Drug Development and Delivery recently published an article written by Saama’s Senior Director of Clinical Analytics Innovation, Srini Anandakumar, on the topic of reducing clinical cost budget variations:

“Data-driven decisions offer higher potential in controlling the schedule and cost drivers, thus enabling reduction in schedule and budget variance. This article explores an approach for how sponsor’s operational data, coupled with syndicated data and Real World Evidence (RWE) data, can enable predictive analytics on clinical cost drivers using a clinical big data and Machine Learning (ML)-enabled platform. The predictive clinical cost drivers can be used to create adaptive clinical financial budgets that include baseline spend, actual spend and projected expenses. This approach also provides details on automating the budgeting of the clinical trial financials based on trial assumptions and re-budgeting based on revised trial assumptions (as part of trial execution).”

Read the full article here.

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