Principal Customer Solutions Manager Amazon Web Services (AWS), United States
Life sciences is being transformed through embracing technology advancements that leverage cloud computing, instrument connectivity, and the power of data to drive innovation. Our research shows that leaders in the precision medicine space, are embracing change to adopt these emerging best practices to yield quicker results. We will breakdown the complexities for researchers, scientists, and technologist into four components: 1/Data Management, 2/Industry Regulations, 3/Cloud Elasticity , and 4/How Artificial Intelligence (AI) is being used to accelerate precision medicine.
We are living in a time of enormous clinical and technology innovation with the hope of achieving the future of medicine. This future state will dramatically improve patient outcomes with state-of-the-art gene and cell therapy delivering patient-centric medicine. Life sciences organizations are challenged with reinventing how they operate to decrease the cost of care for these new therapies. Drug discovery organizations are embarking on a digital transformation journey using the agility of the cloud and high performance computing (HPC) to accelerate results, and leveraging automation to reinvent how their laboratories operate. Industry leaders are pushing the boundaries of modern manufacturing techniques integrating real-time sensors and computer vision at the edge to reduce downtime and make preventative maintenance a reality. Scientists are modernizing their workflows using electronic lab notebooks and storing refined intelligence into data warehouses, which reduces friction and allows therapeutics to be commercialized quicker to market. In the life science industry, “the process is the product,” trends in automated GxP validation, leveraging cloud infrastructure as code for traceable workflows that are easily auditable to create a continuously validated environment with repeatable experiments. Digital transformation is happening all around the globe, the cloud’s elasticity lowers the barrier to entry for startup organizations. Scientists can run tens of billions of tests in a single day, use Alexa-voice enabled lab equipment to reduce errors, and use AI to develop more targeted clinical trials for precision medicine. While these innovations touch different parts of the value chain, they are each built on a common foundation of cloud modernization. Modern labs are adopting data-driven approaches to create the lab of the future with connected lab equipment. This connectivity lays the building blocks for having real-time data from smart instruments to drive innovations in cell and gene therapy with connected bioreactors, robotics, and computer vision to monitor experiments. The power of the cloud and machine learning is now more easily accessible to scientists and researchers to accelerate the time to design and test hypotheses. The journey first starts with a data aggregation strategy. The lab of the future is here today. Helping improve your workflow, reducing support costs, improving lab uptime and allowing you more time to innovate and improved patient outcomes.