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Analytical Method Digital Risk Management

Develop your analytical methods with robustness and flexibility.

Benefits this Solution Provides

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Gain More Flexibility

Work with broader operating ranges.

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Increase Knowledge

Understand the impact of analytical procedure parameters on method performance.

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Improve Robustness

Minimize the risk of poor performance and incorrect reporting.

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Achieve compliance

Fully align with the ICH Q14 guideline.

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Optimize Your Analytical Method Development

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  • Collect and manage all prior and additional knowledge related to analytical procedures to make informed decisions during the development stage. 
  • Easily pinpoint analytical procedure parameters that could impact performance and objectively assess the impact level. 
  • Identify and prioritize analytical parameters to be investigated experimentally, streamlining resources. 

Better Evaluate Your Method’s Performance

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  • Select parameters to investigate the method’s capacity to meet the expected requirements to facilitate robustness evaluation. 
  • Use risk assessment and prior knowledge to identify analytical procedure parameter ranges to be investigated in multivariate experiments.  

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Achieve Control and Continual Improvement

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  • Use risk control principles to establish an analytical procedure control strategy and maintain control of its performance, continuously resulting in a more reliable operation. 
  • Support the continual improvement of the analytical procedure performance throughout its lifecycle with effective risk communication. 
  • Manage change more efficiently with an existing risk-based categorization of changes to analytical procedures. 

What Can You Expect From Implementing Our Solution?

Before After
Risk assessment is more complex and subjective. Risk assessment provides a complete understanding of the impact of analytical procedure parameters on its performance.
Knowledge is stored separately and is not used to its full potential. Uses all analytical procedure knowledge to support preventative measures and facilitate continual improvement.
Difficult to manage changes. Easy to manage future changes with risk-based characterization.
Poor exploration of the operational ranges and interactions between parameters. Wider operating ranges contribute to more flexibility for lifecycle management.

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