Statistics & DoE

Rapid Development via Statistics and Design of Experiments (DoE)

Statistics and DoE are increasingly common in pharmaceutical development processes, from the manufacturing of RSMs and regulatory intermediates to API and the final drug product. The type of analysis can vary over development stages, from initial screening to optimization and filing.

Experiments guided by DoE and statistics reduce ambiguity and often lead to faster and more efficient development. In addition, 1st principal matter experts with statistical DoE knowledge obtain a rapid, global understanding of the systems at hand. Specific examples include:

The Identification of secondary mixing effects (e.g., use of inorganic bases)

Complexation in crystallizations (API forms a scorpionate complex with trace metal)

Catalyst deactivation

Advantages of Statistics and DoE with HTE

DoE and statistics have numerous advantages over classical approaches. In the early stage, the number of experiments can be significantly improved, while also keeping the scientist apprised of potential experimental outliers. At this stage, DoE with HTE becomes a very powerful tool. Models can be improved to provide additional information (e.g., 2-way interactions and curvature).

At later stages of development, more specialized DoE models and analysis can be conducted, providing additional information like NOR, PAR, and a global and local robustness analysis.

Optimizing Design Strategy via DoE

J-Star Research has a wide range of capabilities using different DoE software packages. Our experience across a wide, cross-functional field guides J-Star Research scientists to the best design strategy. Some typical factors impacting the choice of strategy used and the designs are:

Prior knowledge

Material availability

Time constraints

Parallel versus sequential experimentation

Response sensitivity