1. How to Bring AI Medical Devices to the Market. A Case Study From Roche (Gloria Macia)

Healthcare is emerging as a prominent area for AI applications, but innovators aiming to seize this chance face one major issue: achieving regulatory compliance. Using a real industry case study, Gloria Macia walks you through the current American and European regulatory frameworks for medical devices and provides a step-by-step guide to market for AI applications, highlighting the main challenges and pitfalls to avoid as well as the key issues a company needs to consider to succeed in this endeavor.

2. The Role of TensorFlow, PyTorch, and Friends in a Medical Device – the Regulatory Perspective (Oliver Haase)

Machine learning libraries such as TensorFlow, PyTorch, or XGBoost play a key role in the development of virtually any ML-based software as a medical device. From the regulatory perspective, they are third-party software that must be validated to be run in a medical device. This presentation will give an overview on why ML libraries are much more critical than 3rd party software in traditional software development, and how validation reuse can be leveraged to minimize the validation effort.