Genialis, a leader in RNA biomarker development, has announced the launch of Genialis krasID, a groundbreaking biomarker capable of predicting patient response and benefits from KRAS inhibitors (KRASi). This biomarker algorithm is universally applicable across tissue types and KRAS mutation statuses.
Genialis krasID harnesses machine learning to analyze gene expression patterns in patient tumors, revealing a wealth of information far beyond traditional mutation-based diagnostics. Validation studies on real-world data have shown its effectiveness in non-small cell lung cancer (NSCLC), colorectal cancer (CRC), and pancreatic ductal adenocarcinoma (PDAC).
This biomarker has immense implications for all stages of drug development, from preclinical compound selection to clinical trial patient enrollment and therapy optimization for individual patients. By identifying the most suitable patients for KRASi treatment and predicting the benefit duration, Genialis krasID empowers personalized care strategies to improve treatment outcomes.
Currently, KRAS-positive patients are only selected for therapy based on mutation status, a limited approach that fails to account for individual patient variability. Genialis krasID addresses this gap by providing highly accurate predictions of patient response, allowing clinicians to tailor treatment decisions accordingly.
Jon Napitupulu is Director of Media Relations at The Clinical Trial Vanguard. Jon, a computer data scientist, focuses on the latest clinical trial industry news and trends.