A robustness study is usually performed following a process investigation or method development whereupon ranges have been established for the factors that are predicted to produce product that has a high probability of conforming to quality & manufacturing targets. The intention of a robustness study is to determine whether the process or method is robust to the factors varying across these predicted acceptable ranges (i.e., small purposeful changes in the settings of the factors are deliberately introduced). No effects are expected nor wanted, so these confirmatory designs require only a minimal resource to achieve their objective (i.e., for up to 7 factors an 8 run design with repeated centre points – to also demonstrate ruggedness and assess effects against pure error – would be sufficient).

If the robustness study fails to give you confidence that the process can be operated successfully within your predicted design space, then you can use the results of the robustness study to help you decide which factors are critical and require narrower ranges or tighter control. If there is excessive variation between the centre point results you may need to follow up with a variation management study or measurement systems analysis.

To handle robustness designs within the Design Expert DX7 software tool, we have further tipsheets to help you:

   Robustness Designs: Building the Design
   Robustness Designs: Analysing your Results
   Robustness Designs: Interpreting your Results

These tipsheets are linked to this case study

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Granulation Process

This top-spray granulation process has four key process and ingredient parameters:

• Magnesium Stearate
• Granulation Paste Type
• Filler (Dibasic Sodium Phosphate)
• Granulation Blend Time

and three key properties of tablets of a drug product:

• Hardness
• Degradation Rate
• Dissolution

Set up and analyse the results of a resource efficient robustness study to evaluate the predicted acceptable ranges of the six equipment settings of a top spray granulator and assess its robustness to these small but deliberate changes in the six parameters