AI & Clinical Trials: Poised for Disruption

Posted by Arun Shastri on Wed, Sep 11, 2019

This blog post is the third in a series on the impact that AI will have on different business aspects of pharma.

We always tell our clients to start small with AI. As Pratap Khedkar shared in my first interview, it’s important to start with clear, specific use cases. For some aspects of the business, it may take some time to carefully consider what these specific use cases are and what opportunities AI can create. Clinical trials present no such difficulties. The opportunities to improve efficiencies are numerous and clear, and AI has begun to make an impact. The industry is aware of the inefficiencies that abound in clinical trial design and execution and is eager to solve them.


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Boost Patient Recruitment With Data-Centric Trial Planning

Posted by Venkat Sethuraman on Fri, Aug 16, 2019

Denise N. Bronner, Gaurav A. Singh and Ray Zhong co-wrote this blog post with Venkat Sethuraman

A common struggle for pharmaceutical companies is poor patient recruitment for clinical trials. As a consequence, 80% of clinical trials fail to meet their enrollment goals, suffer delayed timelines and absorb skyrocketing R&D costs. Ultimately, the patient suffers from delays in the release of needed therapies. Currently, pharmaceutical companies are partnering with trial matching startups to enhance clinical study design, matching and data collection. With analytics and platforms, pharmaceutical companies are beginning to streamline the clinical trial process in hopes of increasing new entrants to the market.


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