Rethinking Nature’s Pharmacy: AI Era and Natural Product Drug Discovery

Natural products (NPs) have long been a cornerstone of pharmaceutical innovation, contributing to approximately 50% of FDA-approved drugs over the past four decades. However, traditional NP drug discovery faces significant hurdles, including laborious isolation processes, biodiversity constraints, and low hit rates in high-throughput screening. These hurdles often extend the development timelines to 10-15 years with costs exceeding $2 billion per drug. Artificial intelligence (AI) emerges as a transformative force, leveraging machine learning (ML), deep learning (DL), and generative models (Gen. AI) to expedite these processes. AI facilitates virtual screening of vast chemical libraries, predicts molecular interactions with unprecedented accuracy, and designs novel NP-inspired scaffolds, potentially reducing discovery time by up to 70%. This interdisciplinary approach not only addresses unmet medical needs but also aligns with global sustainability goals, potentially increasing success rates from