Summary
Researchers at Johns Hopkins Medicine have developed an innovative computer model that could significantly improve immunotherapy outcomes for lung cancer patients.
Led by Dr. Kellie Smith, the team created a machine learning algorithm capable of distinguishing between immune cells that actively fight cancer and those that don’t, with up to 95% accuracy. This represents a major advancement over current methods that struggle to identify truly tumor-reactive T cells.
For lung cancer patients, particularly those with non-small cell lung cancer (NSCLC) who show variable responses to immunotherapy, this technology could be transformative. The model may help clinicians better predict which patients will benefit from existing treatments and guide the development of more personalized approaches for non-responders.
The Johns Hopkins team is now working to validate their findings in larger patient populations and integrate this technology into clinical practice, potentially leading to improved outcomes for patients facing this challenging disease.
