Influence of artificial intelligence in modern pharmaceutical formulation and drug development

Abstract

Background Artificial intelligence (AI) revolutionized the formulation and development of modern pharmaceuticals. With the help of AI, researchers can now optimize drug design, develop formulations, and streamline clinical trials in a much accurate and efficient way. Drug development might be greatly expedited and time-consuming procedure; however, with the help of AI this are significantly reduced. Main body of abstract The main advantages of AI in pharmaceutical formulation are its capacity to analyse vast amounts of data and spot patterns and connections that human researchers would miss. Various tools and technologies, such as ANN, fuzzy logic, neuro-fuzzy logic, and genetic algorithm are used for analysing the date, of which ANN is popular and mostly used. AI enables the discovery of novel pharmacological targets and the creation of more potent medications. AI may also be used to improve medication formulations by forecasting the solubility, stability, and bioavailability of drug candidates, increasing the likelihood that clinical trials will be successful. AI is also applied in designing clinical trials, reducing the time and cost of the process by identifying patient populations that are most likely to benefit from the treatment. Additionally, AI can monitor patients during clinical trials, detecting real-time adverse effects and adjusting dosages to improve patient outcomes. Conclusion AI is a potent pharmaceutical formulation and development tool, allowing researchers to analyse vast amounts of data, optimize drug formulations, and streamline clinical trials. As technology develops, experts anticipate that AI will increasingly show a crucial part in drug development, enabling faster, more efficient, and more effective treatments for various diseases.

The Role of AI in Drug Discovery

“…[9][10][11] This technology has the potential to significantly streamline the drug discovery pipeline, from computational chemistry and molecular biology to the optimization of lead compounds and the design of clinical trials. [12] AI applications facilitate tasks such as protein-ligand docking, molecular dynamics simulations, virtual screening, and de novo drug design with unprecedented accuracy, opening new therapeutic avenues and expediting the identification of promising drug candidates. [10,13,14] Moreover, AI's role in systems pharmacology, drug-target interaction predictions, and clinical trial design is reshaping drug development strategies.…”