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Updated: Jul 11, 2025

Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models
Published on: November 11, 2020
Clinical Bridging Studies and Modeling Approach for Implementation of a Patient Centric Sampling Technique in
Hester Kramer1, Ceyhun Bicer2, Christian Otoul1
1Early Solutions, Development Sciences, UCB Biopharma SRL, Chemin du Foriest, B-1420, Braine l'Alleud, Belgium.
Abstract:
Volumetric absorptive microsampling (VAMS) techniques have gained popularity these last years as innovative tool for collection of blood pharmacokinetic (PK) samples in clinical trials as they offer many advantages over dried blood spot and conventional venous blood sampling. The use of Mitra®, a blood collection device based on volumetric absorptive microsampling (VAMS) technology, was implemented during clinical development of padsevonil (PSL), an anti-seizure medication (ASM) candidate. The present study describes the approach used to bridge plasma (obtained from conventional venous blood sampling) and blood exposures (obtained with Mitra®) to support the use of Mitra as sole blood PK sampling method in clinical trials. Paired blood (using Mitra®) and plasma samples (using conventional venous blood sampling) were collected in healthy volunteers as well as in patients with epilepsy. PSL concentration in plasma and blood were analyzed using different approaches which included evaluation of blood-to-plasma ratios (B/P) over time, linear regression, Bland-Altman analysis as well as development of a linear-mixed effect model based on clinical pharmacology studies. Results showed that the observed in vivo B/P and the measured bias between the 2 collection methods were consistent with the measured in vitro B/P. Graphical analysis demonstrated a clear time effect on the B/P which was confirmed in the linear mixed effect model with sampling time identified as significant covariate. Finally, the built-in model was validated using independent datasets and was shown to adequately predict plasma concentration based on blood concentration with a mean bias of less than 9% (predicted versus observed plasma concentration).
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