AIMS: Dried blood spots (DBS) alongside micro-analytical techniques are a potential solution to the challenges of performing pharmacokinetic (PK) studies in children. However, DBS methods have received little formal evaluation in clinical settings relevant to children. The aim of the present study was to determine a PK model for caffeine using a 'DBS/microvolume platform' in preterm infants. METHODS: DBS samples were collected prospectively from premature babies receiving caffeine for treatment of apnoea of prematurity. A non-linear mixed effects approach was used to develop a population PK model from measured DBS caffeine concentrations. Caffeine PK parameter estimates based on DBS data were then compared with plasma estimates for agreement. RESULTS: Three hundred and thirty-eight DBS cards for caffeine measurement were collected from 67 preterm infants (birth weight 0.6-2.11 kg). 88% of cards obtained were of acceptable quality and no child had more than 10 DBS samples or more than 0.5 ml of blood taken over the study period. There was good agreement between PK parameters estimated using caffeine concentrations from DBS samples (CL = 7.3 ml h⁻¹ kg⁻¹; V = 593 ml kg⁻¹; t(½) = 57 h) and historical caffeine PK parameter estimates based on plasma samples (CL = 4.9-7.9 ml h⁻¹ kg⁻¹; V = 640-970 ml kg⁻¹; t(½) = 101-144 h). We also found that changes in blood haematocrit may significantly confound estimates of caffeine PK parameters based on DBS data. CONCLUSIONS: This study demonstrates that DBS methods can be applied to PK studies in a vulnerable population group and are a practical alternative to wet matrix sampling techniques.
AIMS: Dried blood spots (DBS) alongside micro-analytical techniques are a potential solution to the challenges of performing pharmacokinetic (PK) studies in children. However, DBS methods have received little formal evaluation in clinical settings relevant to children. The aim of the present study was to determine a PK model for caffeine using a 'DBS/microvolume platform' in preterm infants. METHODS:DBS samples were collected prospectively from premature babies receiving caffeine for treatment of apnoea of prematurity. A non-linear mixed effects approach was used to develop a population PK model from measured DBS caffeine concentrations. Caffeine PK parameter estimates based on DBS data were then compared with plasma estimates for agreement. RESULTS: Three hundred and thirty-eight DBS cards for caffeine measurement were collected from 67 preterm infants (birth weight 0.6-2.11 kg). 88% of cards obtained were of acceptable quality and no child had more than 10 DBS samples or more than 0.5 ml of blood taken over the study period. There was good agreement between PK parameters estimated using caffeine concentrations from DBS samples (CL = 7.3 ml h⁻¹ kg⁻¹; V = 593 ml kg⁻¹; t(½) = 57 h) and historical caffeine PK parameter estimates based on plasma samples (CL = 4.9-7.9 ml h⁻¹ kg⁻¹; V = 640-970 ml kg⁻¹; t(½) = 101-144 h). We also found that changes in blood haematocrit may significantly confound estimates of caffeine PK parameters based on DBS data. CONCLUSIONS: This study demonstrates that DBS methods can be applied to PK studies in a vulnerable population group and are a practical alternative to wet matrix sampling techniques.
Authors: Baba S Mohammed; Garry A Cameron; Lindsay Cameron; Gabrielle H Hawksworth; Peter J Helms; James S McLay Journal: Br J Clin Pharmacol Date: 2010-07 Impact factor: 4.335
Authors: A C Falcão; M M Fernández de Gatta; M F Delgado Iribarnegaray; D Santos Buelga; M J García; A Dominguez-Gil; J M Lanao Journal: Eur J Clin Pharmacol Date: 1997 Impact factor: 2.953
Authors: Julie Autmizguine; Daniel K Benjamin; P Brian Smith; Mario Sampson; Philippe Ovetchkine; Michael Cohen-Wolkowiez; Kevin M Watt Journal: Curr Clin Pharmacol Date: 2014
Authors: Jonas W Perez; Brooke G Pantazides; Caroline M Watson; Jerry D Thomas; Thomas A Blake; Rudolph C Johnson Journal: Anal Chem Date: 2015-05-20 Impact factor: 6.986
Authors: Tomoyuki Mizuno; Katja M Gist; Zhiqian Gao; Michael F Wempe; Jeffrey Alten; David S Cooper; Stuart L Goldstein; Alexander A Vinks Journal: Clin Pharmacokinet Date: 2019-06 Impact factor: 6.447
Authors: Nicole R Dobson; Xiaoxi Liu; Lawrence M Rhein; Robert A Darnall; Michael J Corwin; Betty L McEntire; Robert M Ward; Laura P James; Catherine M T Sherwin; Timothy C Heeren; Carl E Hunt Journal: Br J Clin Pharmacol Date: 2016-06-03 Impact factor: 4.335
Authors: H Mulla; S Yakkundi; J McElnay; I Lutsar; T Metsvaht; H Varendi; G Nellis; A Nunn; J Duncan; H Pandya; M Turner Journal: Pharm Res Date: 2014-09-19 Impact factor: 4.200
Authors: Mario R Sampson; Adam Frymoyer; Benjamin Rattray; C Michael Cotten; P Brian Smith; Edmund Capparelli; Sonia L Bonifacio; Michael Cohen-Wolkowiez Journal: Ther Drug Monit Date: 2014-10 Impact factor: 3.118
Authors: M Bosilkovska; C F Samer; J Déglon; M Rebsamen; C Staub; P Dayer; B Walder; J A Desmeules; Y Daali Journal: Clin Pharmacol Ther Date: 2014-04-10 Impact factor: 6.875