NVIDIA Isaac for Healthcare is an AI developer framework that addresses the challenges faced in healthcare robotics by integrating data collection, training, and evaluation pipelines for both simulation and hardware. The Isaac for Healthcare v0.4 release simplifies the process for MedTech developers through the SO-ARM starter workflow, which facilitates the creation of autonomous surgical assistance robots by providing an end-to-end pipeline from simulation to deployment. This workflow utilizes a mixed training approach, combining synthetic data generated in simulations with real-world data for a comprehensive model training process that addresses the limitations of both environments. It includes a three-stage pipeline: data collection using both simulation and real-world teleoperation, model training on combined datasets, and policy deployment for real-time inference on physical hardware. The framework's capacity to generate over 93% of training data synthetically highlights the potential for reducing costs and overcoming the limitations of real-world data collection. The integration of simulation with real-world applications ensures that developers can train and refine skills in a safe environment before transitioning into actual operating rooms, enhancing the practical application of robotics in healthcare.