#One key iqvia series#

PVO can address talent shortages and knowledge gaps by providing access to customised automation and advanced tools from subject experts. Over the past decade, many biopharma companies have adopted alternative delivery models to increase their PV capacity and efficiency, from full-scale redesign to outsourcing their PV collection and analytical functions (pharmacovigilance outsourcing – PVO). This includes creating next-generation digital learning systems that can increase the efficiency and cost-effectiveness of generating richer insights on product quality and patient safety. The obligation for biopharma companies to report AEs that arise from the unique patient insights and increased data being collected means many biopharma companies are adopting automation and advanced analytics to improve transparency across reporting methods and build trust in their PV systems. This rise in real-time data from such sources requires mature processing systems with the capacity to perform advanced multimodal analysis to derive value. connected medical devices, such as wearables, are increasing the volume of data that can be integrated into PV.8 The heterogeneity adds difficulty to identifying a signal and defining a relationship between the drug and the expressed effect social media is increasingly used as a platform to share personal health-related insights, however, the terms used for medical concepts are often inconsistent and difficult to extract.7 As the increased availability of data sources, data and information on AEs continue to rise, new challenges are emerging, for example: The overarching aim of the report is to explore how AI can improve patient outcomes by detecting real-time adverse events (AEs) more efficiently and effectively and how it can be applied to interoperable health data, generated within PSPs to improve the remote monitoring of patients and deliver safer, more personalised and precise treatment options promptly.ĭespite the volume of ICSRs increasing year-on-year, it is estimated that more than 90 per cent of AEs go unreported. It explores the potential of AI to improve the last step in the value chain – specifically post-market PV and PSPs (figure 1).

#One key iqvia series#

This is the sixth and final report in our series on the role of AI in driving biopharma’s digital transformation. This could enable innovation in new products and services and improve customer engagement and process efficiency. We concluded that digital transformation, with advanced technologies such as AI, was the next logical step in the evolution of biopharma. Improving patient support is a critical step in the biopharma value chainĪs we highlighted in our 2019 overview report, Intelligent biopharma: Forging the links across the value chain, the pace and scale of scientific innovation are improving patient engagement and experience, creating new business models and transforming the biopharma industry.