Fluorine‐Modified SERMs: A DFT, ADMET, and Statistical Analysis of Toremifene and Raloxifene

ABSTRACT Breast cancer remains a major global health challenge, with 670,000 deaths reported in 2022. Current treatment strategies involve surgery, radiation, and pharmacological interventions, including selective estrogen receptor modulators (SERMs) such as Toremifene (TOR) and Raloxifene (RAL). These therapies can cause adverse effects, highlighting the need for modifications to improve safety and efficacy. Fluorine substitution has emerged as a promising approach in drug development due to its ability to enhance pharmacokinetic and pharmacodynamics properties. The introduction of fluorine influences absorption, distribution, metabolism, excretion, and toxicity (ADMET) by increasing lipophilicity, improving metabolic stability, and modifying drug–receptor interactions. Given the extensive use of fluorinated compounds in FDA‐approved drugs, exploring fluorine incorporation in breast cancer therapies is a logical step in drug optimization. This study investigates the impact of fluorine modifications on the structures of TOR and RAL using molecular modeling and computational chemistry techniques. Conceptual density functional theory (CDFT) calculations with Gaussian 16 were employed to analyze reactivity, and ADMET predictions were performed using pkCSM. A statistical analysis was conducted to correlate fluorine substitution patterns with variations in pharmacological properties. The results provide insights into how fluorine incorporation can modulate drug behavior, potentially leading to the development of improved breast cancer therapies with enhanced efficacy and reduced toxicity.