Clinical data platform build
Medical equipment manufacturer
Wavicle helped this medical equipment manufacturer build a new, centralized clinical data platform to improve data accessibility, create clinical trial reports without external dependencies, enhance product quality, and lay the foundation for future AI/ML projects.
Architecture & Engineering
Build & Migrations
Data Management
Amazon QLDB
Amazon Redshift
Amazon S3
Amazon SageMaker
AWS Glue
AWS Lambda

Clinical data platform build

Medical Equipment Manufacturer Saves Millions of Dollars With a New Clinical Data Platform

This medical equipment manufacturer conducts regular clinical trials to ensure the safety and efficacy of their products. Previously, they transferred the trial data to an external partner who created reports that were then sent to a regulatory body for final validation. The growing data volumes and shifting report requirements raised expenses and made engaging with the external partner difficult. Moreover, the lack of direct access to their data assets posed a barrier to executing advanced analytics projects in the future.


To address these challenges, the manufacturer approached Wavicle to build an in-house clinical data platform that centralizes and stores the results of each clinical trial, creating a streamlined and self-reliant solution that they project will save millions of dollars long-term in third-party expenses.


Difficulties arising from the lack of direct access to data

With the aim of ensuring product safety, this medical equipment manufacturer sent their clinical trial data to an external partner to generate detailed reports. This partnership was initially formed to streamline the reporting process and make it more efficient. However, several challenges and complexities emerged over time.


One of the most significant issues was the sheer volume of data involved in these clinical trials. As the manufacturer expanded its research and development efforts, the data generated from these trials grew substantially. Furthermore, the manufacturer couldn’t directly access the data independently of the third-party company, which hindered additional data exploration and analysis and would prevent future AI or machine learning projects.


The variability in report specifications for each clinical trial was another challenge. With different trials requiring different types of reports and analyses, continuously adapting to these changing requirements became costly.


The manufacturer decided to leverage Wavicle’s data and analytics expertise to regain control over their data assets, improving data accessibility and quickly gaining essential insights from clinical trial data. Through this strategic move, they aimed to reduce costs, streamline overall operations, and facilitate growth.


AWS clinical data platform paves the way for product improvements  

Wavicle’s data and analytics consultants collaborated with the medical equipment company’s stakeholders to design a clinical data platform that would meet their specifications. The platform was built on robust AWS cloud infrastructure to support, ingest, and process data from multiple clinical trials in a scalable way to accommodate future growth. To manage the data effectively, Wavicle incorporated Amazon S3 and AWS Redshift for data storage, AWS Lambda and AWS Glue for data processing, and Amazon SageMaker for duplicating code that generates status reports.


To ensure auditability, traceability, and compliance with regulatory standards, Wavicle integrated Amazon QLDB and S3 Object Lock features within the platform. Custom AWS IAM Roles were also meticulously incorporated to restrict data access exclusively to authorized personnel. These measures play a pivotal role in fortifying data management processes, thereby ensuring the safety and effectiveness of the products while upholding the highest standards of regulatory compliance.


Next, to adapt to the increasing data volumes and evolving analysis needs, Wavicle implemented proprietary business logic and designed the platform with the flexibility to embrace and address future requirements.


The collaborative efforts between Wavicle and the manufacturer in creating the clinical data platform led to monumental changes in their clinical data management. By changing their data processes, the manufacturer reduced costs while maintaining high data quality and compliance. Overall, the platform empowers the manufacturer to thrive and innovate while ensuring a future where data-driven excellence remains at the core of their operations.


New platform facilities present and future improvements 

Creating the clinical data platform is projected to save the manufacturer millions of dollars in long-term third-party data management, storage, and reporting expenses. In addition, through this new platform, they can easily access and analyze data and gain holistic insights to make future product improvements. Above all, it serves as the foundation to enable upcoming AI/ML projects.


Here’s how the new platform reshaped the manufacturer’s operations:


  • Cost efficiency: Achieved substantial cost savings by completely removing the reliance on external parties for data management and report generation
  • Auditability and traceability: Established clear audit trails and robust security measures to meet regulatory standards and maintain a clear data lineage
  • Flexibility: Gained the agility to swiftly respond to evolving report requirements and regulatory changes
  • Trust: Leveraged information gathered from trials to demonstrate the effectiveness of the product in the market
  • Scalability: Accommodated the growing volume of data for the new clinical trials


Wavicle consultants delivered a versatile and scalable solution that not only enhances the manufacturer’s data management capabilities but also positions them for future success. With this new clinical data platform, the manufacturer can confidently navigate the complex landscape of clinical trials, ultimately ensuring the safety and efficacy of their products while maintaining the highest standards of data quality and security.