Validation of the rAHF-PFM PK Guided Dose Calculator Medical Device Using an Unrelated Clinical Dataset

Introduction: Prevention of bleeding represents the standard of care for patients with hemophilia without inhibitors. However, standard prophylactic dosing regimens with FVIII are currently based on body weight alone and do not take into account considerable inter-individual variability in FVIII PK profiles. In order to facilitate personalization of prophylaxis to individual needs and individual PK response we have developed a device that allows PK guided dosing in routine clinical care. In fact, the major barrier of PK-guided dosing in clinical practice is the necessity of multiple blood samples (6 to 11 over 48 hours) associated with a single infusion and the lack of easy-to-use statistical software to generate classical PK profiles. Leveraging the vast rAHF-PFM clinical database with more than 150 classical PK assessments, a Population PK model for children and adults was combined with a Bayesian algorithm to create a user friendly medical device. This methodology allows the use of only a few samples after different infusions to estimate individual PK parameters and help to calculate dosing regimens.

Methods: In order to carry on an external validation of the Bayesian population PK model of the device, individual 10 point PK assessment data from an unrelated source, i.e. not included in the base population PK model, (rAHF-PFM prophylaxis study, Valentino et al 2012) was utilized to validate the accuracy of the calculation. First, we compared predicted post infusion FVIII levels with observed FVIII levels using all the available post infusion samples. In a second step we compared individually estimated PK parameters as obtained by using 10 post infusion samples with a progressively reduced number of post infusion samples.

Results: The external validation study indicated a good agreement between the observed and predicted FVIII levels (Figure) and PK parameters. Furthermore it showed that the rAHF-PFM medical device had a good predictive performance even when using only 2 sampling time-points.

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Conclusion: An easy-to-use medical device that can estimate PK parameters and thus assists in designing prophylactic dosing regimens based on individual- PK characteristics represents a groundbreaking innovation. This literally shifts the treatment paradigm from one-size-fits-all prophylaxis towards a more personalized therapy in hemophilia A and allows further optimization of dosing in patients in order to improve outcome in a sustainable fashion.