Background: PDAC has a propensity for early systemic dissemination and most pts with primary tumors radiographically confined to the pancreas harbor micro-metastases. cfDNA based CGP offers a non-invasive mechanism to identify actionable genomic targets in PDAC and account for serial clonal evolution in response to therapeutic selection pressure. We interrogated the Foundation Medicine database to characterize cfDNA based CGP in pts with PDAC. Methods: We performed a retrospective analysis of pts with PDAC who underwent cfDNA based CGP between May 2016 and February 2020. cfDNA based CGP was done utilizing either the FoundationOne Liquid (F1-Liquid) or the Foundation-ACT (F-ACT) testing platform. Samples were interrogated for exonic and select intronic regions of cancer-related genes for both F1-Liquid (Exons: 70 genes; Select Introns: 7 genes) and F-ACT (Exons: 59 genes; Select Introns: 6 genes). Variant zygosity and somatic/germline status (SGZ) for short variant mutations was computationally predicted without matched normal tissue using an investigational method. A Gaussian Mixture Model (GMM) was used to identify latent molecular classes in samples harboring somatic, pathogenic variants (n=613); the Bayesian Information Criteria (BIC) was used for model selection. Results: We identified 1,009 pts with cfDNA based CGP - median age was 65, 55% were male, and median cfDNA concentration was 24 ng/µL. cfDNA yield had an influence on the detection of somatic alterations (p <0.001). 613/1009 (60.8%) of pts had at least one somatic alteration detected on cfDNA based CGP. TP53 (53.7%), KRAS (40.3%) and CDKN2A (6.5%) were the most frequently altered genes (Table1). Homologous Recombination DNA Damage Repair (HR-DDR) gene alterations [somatic and/or germline BRCA2, ATM, and CHEK2 alterations], were detected in 12.3% (124/1009) pts – 11.4% (46/403) in KRAS mutated pts and 12.9% (78/606) in KRAS wildtype (WT) pts. Fusions were detected only in KRAS WT pts (1.5%, 6/403). Pts with cfDNA based CGP could be classified into 4 latent classes – class 1 (KRAS - 100%, TP53 - 100% and CDKN2A– 33.3%), class 2 (KRAS - 65.7%), class 3 (KRAS – 68.2%, CDKN2A/B– 7.7% ) and class 4 (KRAS– 38.5%, TP53 - 26.7%). Conclusions: The putative role of cfDNA based CGP in monitoring therapeutic response and clonal evolution in pts with PDAC may be predicated on cfDNA yield. In clinical scenarios where pre-treatment tissue availability is limited, cfDNA based CGP may be have utility in leveraging the predictive value of somatic and/or germline HR-DDR gene alterations. The prognostic and/or predictive relevance of the four latent classes needs validation in clinically annotated data sets.