The ATR-CHK1-WEE1signaling axis is essential in cell cycle regulation and in maintaining cell cycle fidelity. ATR is a kinase that phosphorylates repair proteins and activates cell cycle arrest. Wee1 is a cell cycle inhibitor that activates CDK1 and CDK2 to initiate cell cycle arrest. Via low-dose combination treatment of ATRi and WEE1i we hope to develop a treatment for high grade serous ovarian cancers (HGSOCs). The factors that are recruited to the replication fork following drug treatment may be recruited to mitigate the effects caused by the drug. We are interested in these factors, as the treatment may be more effective if the patient has a deletion or truncation mutation in them. This furthers the efforts of personalized medicine where the treatments specifically match the cancer type to limit toxic effects. We employed iPOND to identify the factors that are recruited to the replication fork in response to the ATRi-WEE1i treatment. The iPOND-QMS process stands for the isolation of proteins on nascent DNA with quantitative mass spectrometry. This process is our strategy to determine which factors are present at the replication fork. The initial iPOND dataset made use of four different inhibitors ATRi, WEE1i, CDKi, and Aphidicolin. This project will focus specifically upon the proteins recruited under combination drug treatments including ATRi and WEE1i. The bioinformatic analysis of such factors, provided by iPOND-QMS experimentation, under specific drug conditions to serve as a prioritization pathway for identifying hits is unresolved. Seeking to validate the results of the iPOND-QMS experimentation and narrow down the list of 2056 proteins recruited to the replication fork, we hope to identify which proteins, if knocked down, would enhance the effects of the drug treatment. Specifically, Cytoscape, the STRING Database, and Cancer BioPortal are the main bioinformatic strategies employed throughout this project. Thus, through the validation of such data we hope to identify biomarkers for efficacious drug treatment. Additionally, we hope to gain a deeper understanding of the applications of bioinformatic analytical pathways, as well as developing a prioritizing process to determine the significance of proteins. The use of such inhibitors may induce genomic instability in cells, possibly resulting in synthetic lethality in cancer cells with mutated damage repair pathways.