SynthesisFrontiers in medicine2023
A systematic review of pregnancy-related clinical intervention of drug regimens due to pharmacokinetic reasons.
Synthesis in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- Clinical study design and modeling approaches to study secretion of drugs in human milk.Frontiers in pediatrics · 2026Review
- Enhancing inclusivity in clinical trials: Model-informed drug development for pregnant individuals in the era of personalized medicine.CPT: pharmacometrics & systems pharmacology · 2024Article
- Medicines in pregnancy: A clinical pharmacology extrapolation framework to address knowledge gaps.CPT: pharmacometrics & systems pharmacology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and objective: Published works have discussed the pharmacokinetic interactions of drugs with pregnancy, but none comprehensively identify all the approved United States Food and Drug Administration (FDA) and European Medicines Administration (EMA) drugs that have a pregnancy-related intervention. The objective of this systematic review is to comprehensively identify medications that have clinically meaningful interventions due to pharmacokinetic reasons. Methods: An in-depth search of clinical data using the PDR3D: Reed Tech Navigator™ for Drug Labels was conducted from 1 June to 12 August 2022. The PDR3D was analyzed using the search terms "pregnant" and "pregnancy" within the proper label section. Regarding the US labels, the terms were searched under the "dosage and administration" section, whereas with the EU labels, the terms were searched within the "posology and method of administration" section. If a finding was discovered within the search, the rest of the label was analyzed for further information. Clinical relevance was based on whether an intervention was needed. Results: Using the search strategy, 139 US and 20 EU medications were found to have clinically meaningful interventions in pregnancy. The most common explanations for clinical relevance included hepatic metabolism, protein binding, renal elimination, and P-gp influence. Of the US labels: 40 were found to undergo hepatic metabolism, 11 were found to be influenced by renal elimination, 12 were found to be influenced by protein binding, 7 were found to be influenced by P-gp, and the remaining drugs required further research. Of the EU labels: 11 were found to undergo hepatic metabolism, 3 were found to be influenced by renal elimination, 3 were found to be influenced by protein binding, 1 was found to be influenced by P-gp, and the remaining drugs required further research. Conclusion: This comprehensive review of clinically relevant interventions in pregnancy will potentially aid in the treatment of pregnant females when they are undergoing therapy, provide intervention and dosing guidance for physicians, and save time for prescribers and pharmacists. Advances in non-clinical predictions for pregnancy dosing may guide the need for a future clinical evaluation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.