(apparently in Rheumatoid Arthritis, RA) can significantly impact the performance of specific drug treatments because the study revealed 1,277 genes that specifically have
therapy (rituximab or tocilizumab).
The team applied a data analysis technique called machine learning modeling to develop computer algorithms that can predict drug response in individual patients and correlate it with gene profiles from biopsies, histological or clinical factors.
“Combining molecular information before prescribing arthritis treatments to patients could forever change the way we treat the condition. Patients will benefit from a personalized approach. chemistry has a much greater chance of success than today’s trial and error prescribing Standards These results are extremely interesting in demonstrating the potential at our fingertips, however, the field This is still a stub and additional validation studies will be required to fulfill the promise of precision medicine in RA,” said Prof. Costantino Pitzalis, at Queen Mary University of London.
Incorporating these markers in future diagnostic tests will be a necessary step in translating these findings into routine clinical care.