Abstract
The pursuit of bioactive compounds from natural sources remains central to early-stage drug discovery, offering structurally diverse scaffolds with significant therapeutic promise. This paper explores the optimization and sustainability of contemporary extraction techniques—such as Supercritical Fluid Extraction, Microwave-Assisted Extraction, Ultrasonic-Assisted Extraction, and Deep Eutectic Solvents—as environmentally responsible and highly efficient alternatives to conventional methods. These technologies demonstrate enhanced selectivity, reduced solvent usage, shorter extraction times, and superior yields, aligning with the principles of green chemistry. Through practical case studies, including the extraction of curcuminoids from turmeric and phenolic-rich compounds from Carica papaya leaves, the paper highlights how process optimization and advanced analytics contribute to improved purity, reproducibility, and scalability. The integration of artificial intelligence and predictive modelling further streamlines yield prediction and decision-making in process development. Key findings emphasize the critical role of optimized extraction in lead identification and preclinical testing, ensuring that candidate molecules possess the desired pharmacological activity and safety profiles. Despite substantial advancements, challenges remain in scaling laboratory successes to industrial applications, harmonizing regulatory standards, and adopting universally applicable green solvents. This study concludes with recommendations for best practices in medicinal chemistry, including the adoption of hybrid extraction models, the use of data-driven optimization tools, and cross-disciplinary collaboration. By aligning extraction science with sustainability and innovation, the pathway from natural products to clinical candidates can be made more efficient, ethical, and impactful.