In recent years, we have witnessed a breakthrough in genome engineering technology, attributed to the gene-editing technique CRISPR-Cas9 (or often called CRISPR) that works like a pair of scissors to cut, insert or reorder specific genetic fragments, creating changes in the biological cell to understand gene function. CRISPR is full of promise and has already been used in a variety of applications such as to help create mosquitoes that do not transmit malaria (Hammond et al. 2016), to eradicate pathogen genomes from infected species (Ebina et al. 2013, Hu et al. 2014), and more recently to test and to battle cancer (Sanchez-Rivera and Jacks 2015, Shi et al. 2015, Platt et al. 2014). However, with the advent of this technology, there is still a lack of new treatments found for cancer. Progress in this area has been hindered primarily by the lack of automation tools for manipulating, editing, and analyzing large genomes without any bias – this has limited our understanding of the genes and biological processes involved with cancer. Here, I will describe how we have developed a new automated microfluidic tool that will target a specific set of genes in lung cancer cells (specifically H1299 cells) and determine which genes are modulators of cancer progression. This new gene-editing tool powered by droplet-based microfluidics is being used to eliminate multiple perturbations within cells while the readouts will depend on cell population measurements. Such a technology has emerged as a versatile liquid handling platform for automating biology (Shih et al. 2013) (Ng et al. 2015) and screening-based applications (Dressler, Casadevall, and deMello 2017). In my presentation, I will describe our system to automate gene-editing processes specific to the CRISPR-Cas9 editing workflow, namely cell culturing, lipid-mediated transfection, and cellular analysis. Next, I will show results from optimizing our gene-editing platform to assess the impact of variations in several parameters on the efficacy of cell transfection and gene targeting using Cas9. Finally, we will demonstrate the broad applicability of the device showing results from a knockout loss-of-function screen that is tackling several oncogenes. Overall, this study aims at demonstrating that our genome editing-on-a-chip approach will greatly speed up validation of loss-of-function screens, including genome wide arrayed or pooled screens, at relatively low cost, with minute amount of material and without the need for enrichment analysis based on next-generation sequencing profiles as required by pooled screens. We believe that this new method will further enhance our understanding of mechanisms related to cancers, which we hope can possibly lead to novel therapies options for those suffering from this disease.