About 70% of breast tumours express estrogen receptor alpha (ER), and has been a strong stimulator for breast cancer proliferation. In addition to their complex roles in cancer, ER also controls a wide range of physiological processes from regulating the development and function of the female reproductive system and initiate protective based functions. Although to fully understand the connection between physiological and molecular functions of the estrogen receptor, it requires an in-depth understanding of the spectrum of genes regulated in the ER pathway. Hence, there have been studies in finding new small molecule inhibitors that will prevent the upregulation of genes related to the estrogenic signaling pathway. But before designing new inhibitors, a continuous challenge is to find genes that are related to the ER pathway that regulates the growth and differentiation of the cells. A possible mechanism is to search for these genes is by knocking out these genes in the genome using gene-editing techniques. Our group has recently developed an automated gene-editing droplet-based microfluidic platform which is capable of automating culturing and editing of lung cancer cells using traditional-based lipid-mediated transfection and performed cellular analysis through imaging techniques. However, in the context of breast cancer cells, traditional methods of gene-editing are not possible. Breast cancer cells (like T47D-KBLuc) are typically hard-to-transfect cell lines which lead us to integrate alternative gene delivery methods (e.g., viral transduction and electroporation) on our microfluidic system to improve delivery. Furthermore, to show the versatility of our platform, this led us to test different types editing methods: RNA interference (RNAi) using short-hairpin RNA (shRNA) and CRISPR using Cas9 protein. Using these different methods, we present three main findings: (1) results from the optimization of gene delivery conducted through viral transduction and electroporation to assess the efficacy of the novel integration of these methods on droplet-based microfluidics, (2) to maintain the integrity of analysis-on-chip, results of cell proliferation measurements using immunofluorescence on device is shown and (3) finally, the targeting of genes expressing ER, p53 and other important oncogenes will be assessed for a loss-of-function screen. Overall, with the novel incorporation of alternative gene delivery methods, this platform aims for working with harder-to-transfect cell lines regarding automated gene-editing to further demonstrate the flexibility and efficacy of using automated gene-editing tools on device. We hope this would allow for better ease and rapidity in finding therapeutic targets for breast cancer treatment.