Researchers at the University of California (UCLA), in Los Angeles, have taken a big step towards creating drug doses and combinations that are tailored to people’s specific diseases and body chemistry.
The researchers, from the UCLA schools of dentistry, engineering and medicine, developed a revolutionary technology platform called phenotypic personalised medicine, or PPM, which can accurately identify a person’s optimal drug and dose combinations throughout an entire course of treatment. Unlike other approaches to personalised 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 drug regimen based on information about a person’s phenotype — biological traits that could include anything from blood pressure to the size of a tumor or the health of a specific organ.
Dean Ho, who holds appointments in oral biology and medicine at the UCLA School of Dentistry, and in bioengineering at the UCLA Henry Samueli School of Engineering and Applied Science, said that one of the platform’s remarkable capabilities is its ability to produce graphs personalized for each individual patient that represent precisely how they respond to treatment. A corresponding author on the study, he said: “This study demonstrated the ability to use a patient’s phenotype to personalise their treatment in an actionable manner without the need for genome profiling. We also have shown that PPM can be extended to optimize combination therapy for a wide spectrum of diseases.”
The technique can be used for diseases ranging from cancer to infectious diseases, or following an organ transplant and Dean Ho said: “Among other things, 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 in the past.” Another benefit of PPM is that it can be recalibrated in real time to adapt to changes during treatment — for example if a person undergoes surgery or develops an infection, or if their organ function changes over time, any of which could mean that drug dosages or combinations need to be modified. The platform can use the patient’s new data to provide doctors with a new parabola and revised recommendations.
The new study was based in part on evaluation of eight people who had recently received liver transplants. Dr Ali Zarrinpar, assistant professor of surgery in the UCLA division of liver and pancreas transplantation and a corresponding author of the study, said: “Properly managing patients’ immunosuppression can have profound long-term impacts on the survival of the organ and the patient. “This study shows that we can pinpoint drug doses that can substantially improve patient outcomes. The ability to confidently and systematically guide the treatment of each patient is a critical advance in minimising the chance that transplant recipients will reject their new organs, while also avoiding drug side effects.”
Chih-Ming Ho, who is UCLA Engineering’s Ben Rich–Lockheed Martin Professor, and a corresponding author of the study, said. “Our ability to calibrate how individual patients respond to treatment and to use that information to robustly guide their regimen based on the parabola-based approach has made personalised medicine a reality.” The team is using PPM in several other clinical trials, some of which are already under way, including for treating cancer and infectious diseases.
Support for the project was provided in part by the National Cancer Institute, the National Institutes of Health, the National Science Foundation, the V Foundation for Cancer Research, the Wallace H. Coulter Foundation, the Society for Laboratory Automation and Screening, Beckman Coulter Life Sciences, and the Endowment Fund of the Ben Rich–Lockheed Martin Chair Professorship.