Is Clinical Trial Analytics Innovating as Fast as the Rest of Pharma?

▤ Summary

In this post we’ll look at 6 key areas of operation that play a role in clinical data analytics, and investigate problems being addressed and share some examples of solutions being implemented by modernization pioneers. On top of this, new talent coming into organizations aren’t as familiar with legacy programs and are generally more comfortable using tools they’ve been trained on during formal education. Containers offer pharmaceutical companies the ability to have multiple little servers that are set up for individual use cases (e.g. different software versions, programming languages, packages, validation requirements etc.). We’re careful to advise our clients to consider how they’ll create a level playing field when it comes to using any combination of languages to ensure they’re making the best use of their compute resources. • Visualization tools are helping companies make sense of data through graphs and charts • R Shiny is increasing in popularity, but how to deploy is proving a tricky obstacle • Data volumes are increasing, so extra attention needs to be given to environment architecture Regulators are required to be a bit risk-averse and remain able to accept submissions from companies all over the world with varying levels of access to technology and advancement.

▦ Linked Companies

d-Wise

$10M to $25M