Breast cancer is the most prevalent malignancy and second leading cause of death in women worldwide, with hormone receptor-positive luminal breast cancers being the most widespread subtype. While these tumors are generally amenable to endocrine therapy, cellular heterogeneity and acquired ability of tumor cells to undergo cell state switching makes these populations difficult to be fully targeted and eradicated through conventional methods. We have leveraged a quality-by-design (QbD) approach that integrates biological responses with predictive mathematical modeling to identify key combinations of commercially available drugs to induce estrogen receptor expression for therapeutic targeting. This technology utilizes a high level of automation through a custom-built platform to reduce bias as well as design-of-experiments methodology to minimize the experimental iterations required. Utilizing this approach, we identified a combination of clinical compounds, each at concentrations well below their efficacious dose, able to induce the expression of estrogen receptor alpha (ESR1) in hormone-positive breast cancer cells. Induction of ESR1 in luminal cells leads to chemosensitization. These findings provide proof of concept for the utility of the QbD strategy and identify a unique drug cocktail able to sensitize breast cancer cells to tamoxifen.