A major global Contract Research Organization (CRO) in the pharmaceutical industry.
- Comparison of different combinations of labeling and packaging options for a set of three clinical trials investigating the same drug
- Optimization of the supply plan for each of the options tested
When several clinical trials use the same investigational product, it is possible to “pool” their supply plans, i.e. label the products in such a way that each package can be used in any of the trials. Although this increased flexibility makes supply a bit more challenging, it allows a reduction of total production and cost.
In this case, the client’s initial packaging design involved different package types for each dose level and different labels for each clinical trial as well as for each region. It was clear that this concept could not be flexible enough to deal with the uncertainty levels as production would have to cover the potential maximum demand, even though actual demand could be far lower.
The client had to choose between several labeling and packaging protocols, each of which was characterized by high uncertainty due to:
- Many different dose levels in the treatment, with the possibility that the patient might change dosage several times during the trial
- Only a few patients per investigational site
- A fixed batch size
A clear idea was needed of the cost reduction that could be achieved by “pooling” the supply, i.e. reducing the number of unique packages and increasing their flexibility within each trial:
- By using multi-language “booklet” labels that can be sent anywhere in the world
- By combining a small number of package types to create the different dose levels
And across all three trials:
- By printing no trial-specific label, each package can be used in any trial.
To this end, several packaging and labeling options were modeled in CT-FAST, N-SIDE’s simulation tool. An optimization of the supply plan was performed for each of them. The designs were then compared, in terms of cost and risk and the advantages of pooling made clear.
First of all, simulation showed how demand uncertainty decreases when protocols are pooled together.
The statistical logic behind that is that the maximum demand for all three protocols pooled together is lower than the sum of the maximum demands for the three protocols taken separately.
The total maximum package demand could be reduced by almost 20 %.
Simulation also showed that pooling the clinical trials supply plans would reduce total cost by half, while maintaining a very low risk level.
Furthermore, simulations were used to assess the impact of reducing the number of package types. A cost-risk analysis comparison was done for the following options:
1. No pooling
2. Pooled trials
3. Pooled trials + reduced number of package types
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