Data-Driven Predictive Analytics Framework for Combating Antibiotic Resistance through AI-Enabled Drug Discovery and Surveillance

Abstract

Antibiotic resistance (AR) has become a pressing concern to the world at large. This has been the case as a proactive strategy can now only be achieved through the use of intelligent solutions toward curbing AR. Research has shown that the development of antibiotics has been hampered by the long drug development process. Moreover, the increase in resistance among microbes has been faster compared to the development of effective antibiotics. This researcher introduces a Data-Driven Predictive Analytics Framework. This has been based on Manik et al. (2018-2023), as the researcher has used AI solutions for the development of medications. This has progressed from drug development to the usage of analytics for chronic and neurological disorders. This has finally led to the development of the Data-Driven Predictive Analysis Framework. This will consist of four aspects: (1) the development of data from multiple sources including genomics and phenomics. This will also involve the usage of the environment. (2) This study will apply analytics solutions to predict the development of AR. (3) AI solutions will also incorporate solutions to develop medications. This has been the final aspect as the researcher concludes the drug development framework. (4) This will involve the development of solutions across the world. This has been the case as the world has been suffering due to the lack of effective antibiotic development. This has been based on the CDC as well as WHO guidelines.