How AI Can Revolutionize the Pharmaceutical Industry

Abstract

The pharmaceutical industry has seen a lot of transformation in the last five years because of technological innovations such as AI. AI-based technologies such as ML and DL are revolutionizing the sector and making processes such as drug discovery, research, dose optimization, therapeutic drug monitoring, drug repurposing, predictive analytics, and clinical trials much easier. Drug development is a complex, time consuming, and labor-intensive process. In some instances, drug development takes up to 10 years and a significant amount of investment. However, AI-based technologies are showing a lot of promise when it comes to simplifying the process and making it less-time consuming. The drug development involves a lot of data. AI-based technologies such as ML shows a lot of promise when it comes to analyzing and managing these large volumes of data making the process more manageable. AI has also simplified the process of identifying therapeutic targets. AI is also being used in drug design to help in making predictions of 3D structure of the target protein and predict drug-protein interactions. Other areas where AI is being used in drug discovery are de novo drug design, optimizing clinical trials, predictive modelling, and precision medicine. Despite the advantages that AI offers in pharma, it has its limitations. For instance, ethical considerations regarding patient data, privacy, and confidentiality remains a key issue. Risk of bias also raises ethical concerns that should be considered. Other limitations are limited skills that make it difficult to optimize AI, financial limitations that make it difficult to invest in AI, and data governance challenges. Keywords: Artificial intelligence (AI), machine learning (ML), deep learning (DL), drug discovery, clinical trials