A Study on the Use of Machine Learning (ML) In Translational Medicine

Abstract

: The vast progression of Internet web facilities, along with advances in computer technology and algorithm development, in addition to existing developments in high-throughput methodologies, facilitate the research establishment to obtain access to biological sets of data, medical evidence, and many database systems usually contain millions of pieces of scientific knowledge. Recent years have seen an explosion in the use of Artificial Intelligence (AI) and Machine Learning (ML) to make sense of massive amounts of data in the pharmaceutical industry, completely changing the face of research and innovation. . Author discusses the potential of ML to revolutionize the field of medicine by providing an overview of its applicability in drug research and development. The possibilities for applying ML methods to the field of Pharmacometrics are explored since they have the potential to radically alter the way model-informed drug discovery and development is conducted. Furthermore, the author suggests that cross-functional groups comprised of specialists in Clinical Pharmacology, Bioinformatics, or Biomarker Technology were necessary to fully utilize the potential of AI/ML-enabled Translational and Personalized Medicine.