{"id":3911,"date":"2023-11-01T09:02:58","date_gmt":"2023-11-01T09:02:58","guid":{"rendered":"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/?p=3911"},"modified":"2025-11-18T07:51:23","modified_gmt":"2025-11-18T07:51:23","slug":"medical-equipment-manufacturer-clinical-data-platform","status":"publish","type":"post","link":"https:\/\/beta74.thewebsitepreview.com\/wavicle\/dev\/case-studies\/medical-equipment-manufacturer-clinical-data-platform\/","title":{"rendered":"Medical Equipment Manufacturer Saves Millions of Dollars With a New Clinical Data Platform"},"content":{"rendered":"<p><span data-contrast=\"auto\">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\u00a0<\/span><a href=\"https:\/\/wavicledata.com\/advanced-analytics\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">advanced analytics<\/span><\/a><span data-contrast=\"auto\">\u00a0projects in the future.<\/span><\/p>\n<p><span data-contrast=\"auto\">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.<\/span><\/p>\n<h2><span data-contrast=\"none\">Difficulties arising from the lack of direct access to data<\/span><\/h2>\n<p><span data-contrast=\"auto\">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.<\/span><\/p>\n<p><span data-contrast=\"auto\">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\u2019t 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.<\/span><\/p>\n<p><span data-contrast=\"auto\">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.<\/span><\/p>\n<p><span data-contrast=\"auto\">The manufacturer decided to leverage Wavicle\u2019s 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.<\/span><\/p>\n<h2><span data-contrast=\"none\">AWS clinical data platform paves the way for product improvements\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/h2>\n<p><span data-contrast=\"auto\">Wavicle\u2019s data and analytics consultants collaborated with the medical equipment company\u2019s stakeholders to design a clinical data platform that would meet their specifications. The platform was built on robust\u00a0<\/span><a href=\"https:\/\/wavicledata.com\/aws-cloud-migration-and-data-analytics-consulting\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">AWS cloud infrastructure<\/span><\/a><span data-contrast=\"auto\">\u00a0to 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.<\/span><\/p>\n<p><span data-contrast=\"auto\">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\u00a0<\/span><a href=\"https:\/\/wavicledata.com\/data-management-services\/\" target=\"_blank\" rel=\"noopener\"><span data-contrast=\"none\">data management<\/span><\/a><span data-contrast=\"auto\">\u00a0processes, thereby ensuring the safety and effectiveness of the products while upholding the highest standards of regulatory compliance.<\/span><\/p>\n<p><span data-contrast=\"auto\">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.<\/span><\/p>\n<p><span data-contrast=\"auto\">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.<\/span><\/p>\n<h2><span data-contrast=\"none\">New platform facilities present and future improvements<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/h2>\n<p><span data-contrast=\"auto\">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.<\/span><\/p>\n<p><span data-contrast=\"auto\">Here\u2019s how the new platform reshaped the manufacturer\u2019s operations:<\/span><\/p>\n<ul>\n<li><span style=\"font-size: 20px;\">Cost efficiency: Achieved substantial cost savings by completely removing the reliance on external parties for data management and report generation<\/span><\/li>\n<li><span style=\"font-size: 20px;\">Auditability and traceability: Established clear audit trails and robust security measures to meet regulatory standards and maintain a clear data lineage<\/span><\/li>\n<li><span style=\"font-size: 20px;\">Flexibility: Gained the agility to swiftly respond to evolving report requirements and regulatory changes<\/span><\/li>\n<li><span style=\"font-size: 20px;\">Trust: Leveraged information gathered from trials to demonstrate the effectiveness of the product in the market<\/span><\/li>\n<li><span style=\"font-size: 20px;\">Scalability: Accommodated the growing volume of data for the new clinical trials<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">Wavicle consultants delivered a versatile and scalable solution that not only enhances the manufacturer\u2019s 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.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Migrated 550+ Tableau dashboards to QuickSight using EZConvertBI, achieving 80% automation, 60% time savings, and seamless collaboration under tight timelines and data constraints.<\/p>\n","protected":false},"author":2,"featured_media":5224,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[148,146,145,144,77,141,133,76,54,72,55,95],"tags":[],"class_list":["post-3911","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-amazon-qldb","category-aws-redshift","category-amazon-s3","category-amazon-sagemaker","category-architecture-engineering","category-aws","category-aws-lambda","category-build-migrations","category-case-studies","category-data-management","category-industry","category-technology","entry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Medical Manufacturer Saves Millions with Clinical Data Platform<\/title>\n<meta name=\"description\" content=\"Learn how a medical 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