A protein called p38 was regarded as a very attractive target for treating rheumatoid arthritis by many pharmaceutical companies. Arthritis patients generally have increased activity of this protein that generates inflammation. In many lab studies p38 inhibitors successfully soothed the inflammation. However, these same drugs could not succeed in many of the clinical trials.
In a new study from Massachusetts Institute of Technology or MIT as it is popularly known as throws some light on as to why these drugs did not work successfully for arthritis in clinical trials. By simplifying the complex interactions between different cell pathways that are engaged with inflammation, the scientists unraveled that by shutting off p38 other inflammatory pathways are being triggered.
Impact of Potential Drugs on Cellular Systems is Being Discovered
Rheumatoid arthritis affects around more than 1 million Americans and it is an autoimmune disorder that generates painful and swollen joints, basically adversely affecting the hands and wrists. This pain arises out of inflammation in the very lining of the joints. Cells are known as synovial fibroblasts and it categorically supplies structural support for the joint lining thereby enabling the promotion of swelling and inflammation in arthritic conditions.
Many years ago, researchers who were exploring new treatments methods for arthritis came across those synovial fibroblasts from the patients who are suffering from arthritis patients and had quite high levels of p38. Following such a discovery, many of the pharmaceutical companies started working on p38 inhibitors.
The findings of this study demonstrate that the significance of studying an impact of potential drugs on complex systems of cells, as mentioned by Doug Lauffenburger, senior author of the study and head of MIT’s Department of Biological Engineering. He further opines on the importance of doing these studies under different environmental conditions that could also match with those found in diseased tissues.
The said study has been published on Science Signaling, March 2018 issue.