You are working with a pharma or biotech company with active real-world evidence projects. Your company has an established Phase II/Phase III clinical trial pipeline, and you are looking to smooth the transition between real-world research and clinical trial research.
Your challenge
Open-source technologies such as R and Python have long been used in real-world research. As their adoption in clinical research and development continues to grow, there is an increasing need to bridge the gap between real-world evidence and clinical trial research. The goal is to bring these domains closer together, enabling insights from real-world data to be more effectively leveraged within clinical trial settings
Our solution
entimICE FastTrack offers a validated data science platform with flexible hierarchies, workflows, and permission structures, enabling both regulatory and non-regulatory activities to be supported within the same environment.
Real-world research projects can be carried out using R and Python with the flexibility to leverage a wide range of packages and modules, and with minimal constraints on workflows and traceability.
When needed, work can transition seamlessly to more controlled areas within the same platform, where clinical trial analysis for regulatory submissions is performed using validated and standardized execution environments for SAS, R, and Python.
In these regulated areas, workflows and traceability are tightly managed, guiding users efficiently through each step of the submission process.
entimICE FastTrack simplifies and speeds all of these processes in research projects.
Take a closer look at the features and performance benefits we’ve developed to bring more speed and precision to every stage of your clinical trial services.
