Pharma sample request process simplifying

Dyviron conducted thorough analysis, implemented comprehensive testing procedures, and provided a robust platform enabling efficient distribution management with configurable restrictions and ensured compliance through rigorous functional and data quality testing.

Client

The client in this project is a provider of solutions for pharmaceutical companies   focused on full cycle of sample management program compliant to satisfy dynamic regulatory landscape.

Client's Challenge

Dyviron faced the challenge of efficiently managing and controlling the distribution of products to pharma and healthcare professionals. They needed a platform that would allow them to set and enforce restrictions on the quantity of products distributed by sales representatives. These restrictions needed to be configurable at both the sales representative level, based on assigned territories, and at the individual healthcare practitioner level.

Industry:
Pharma
Location:
US
QA Team:
3
Duration (month):
4
Services Used :

What We Did

Dyviron conducted next activities:

  • Functional testing to verify that all features and functionalities, API testing to validate the interactions between the platform and external systems.
  • Data quality testing to ensure the accuracy, completeness, and consistency of data within the platform.
  • Developed formal Installation Qualification (IQ) and Operational Qualification (OQ) test procedures to ensure that the platform met the specified requirements.
  • Additionally, we implemented comprehensive test documentation to track the testing process and results.

Results

The implementation of the platform resulted in several key outcomes:

  • Compliance and Accountability. By implementing formal IQ/OQ test procedures and documentation, Dyviron ensured compliance with regulatory requirements and maintained accountability throughout the testing process.
  • All features and functionalities of the platform performed as intended, meeting the client's requirements and expectations.
  • Data quality testing procedures ensured the accuracy, completeness, and consistency of data within the platform.
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