Transform patient-driven healthcare: Synthesize RWE and AI
The future of healthcare is here, and it's powered by real-world evidence (RWE) and artificial intelligence (AI), transforming patient care and clinical decision-making.
A poll of attendees found that almost half (46%) had invested in AI to enhance their use of rea world data (RWD), with a further 33% stating that they were considering such an investment.
While our attendees were somewhat split in their uptake of AI to date, panelists were unanimous in their verdict that the technology can have a profound impact on the use of RWD in healthcare.
Moderna’s Andrew Rosen highlighted the opportunity for personalized medicine through intelligent analysis of RWD data, stating, "We can enable better clinical decision-making, treating patients not just as their disease, but considering the complete constellation of properties that make up that patient."
This approach goes beyond focusing solely on the disease, taking into account various factors such as clinical, demographic, personal and behavioral data. By tailoring treatments to the patient’s needs, healthcare professionals can optimize outcomes and improve overall patient wellbeing.
Preventive medicine emerged as another significant application of AI and RWD, as mentioned by Rosen, who spoke of the potential to develop models to detect disease and intervene earlier, enabling better patient outcomes.
The utilization of virtual cohorts garnered significant attention as an effective strategy to improve medicines. Novartis’ Nicholas Kelley highlighted the value of virtual cohorts, describing those originating from disease registries and other sources as “very interesting”.
"They can help enter new indications, enrich trials through progression modeling, risk prediction, and understand the generalizability of the population in a real-world setting," he added.
Leveraging diverse data sources through virtual cohorts can provide valuable insights into patient populations, aid in identifying new indications for treatments and enhance the understanding of treatment efficacy in real-world scenarios.
Nonetheless, panelists and attendees addressed the challenges that come with using patient data, with data privacy highlighted as the greatest challenge the industry currently faces. Just less than half (45%) of attendees identified data privacy as the greatest challenge, followed by 15% who selected the transparency and ‘explainability’ of AI algorithms.
This can, however, be remedied by fully understanding data privacy laws and regulations when using AI. Viatris’ Kelly H. Zou, stated, "One way to deal with this problem is really using federated data [as these] data models ensure that data does not need to travel. You can use distributed research networks and safeguard the data." This approach allows for the protection of patient privacy while enabling the utilization of data for research purposes, maintaining the necessary level of transparency and accountability.
Conducting a thorough assessment of data quality is crucial for AI interpretation, as emphasized by Cegedim's Gilles Paubert. He stated, "Assessment of data quality is really essential. This involves inspection, describing missing data, addressing potential measurement errors, and understanding the underlying mechanisms." The examination of these aspects serves as the foundation for generating accurate and meaningful insights from AI models.
Leveraging AI algorithms and comprehensive datasets allows healthcare professionals to make informed decisions, tailor treatments, and improve patient outcomes. We invite you to explore the full webinar here to gain deeper insights from the panelists, and explore other topics discussed, such as challenges associated with deploying predictive models to healthcare professionals and biases in datasets. Take action and unlock the transformative possibilities of AI in healthcare!
Experts that contributed:
- Kelly H. Zou, Head of Global Medical Analytics & Real World Evidence, Viatris
- Nicholas Kelley, Director Data Science & AI Portfolio Strategy & Innovation, Novartis
- Andrew Rosen, Senior Director, Integrated Evidence Team Lead, Moderna
- Gilles Paubert, Senior Vice President, Global Head of Cegedim Health Data
Watch the full webinar and learn more about RWE and the role that AI plays in analyzing this data on here.