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Updated: Dec 27, 2025

A Web Tool for Generating High Quality Machine-readable Biological Pathways
Published on: February 8, 2017
Application programming interfaces for knowledge transfer and generation in the life sciences and healthcare
Stephen K Woody1, David Burdick2, Hilmar Lapp3
11Duke University School of Medicine, 701W. Main St, Durham NC, 27701 USA.
Abstract:
Storing very large amounts of data and delivering them to researchers in an efficient, verifiable, and compliant manner, is one of the major challenges faced by health care providers and researchers in the life sciences. The electronic health record (EHR) at a hospital or clinic currently functions as a silo, and although EHRs contain rich and abundant information that could be used to understand, improve, and learn from care as part learning health system access to these data is difficult, and the technical, legal, ethical, and social barriers are significant. If we create a microservice ecosystem where data can be accessed through APIs, these challenges become easier to overcome: a service-driven design decouples data from clients. This decoupling provides flexibility: different users can write in their preferred language and use different clients depending on their needs. APIs can be written for iOS apps, web apps, or an R library, and this flexibility highlights the potential ecosystem-building power of APIs. In this article, we use two case studies to illustrate what it means to participate in and contribute to interconnected ecosystems that powers APIs in a healthcare systems.
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