STM Journals Peer-reviewed research from Consortium e-Learning Network

Research & Reviews: A Journal of Drug Design & Discovery Review Article

A Study on The Impact of Artificial Intelligence in Pharmaceuticals

  1. Vedant V. Patil Department of Pharmaceutics, Poojya Sane Guruji Vidya Prasarak Mandal
  2. Roshan.m.Chaudhari Department of Pharmaceutics, Poojya Sane Guruji Vidya Prasarak Mandal, Shahada
  3. S.P. Pawar Department of Pharmaceutics, Poojya Sane Guruji Vidya Prasarak Mandal, Shahada,

Abstract

The main goal of artificial intelligence (AI) is to create intelligent modeling, which facilitates knowledge imagination, problem-solving, and decision-making. AI is becoming more and more significant in several pharmacy domains, including polypharmacology, hospital pharmacy, drug discovery, and drug delivery formulation development. Various types of artificial neural networks (ANNs), including deep neural networks (DNNs) and recurrent neural networks (RNNs), are utilized in the development of drug delivery formulations and in drug discovery. The technology’s promise in quantitative structure-property relationships (QSPR) and quantitative structure-activity relationships (QSAR) has been supported by several drug discovery implementations that have been studied thus far. In terms of desired/optimal properties, de novo design also promotes the creation of significantly more innovative medical substances. This review paper discusses the application of AI in pharmacy, specifically in areas, such as polypharmacology, the development of drug delivery formulations, drug discovery, and hospital pharmacy. A branch of computer science called artificial intelligence makes it possible for machines to function efficiently. Because of its capacity to manage complex data processing tasks, which has enhanced workflow efficiency, its use in pharmaceutical technology has expanded. Reducing operating expenses while enhancing safety, precision, and efficiency. It might help us conserve time and resources while enhancing our comprehension of the relationships among different formulations and process parameters. Research in artificial intelligence (AI) has surged, and it has been shown that AI technology can analyze and understand data across several key areas in pharmacy, including hospital pharmacy, formulation design, and drug discovery.

Keywords

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