of medicines and procedures to make sure that the graft is not rejected. Currently, physicians use dosing guidelines for drugs meant to suppress the immune system, but also use educated guesses in choosing dose, to account for variability in patient response to the drugs and drug-drug interactions.
The research team from the UCLA schools of dentistry, engineering and medicine, developed a revolutionary technology platform called phenotypic personalized medicine, or PPM, which can accurately identify a person’s optimal drug and dose combinations throughout an entire course of treatment. Their research appeared online in the April 6 issue of the journal Science Translational Medicine. Unlike other approaches to personalized medicine currently being tested, PPM doesn’t require complex, time–consuming analysis of a patient’s genetic information or of the disease’s cellular makeup. Instead, it produces a personalized drug regimen based on information about a person’s phenotype, biological traits that may include anything from blood pressure to the size of a tumor or the characteristics of a specific organ.