The client was a world-leading pharmaceutical company working on treatments for rare genetic diseases. They are the first company to provide therapeutics for mucopolysaccharidosis type I (MPS I) and for phenylketonuria (PKU). The client developed a cost-effectiveness model based on a Markov structure for one of their new treatments but encountered that the way of modelling the disease was not completely consistent with what was found in their trial. The model needed to be updated with the new data to create a better representation of the disease and estimate the cost-effectiveness more accurate.
The whole structure of the model needed to be adjusted to create the appropriate patient flow and distributions in the model. Especially background coding with regard to the sensitivity analyses needed to be rewritten to account for the change in model structure and data inputs. Additionally, the whole model had to be updated with the latest information on pricing.