Navigating the Pharma 4.0 revolution: how AI-enabled applications and predictive modelling shaped pharmaceutical development in the post-pandemic era: a systematic review

Pharma 4.0 is touted to make processes more efficient and resilient to unforeseen circumstances, boosting productivity, speed and accuracy of pharmaceutical systems. Besides operational stability, these technological implementations could potentially improve clinical outcomes. AI-enabled Pharma 4.0 applications and predictive modelling are utilised in pharmaceutical development for the discovery of new compounds that could potentially be used as drugs for COVID-19. This systematic review examined how contemporary Pharma 4.0 technologies have impacted pharmaceutical development in the post COVID-19 pandemic. A systematic review following the “Preferred Reporting Items for Systematic Review and Meta-Analyses” (PRISMA) method was carried out on scientific peer-reviewed literature, covering the period from 2023 to 2025. From the PubMed and Scopus databases, 593 articles were identified and 57 were included for further analysis. Performance metrics describing the reported predictive models used in research areas were identified and descriptive statistics were used to present the findings. We found that predictive models of Pharma 4.0 technologies were predominantly concentrated in early-stage drug discovery and computational research, with reported benefits of more efficient and accurate processes. Our current findings on the nonclinical performance metrics observed good use cases for drug discovery, but limited insights on the clinical applications that these recent technological developments had on the pharmacological effects. These technologies enhanced complex processes, facilitated predictive models to optimise product development in the early phase of the product life cycle.