Replica Analytics - An Aetion Company

Session 4: Applications of Synthetic Data in the Life Sciences Industry II

Title: Applications of Privacy Enhancing Technology to Data Sharing at a Global Pharmaceutical Company

Speaker: Stephen Bamford Senior Director Clinical Data Standards & Transparency, IDAR, J&J Innovative Medicine

Abstract: J&J has been at the forefront of the recent pharmaceutical industry trend toward more transparency and sharing of clinical trials data; committing early on to make its data available for both internal and external innovation. Janssen is also committed to protecting patient privacy and giving individuals a voice on how their data is used and disclosed.

This presentation will outline Janssen’s data sharing initiatives and describe how it is using leading-edge privacy enhancing technologies (PETs) to mitigate privacy risks and find the right balance between innovation and privacy.

The move to adding Synthetic clinical trial data to the available PETs has vastly increased the number of use cases and has opened a new level of sharing clinical trial data within the company.

Title: Applications of Synthetic Data to Accelerate Data Access & Insight Generation

Speaker: George Kafatos Director – Data & Analytics Int’l team lead, Amgen

Abstract: Real-world data (RWD) are increasingly recognised as playing an important role in guiding drug development and understanding healthcare delivery. This is in part due to the growing availability of RWD sources and the advances in health informatics.

However, access to patient-level data, particularly in Europe and Asia, is complex due to governance rules to protect patient privacy. This presentation will describe use cases for leveraging synthetic data in order to accelerate analytics on otherwise restricted data sources and gain insights to inform patient care.

Following the acquisition of Replica Analytics by Aetion, the generative AI technology previously known as Replica Synthesis is now Aetion® Generate and continues to create privacy-enhancing synthetic data.