Revolutionizing Drug Discovery

摘要

Historically, drug discovery was dominated by relentless scientific experiments and repetitive laboratory procedures. However, with the introduction of computational technologies and multidimensional data, this process has undergone significant transformation. This chapter emphasizes the pivotal role of AI, ML, DL, NLP, and robotics in contemporary drug development. AI, with its evolving intelligence, amplifies decision processes when supported by comprehensive data. The focus remains on the capabilities of ML, DL, and NLP in the pharmaceutical industry—from accurate drug interaction predictions to the formulation of specialized treatment methods. Robotics has emerged as a vital tool, streamlining the management and distribution of medications. By leveraging AI methodologies such as random forest, SVM, and others, it is feasible to predict drug outcomes, identify new pharmaceutical benefits, and foresee any adverse side effects. It is notable how AI is the cornerstone for innovations including personalized medications, digital drug analysis, original drug formulation, and data-driven predictions. While these technological breakthroughs signify a monumental evolution in drug discovery, there exist challenges like data gaps, unclear models, and ethical considerations. This chapter provides a comprehensive overview of the present drug discovery techniques, outlines prevalent challenges, and suggests potential solutions.