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Using Machine Learning to Mitigate Failures and Reduce Costs in Clinical Operations

Elvin Thalund
Director, Industry Strategy

On September 22, 2020, Oracle Health Sciences presented on the impact of machine learning at the US DPHARM disruptive innovation conference with regards to how business knowledge is essential to the success of machine learning, and how machine learning will lead to operational efficiencies and cost reductions in clinical operations.

The DPHARM conference challenges and reports on innovation designed to shake up the way clinical trials are designed and implemented in order to reduce patient/physician burden and drive greater efficiencies.

The presentation introduced examples on why technology is not the limiting factor in a successful implementation of machine learning. A summary of what is required to implement machine learning in clinical operations, and especially study startup was discussed, along with how machine learning will lead to greater trial success and ultimately significantly reduce the $2.6B average cost of developing a clinical product.

Using Machine Learning to Mitigate Failures and Reduce Costs in Clinical Operations

What to learn more?

Download the ChromoReport Spring 2020 report on the Importance of Leading Indicators to Machine Learning Predictive Models.

Download the ChromoReport Winter 2019 report on Proactive Planning with Predictive Analytics.

Learn more about optimizing your study startup.

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