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Artificial Intelligence And New Technology Adoption In Risk-Based Quality Management

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This paper is the second in a series of two papers written by the same authors taking you through: 

1. Right sized Risk-Based Quality Management Solution (RBQM) for your trials

Implementing RBQM from an operational standpoint – your journey through the early stages of RBQM, critical decisions to be made in identifying the right approach for your particular needs, de-risking your protocol, centralized monitoring, and more.

2. Artificial Intelligence (AI) and new technology adoption in Risk-Based Quality Management (RBQM)

Implementing RBQM from a technological standpoint – and on to implementation challenges and lessons learned, including data integration, and automation of processes using artificial intelligence and machine learning (AI/ML) with advanced and predictive analytics.

Leverage experts and technology for superior RBQM delivery

The alignment of RBQM experts and technology can improve data and study quality as a whole. Dedicated platforms from companies such as IQVIA cover the entire RBQM process, effectively making them a single solution for a company’s RBQM needs. With built-in technological sophistication leveraging AI/ML and advanced analytics, these platforms drastically reduce human error and data integrity issues, and automated processes trigger faster corrective actions. It is important to understand more on how each component functions.


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