Prospects for the Future: Artificial Intelligence in Pharmaceutical Technology

Abstract

Artificial intelligence is one of the emerging technologies being utilized in various areas in the pharmaceutical sector to optimize different process parameters, which leads to the development of novel drug delivery systems very efficiently. Astonishing evolution in AI technology and machine learning brings out transformational productivity in the formulation, drug discovery, and testing of pharmaceutical dosage forms. Artificial intelligence utilizes various computational tools and engineering technologies to fabricate varying dosage forms with high therapeutic efficacy and precision. AI algorithms efficiently analyze substantial biological data of proteomics and genomics, which allow researchers to find out the target site and also to predict the interactions with potential drug molecules. This phenomenon permits a targeted approach to drug discovery thereby enhancing the probability of effective drug approvals. Artificial Intelligence (AI) allows the development of intelligent modeling, resolving issues, and decision-making to create efficient data handling. Artificial intelligence plays a very crucial role in various pharmaceutical sectors including drug discovery, formulation and development of novel dosage forms, development of new analytical techniques, development of design of experiments, sales and marketing, quality assurance, clinical trials, hospital pharmacy, etc. Various AI-based tools like Artificial Neural Networks (ANNs) or Recurrent Neural Networks (RNNs) are successfully utilized in the field of drug discovery and newer drug delivery systems. Several drug discoveries are being made in pharmaceutical fields using AI technology in combination with quantitative structureproperty relationship (QSPR) or quantitative structure- activity relationship (QSAR), which support evidence-based accurate and precise results. Additionally, de-novo design is employed to invent significant new drug molecules with the desired quality. AI algorithms are helpful in experimental design, which can accurately determine the pharmacokinetic parameters and toxic effect of drug molecules. They also allow the identification of impurities and the optimization of their concentration in the product to formulate an effective dosage form. AI-based technology can be applied to optimize the drug excipient ratio in the formulation of a new modified drug delivery system including sustained, delayed, or immediate release formulation. Formulation of personalized medications as per patient’s need is one of the novel approaches that can be possible by the utilization of AI tools, leading to more precise rational treatment and improved patient compliance. The content incorporated further highlights more detailed information on AI tools and their wide applications in various pharmaceutical departments including drug discovery, process optimization, designing novel delivery systems, testing, pharmacokinetics/ pharmacodynamics (PK/PD) studies,