1. A custom designed sequential workflow
Kate Llewellyn, Product Development, GlaxoSmithKline
The Product Development Challenge
Pre-term labour (prior to 37 weeks gestation) is the largest single cause of infant morbidity and mortality and it is frequently associated with long-term disability. GSK (Retosiban) is an oxytocin receptor antagonist in development for the treatment of pre-term labour.
The product development challenge is to manufacture supply of drug substance for Phase III clinical trials, commencing in
The final chemical stage (Stage 6) in the synthesis of the drug substance is the coupling of GSK277221A with morpholine, in a stereoselective reaction, which yields drug substance in around 70% w/w yield.
At GSK, we use experimental design to generate the process understanding that identifies critical process parameters (CPPs) and safe operating conditions (design space) for the manufacture of the drug substance. Using the example of Stage 6, a range of custom designs are exemplified in chemistry and engineering scenarios.
Integrated DoE and process understanding
A chemical stage consists of several unit operations that must be studied individually to identify potential CPPs and then studied together in order to develop a design space. Each unit operation was investigated using custom design technology in order to fully integrate prior process understanding in designing experiments.
The team wished to explore the factors controlling stereoselectivity in Stage 6 and identify potential CPPs controlling diastereoisomer formation under reaction conditions. Additionally, purging of critical impurities across the washes and crystallisation unit operations was investigated. Each of the unit operations were studied individually, with the initial focus on the reaction chemistry, in which a highly tailored custom design was employed.
Reaction custom design
The starting point for any DoE is a review of the historical data, any prior DoE work and a brainstorm of parameters to be studied. A 4 factor study had assessed the impact of 4 parameters in a fractional factorial design, which had identified an important interaction and the
potential for curvature for some parameters.
Reaction
Washes
Crystallisation
Isolation
From this review and discussion, a set of 9 parameters were identified for further investigation, including all of those previously studied by DoE.
The custom design chosen to study the Stage 6 reaction is shown here. This design incorporated prior knowledge on known interactions and potential curvature.
An additional constraint that temperature 2 ≤ temperature 1 was also included and the experimental study was conducted in 19 runs.

2. A custom designed sequential workflow
Kate Llewellyn, Product Development, GlaxoSmithKline
Custom design analysis
The data from this design was then analysed using several platforms in JMP11. In most cases, simple models may be identified using the screening platform.
However in some case, the screening platform fails to identify a sensible model. In these cases, multiple alternative models can be assessed using “all possible models” within the Stepwise platform.
Bespoke designs to solve chemistry problems
Crystallisation
In order to meet the deadline for scale-up of the chemistry, a fractional factorial design was initially selected. The two most forcing sets of conditions in the design were run first. During processing, issues with performance of the
The remaining unit operations, the washing and crystallisation were studied in smaller scale bespoke designs, intended to quickly identify any interactions across the unit operations and provide assurance of robustness prior to scale-up.
crystallisation were
observed. A change to
ranges was needed to
Washing
avoid problematic
conditions, producing
an unbalanced design
which was also
analysed in JMP.
Outcomes & next steps
A custom design was
targeted at understanding
the impact of water in
washes on purging of
key impurities in this unit
operation. The model was
specified so that the main effect of water, the crossed term for water and a key interaction of water with input were not aliased.
Selection of processing set points and ranges, is enabled by visualising multiple responses using the prediction profiler.
Following the completion of the sequence of experiments across the three unit operations, the manufacture of Phase III clinical supplies was conducted in Singapore. Six batches at 2.9 kg each were manufactured in excellent yield and quality.
Next steps for Stage 6 will include revisiting the problematic crystallisation and exploring how the established ranges perform as the specification of the input materials vary.
At each stage, we will be custom designing the experiments to solve the unique chemistry problems.
Models across multiple potentially correlated responses are visualised using the PCA platform. Impurities that are formed by similar mechanisms can be identified, grouped and remodelled.
The prediction profiler is used throughout to visualise the size and direction of parameter effects.

3. Reaction custom design analysis
Back 1
Back 2
Combining all data in a PCA model
Defining the model
Rapid analysis in the screening platform
Modelling of key responses
Exploring alternative models in “all possible models”

4. Workup custom design analysis
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Assess colinearity using VIFs
Defining the model
Resolving conflicts through visualising multiple responses
Visualising column correlations

5. Crystallisation “edited” fractional factorial
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Inputting the original model
Visualising correlations when things go wrong!
Visualising model outputs