Design and conduct of an ethical yet informative study in this special population can be challenging. Capturing changes in PK during pregnancy may be complicated due to practical difficulties such as limited recruitment of subjects, limited numbers of feasible blood samples or sampling occasions. When designing and analyzing a clinical study, ideally pregnancy should not be treated as a dichotomous covariate, since changes in physiological parameters and PK are continuous. Moreover, the combination of small sample sizes and large inter- and intra-patient variability in PK parameters may further complicate the detection of significant changes in PK parameters during pregnancy.
As illustrated in the case examples covered during the ACoP session, pharmacometric approaches such as optimal design [56
] or simulation studies may be used to support design of informative studies in this vulnerable population in various ways. These include sparse sampling designs, leveraging of physiological data to quantify anticipated changes in PK, conducting the trial in silico
before its execution in vivo
, and the overall evaluation of potential study designs for their likelihood of quantifying the (changes in) PK parameters of interest. All these approaches generate information or hypotheses that can be rigorously tested as data become available from controlled experiments. As clinical studies have been performed, these data may also be used to evaluate or validate the performance of developed models and further improve these models based on observed data.
Relevant methods available for analyzing PK studies were briefly discussed, each with their own benefits and drawbacks. It is important to consider carefully an appropriate method, or combination of methods, specific to the question to be answered. Semi-physiological approaches may sometimes be considered, offering benefits of both PPK and PBPK methods. Further advances in PBPK models are expected to be useful in further exploration of both maternal and fetal exposure in silico. Increased understanding of maternal-fetal transport processes and gestationally-induced changes in drug metabolism and transport would be especially helpful in improving the utility of PBPK models.
Optimizing drug treatment in (pregnant) patients is related ultimately to observed variability within and between patients, both in PK and PD. Such variations are the sum of the interplay between difference in physiological changes during pregnancy and other causes such as differences in metabolism (e.g. pharmacogenetic variation), patient compliance or obesity. The multitude of factors influencing PK and PD complicates the assessment of changes in the pharmacology of drugs during pregnancy.
The session and this review focused on changes in PK in the pregnant women. Post partum changes in maternal PK were not specifically discussed, but should ideally also be investigated in any clinical study aiming to investigate changes in PK during pregnancy, as it is not expected that PK will change back to the non-pregnant baseline instantaneously. Another subject which was discussed in this review was assessment of fetal exposure through the placenta and drug exposure through breast milk. However, as indicated, PBPK methods would be expected to be the most appropriate methodology to provide quantitative predictions for these events.
We discussed the specific challenges related to the design, conduct and analysis of clinical studies in pregnant women, underlining the unmet need for pharmacometric analysis approaches and examples of impact to date. There have been significant developments in pharmacometric models over the past three decades, as well as increased understanding of the profound physiological changes which occur during pregnancy. The pharmacometric approaches discussed allow design and analysis of more informative studies. However, effective application of pharmacometric methods is dependent on interdisciplinary expertise and collaboration, in order ultimately to support the improvement in care for pregnant women and their offspring.