How Bayer Pharmaceuticals Found the Right Prescription for Clinical Data Access

Like other pharmaceutical companies, Bayer Pharmaceuticals conducts research to discover new drugs, test and validate their effectiveness and safety, and introduce them to the market. That process requires accumulating, analyzing and storing vast amounts of clinical data coming from patients and healthy volunteers, which is recorded on an electronic case report form (eCRF). Data is also collected from laboratories and electronic devices and all data is automatically anonymized at the point of collection.

Bayer wanted to gather more data about its drugs to comply with documentation requirements such as those in GxP, a collection of quality guidelines and regulations created by the U.S. Food and Drug Administration (FDA).

Building a microservices-based architecture

To make it faster and easier for researchers to analyze drug development data, the company deployed a microservices-based architecture for its data platform.

dGerman software developer QuinScape GmbH helped Bayer deploy the Talend-powered Karapit framework, which the company is using to integrate several clinical databases and support the pharmacokinetics dataflow and biosampling parts of the drug development process.

“Through Talend microservices, we can obtain clinical pharmacokinetic data more rapidly in order to determine drug doses and better characterize compounds and adhere to quality processes” – Dr. Ivana Adams, Project Manager, Translational Science Systems

Understanding pharmacokinetics data to optimize drug doses

The role of pharmacokinetics (PK) in drug discovery can be described simply as the study of “what a body does to a drug,” and includes the rate and extent to which drugs are absorbed into the body and distributed to the body tissues. It also includes the rate and pathways by which drugs are eliminated from the body by metabolism and excretion. Understanding these processes is extremely important for prescribers because they form the basis for the optimal dose regimen and explain the inter-individual variations in the response to drug therapy

Having clean, verified traceable clinical data saves development time, accelerates the process of determining proper dosage and drug interactions, and leaves a clear audit trail as per FDA GxP guidelines.

Read the full case study here. 

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