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Background Circulating cell‐free tumor DNA (ctDNA)‐based mutation profiling, if sufficiently sensitive and comprehensive, can efficiently identify genomic targets in advanced lung adenocarcinoma. Therefore, the authors investigated the accuracy and clinical utility of a commercially available digital next‐generation sequencing platform in a large series of patients with non–small cell lung cancer (NSCLC). Methods Plasma‐based comprehensive genomic profiling results from 8388 consecutively tested patients with advanced NSCLC were analyzed. Driver and resistance mutations were examined with regard to their distribution, frequency, co‐occurrence, and mutual exclusivity. Results Somatic alterations were detected in 86% of samples. The median variant allele fraction was 0.43% (range, 0.03%‐97.62%). Activating alterations in actionable oncogenes were identified in 48% of patients, including EGFR (26.4%), MET (6.1%), and BRAF (2.8%) alterations and fusions (ALK, RET, and ROS1) in 2.3%. Treatment‐induced resistance mutations were common in this cohort, including driver‐dependent and driver‐independent alterations. In the subset of patients who had progressive disease during EGFR therapy, 64% had known or putative resistance alterations detected in plasma. Subset analysis revealed that ctDNA increased the identification of driver mutations by 65% over standard‐of‐care, tissue‐based testing at diagnosis. A pooled data analysis on this plasma‐based assay demonstrated that targeted therapy response rates were equivalent to those reported from tissue analysis. Conclusions Comprehensive ctDNA analysis detected the presence of therapeutically targetable driver and resistance mutations at the frequencies and distributions predicted for the study population. These findings add support for comprehensive ctDNA testing in patients who are incompletely tested at the time of diagnosis and as a primary option at the time of progression on targeted therapies., Circulating cell‐free tumor DNA‐based liquid biopsy using next‐generation sequencing detects a spectrum of targetable alterations at frequencies expected in patients with advanced non–small cell lung cancer. These findings support the concept of a plasma‐first algorithm at the time of progression on targeted therapy for this population.