After a patient undergoes an organ transplant, one of the most important parts of their follow-up care is making sure their immune system does not attack and reject the new organ. This usually involves careful matching of tissue compatibilities prior to transplant and a complex combination of immunosuppressant drugs given in different, and often changing, doses.
Maintaining the right level of immunosuppressive drugs in the body can be difficult. Too little may risk rejection; drug levels that are too high may cause side effects. Traditionally, doctors monitor drug levels and prescribe doses and combinations of these drugs based on how other patients have responded in the past. This type of treatment looks at the most common outcome for the average patient and assumes that it will apply to most other patients.
However, a study from researchers at the University of California, Los Angeles (UCLA), has found that personalized medicine techniques can be used to create tailored treatments, such as personalized drug therapy, for organ transplant patients that minimize the chances of transplanted organs being rejected. The results of their study could completely change the way post-transplant care is managed.
The study details the success of a new approach to personalized treatments for transplant patients known as phenotypic personalized medicine, or PPM.
Most forms of personalized medicine use a patient’s genetic profile to create a tailored treatment. Though this is effective, it is costly and time-consuming. By contrast, PPM creates a recommended treatment profile based on a person’s phenotype, a profile of personal traits that includes variables from blood pressure to organ health to levels of certain proteins in a patient’s blood.
When a person’s phenotype changes, for example due to additional surgery or an infection, their body may metabolism immunosuppressant drugs slower or faster, and a new dosage may be necessary. This makes PPM ideal for treating organ transplant patients, whose health often changes dramatically and frequently in the years following transplants.
Researchers at UCLA used the phenotypes of transplant patients to create graphs that plotted different drug doses against the patient’s predicted blood levels of immunosuppressant medication and found that the curves of these graphs were remarkably consistent. Each of these PPM graphs provided a personalized treatment plan that allowed doctors to select the ideal dose and combination of immunosuppressant drugs based on the outcome they hoped to achieve.
The actual study involved liver transplant patients, half of whom were treated according to the old model (doctors prescribing doses of drugs based on how other patients have responded in the past) and half of whom were treated using drug combinations based on their phenotypic personalized medicine graph. The researchers tested the levels of an immunosuppressant drug called tacrolimus, which is commonly given to transplant patients. In order to minimize the chance of side effects or rejection of a transplanted organ, a patient’s tacrolimus levels must stay within a certain narrow range.
The study found that the patients treated using PPM were more likely to have tacrolimus levels within the ideal range than patients treated with the traditional approach, which meant they were less likely to reject their transplanted organs.
The authors of the UCLA study have begun additional research to further examine how PPM can be used to improve patient outcomes for other types of organ transplants, and in June 2016 a separate group of scientists published research on the benefits of phenotyping for kidney transplant patients. While their results require further study, they also seem to confirm that profiling patient phenotypes can improve outcomes in post-transplant care.
Other research into PPM has sprung up, with researchers examining how it could be used not just to prevent organ rejection, but also to treat cancer and other chronic diseases.
While phenotypic personalized drug therapy is still a new field of study, recent research seems to indicate that it could provide the key to caring for post-transplant patients, with far more precise outcomes than traditional treatment options and at far less cost that most forms of personalized medicine.
August 31, 2016
Christopher Nystuen, MD, MBA