This episode provides a foundational understanding of structure-activity relationships (SAR) in medicinal chemistry. We will explore how systematic chemical changes inform potency and selectivity of drug candidates. The conversation will cover SAR data, reaction mechanisms, and how adjustments are made based on real experimental outcomes. Modern techniques like AI-driven SAR modeling will be introduced, along with the challenges of multiparameter optimization (efficacy, toxicity, solubility).

We'll also delve into real-world examples to illustrate how SAR principles are applied in practice. The episode will explore the use of VR applications like Nanome for SAR visualization, showcasing how technology is transforming drug discovery. Furthermore, we'll discuss the concept of "fail fast, fail cheap" and its importance in early-stage drug development. The episode will conclude with a look at preclinical drug development, highlighting the importance of considering metabolic soft spots and the ADME profile of a drug candidate.