Using AI to Automate Common Tasks: Q&A with Dan Sheeran

Dan Sheeran
General manager
Healthcare and Life Sciences
AWS

Faruk Capan, chief innovation officer at EVERSANA and CEO of EVERSANA INTOUCH, and Dan Sheeran, GM of healthcare and life sciences at AWS, spoke with Pharmaceutical Executive about how the two companies worked together to launch a platform that uses AI to automate most of tasks associated with the MLR process. In the second part of this interview, Sheeran discusses the history of this collaboration.

Pharmaceutical Executive: What made a collaboration with EVERSANA a good fit for AWS?
Dan Sheeran: At AWS, our vision for healthcare and life sciences is to empower organizations with secure, scalable AI and cloud solutions that improve patient lives. EVERSANA’s deep domain expertise in life sciences commercialization, particularly around Medical, Legal, and Regulatory (MLR) review. By building on Amazon Bedrock, EVERSANA was able to harness the power of generative AI to solve an industry pain point, reducing administrative burden while maintaining regulatory rigor. Their ability to integrate technology with real-world healthcare challenges aligned perfectly with AWS’s mission to accelerate innovation and improve outcomes across the healthcare and life sciences industry. We continue to drive innovation through AI with EVERSANA in acceleration of drug commercialization, clinical trials, and improving patient experiences.

PE: How big is the need for this type of solution in the life sciences sector?
Sheeran: The need is substantial. MLR review is one of many time-consuming and resource-intensive processes in the commercialization journey. Teams are often overwhelmed by the volume of materials and the complexity of ensuring compliance, which can slow time to market and increase the risk of errors. With growing pressure to bring therapies to patients faster, without compromising quality or safety, life sciences companies are looking for smarter, scalable ways to streamline operations. That’s where AI-powered platforms like EVERSANA ORCHESTRATE MLR come in, offering real impact by improving accuracy and allowing users to focus more on patient outcomes.

PE: From the AWS team’s side, how have your technologies like Bedrock helped in the development of this solution?
Sheeran: Amazon Bedrock played a pivotal role in the development of this solution by providing a secure, scalable, and fully managed platform for building generative AI applications. With Bedrock, EVERSANA had access to a diverse selection of foundation models from leading AI providers, along with the ability to securely customize these models to meet their specific needs. Bedrock's fully managed, serverless environment allowed EVERSANA to focus on developing a solution that automates up to 90% of common MLR review tasks, without sacrificing security or compliance.

PE: Talk about how important data privacy and security is as the tool was built to ensure compliance with industry standards?
Sheeran: Data privacy and security are critical when developing AI tools for the life sciences sector, especially those that support regulatory functions like MLR. As we built this solution in collaboration with EVERSANA, upholding industry standards was essential. With Amazon Bedrock, we were able to provide a secure environment where sensitive medical and regulatory data could be used safely. This allows life sciences companies to utilize generative AI while maintaining control over how their data is used, meeting regulatory requirements, and protecting patient and proprietary information at every step.

PE: What’s the future look like for your work with EVERSANA?
Sheeran: Going forward, AWS and EVERSANA are continuing to build out a robust pipeline of innovation, working backwards from our life sciences customers to find new ways to solve long-standing industry challenges and bring effective therapies to patients in need.