Getting a new medicine to market is a marathon, not a sprint. Or perhaps a better analogy is a steeplechase, where competitors must overcome gruelling obstacles on their way to the finish line.
Clinical trials are one of the biggest hurdles on the route to market and they’re getting more challenging yearly. While the industry’s response to the pandemic has proven that we can set up and deliver large-scale trials much faster than we previously suspected, it has also raised the bar. Accelerated timelines will soon become the rule rather than the exception.
At the same time, we’re seeing massive innovation in the type of clinical trials companies run. Streamlined master protocols such as those used in the COVID-19, Recovery and Solidarity trials as well as decentralised or adaptive trials can help expedite and speed up the identification of valuable new therapies. Companies are also exploring the potential of augmenting trial protocols with real-world evidence, such as electronic medical records and genomics data and incorporating technologies like machine learning and neural networks in their analysis and submissions.
Yet, despite all this progress, there’s still a strong sense that there are more opportunities for collaboration and standardisation in how trials are run. A lack of standardisation in clinical trial management platforms, standards, workflows, and tools makes it difficult for stakeholders to collaborate effectively, share data securely, or ensure reproducible results.
As trials grow more extensive, more data is used to drive therapeutic insights, and more participating organisations are involved from around the world in each test; industry associations are discovering the latest technologies that are harmonising on ways to use cloud technology and the capabilities that it offers. Industry organisations like PHUSE and TransCelerate are producing white papers calling for a “statistical computing environment” or a “statistical analytics framework” that can make clinical trial management and analytics more tractable.
Companies are recognising the need to adopt these technologies. In many ways, SAS has been pioneering multi-lingual cloud-native technologies in the context of the highly regulated Life Science industry. While these organisations are far from achieving the hyper-automation, SAS is helping other regulated industries implement. We have worked with big and boutique pharmaceutical companies and clinical research institutions for over 20 years to help them on the journey. We refined our best practices and progressive ideas into a platform that we now call SAS Life Science Analytics Framework.
An innovative Framework
SAS Life Science Analytics Framework (LSAF) provides a clinical data repository with complete governance and version control for all data assets, a robust statistical computing environment, collaborative workflows, regulatory reporting, and management insight capabilities. It’s already in use at some of the world’s largest pharmaceutical companies and specialist players like Santen, Gunvatta, and Ferring Pharmaceuticals.
“SAS Life Science Analytics Framework gives you the capability to do the workflows right… Everybody is looking into one integrated and streamlined system. Everything is there in one place, accessible in real-time.”
- Bhawna Goel, CEO of Gunvatta
If you would like to learn more about how LSAF can help your business accelerate the delivery of clinical trials and provide a rock-solid environment for reproducible analytics, check out our new eBook, Accelerating clinical trials innovation. You can download here.