Human hepatic membrane-embedded transporter proteins are involved in trafficking endogenous and exogenous substrates. Even though impact of transporters on pharmacokinetics is recognized, little is known on maturation of transporter protein expression levels, especially during early life. We aimed to study the protein expression of 10 transporters in liver tissue from fetuses, infants, and adults. Transporter protein expression levels [ATP-binding cassette transporter (ABC)B1, ABCG2, ABCC2, ABCC3, bile salt efflux pump, glucose transporter 1, monocarboxylate transporter 1, organic anion transporter polypeptide (OATP)1B1, OATP2B1, and organic cation/carnitine transporter 2) were quantified using ultraperformance liquid chromatography tandem mass spectrometry in snap-frozen postmortem fetal, infant, and adult liver samples. Protein expression was quantified in isolated crude membrane fractions. The possible association between postnatal and postmenstrual age versus protein expression was studied. We studied 25 liver samples, as follows: 10 fetal [median gestational age 23.2 wk (range 16.4-37.9)], 12 infantile [gestational age at birth 35

Objectives The structured digital dosing guidelines of the web-based Dutch Paediatric Formulary provided the opportunity to develop an integrated paediatric dose calculator. In a simulated setting, we tested the ability of this calculator to reduce calculation errors. Methods Volunteer healthcare professionals were allocated to one of two groups, manual calculation versus the use of the dose calculator. Professionals in both groups were given access to a web-based questionnaire with 14 patient cases for which doses had to be calculated. The effect of group allocation on the probability of making a calculation error was determined using generalized estimated equations (GEE) logistic regression analysis. The causes of all the erroneous calculations were evaluated. Results Seventy-seven healthcare professionals completed the web-based questionnaire: thirty-seven were allocated to the manual group and 40 to the calculator group. Use of the dose calculator resulted in an estimated mean probability of a calculation error of 24.4% (95% CI 16.3-34.8) versus 39.0% (95% CI 32.4-46.1) with use of manual calculation. The mean difference of probability of calculation error between groups was 14.6% (95% CI 3.1-26.2; p = 0.013). In a secondary analysis where calculation error was defined as a 10% or greater deviation from the correct answer, the corresponding figures were 19.5% (95% CI 13-28.2) versus 26.5% (95% CI 21.6-32.1) with a mean difference of 7% between groups (95% CI 2.2-16.3; p = 0.137). Juxtaposition, typo/transcription errors and non-specified errors were more frequent as cause of error in the calculator group; exceeding the maximum dose and wrong correction for age were more frequent in the manual group. The percentage of tenfold errors was 3.1% in the manual group and 3.7% in the calculator group. Conclusions Our study shows that the use of a dose calculator as an add-on to a web-based paediatric formulary can reduce calculation errors. Furthermore, it shows that technologies may introduce new errors through transcription errors and wrongly selecting parameters from drop-down lists. Therefore, dosing calculators should be developed and used with special attention for selection and transcription errors.