Evidence map›Paper›PMID 41700635›Full record

ArticleJournal of clinical pharmacology2026

Mechanism-Based Predictions of Local Tissue and Systemic Exposure for Drug Products Delivered Through the Female Reproductive Tract.

Xinnong Li, Thomas Straubinger, Lisa C Rohan, Sharon L Achilles, Beatrice A Chen, Guru Valicherla, Zhongfang Zhang, Mark Donnelly, Eleftheria Tsakalozou, Liang Zhao and 1 more

Abstract read
In one paragraph

Article in Journal of clinical pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Xinnong LiDepartment of Pharmaceutical Sciences,Division of Pharmacokinetics, Pharmacodynamics and Systems Pharmacology, University at Buffalo, Buffalo, USA.ORCID https://orcid.org/0009-0009-3002-4146
Thomas StraubingerDepartment of Pharmaceutical Sciences,Division of Pharmacokinetics, Pharmacodynamics and Systems Pharmacology, University at Buffalo, Buffalo, USA.
Lisa C RohanDepartment of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, USA.
Sharon L AchillesDepartment of Obstetrics, Gynecology, & Reproductive Sciences, School of Medicine, University of Pittsburgh, Pittsburgh, USA.ORCID https://orcid.org/0000-0002-7478-8262
Beatrice A ChenDepartment of Obstetrics, Gynecology, & Reproductive Sciences, School of Medicine, University of Pittsburgh, Pittsburgh, USA.ORCID https://orcid.org/0000-0002-4437-4632
Guru ValicherlaDepartment of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, USA.ORCID https://orcid.org/0000-0002-1180-2530
Zhongfang ZhangDepartment of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, USA.ORCID https://orcid.org/0009-0000-3640-1429
Mark DonnellyDivision of Quantitative Methods and Modeling, Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), U.S. Food and Drug Administration (FDA), Silver Spring, USA.ORCID https://orcid.org/0000-0001-7537-9615
Eleftheria TsakalozouDivision of Quantitative Methods and Modeling, Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), U.S. Food and Drug Administration (FDA), Silver Spring, USA.ORCID https://orcid.org/0000-0003-1993-8528
Liang ZhaoDepartment of Bioengineering and Therapeutic Sciences, School of Pharmacy, University of California San Francisco, San Francisco, USA.
Robert BiesDepartment of Pharmaceutical Sciences,Division of Pharmacokinetics, Pharmacodynamics and Systems Pharmacology, University at Buffalo, Buffalo, USA.ORCID https://orcid.org/0000-0003-3818-2252

Funding

US Food and Drug Administration #HHSF223201810188C
6 · The paper itself

Abstract

Effective drug delivery through the female reproductive tract (FRT) presents unique challenges due to the lack of robust predictive models for drug exposure via this route. Addressing this gap, we developed and evaluated a comprehensive whole-body physiologically based pharmacokinetic (PBPK) model that incorporates anatomical and physiological information of the FRT. This model was calibrated using both published and experimental data for the drug levonorgestrel (LNG), administered via oral, vaginal, and intrauterine routes. The PBPK model simulates drug absorption, distribution, and elimination, providing predictions of local tissue concentrations and systemic exposure. The majority of observations can be contained within or overlaid with the simulated profiles. Noteworthy is the model's capability to predict the pharmacokinetics of LNG with reasonable precision across different administration routes, thereby demonstrating its potential utility in supporting drug development and regulatory decisions. The application of this model allows for exploration of drug formulations and dosing regimens, reducing the reliance on extensive clinical trials. Furthermore, the model may potentially be used to facilitate generic drug development, and thus promote generic competition, for drug products that are important in women's health. By bridging critical knowledge gaps, this model facilitates in silico evaluation of drugs administered through the FRT, potentially fostering advancements in therapeutic strategies and patient care.

Indexed as

Genitalia, FemaleLevonorgestrelModels, BiologicalAdministration, OralFemaleHumansTissue DistributionLevonorgestrelfemale reproductive tractintrauterine systemlevonorgestrelpharmacokineticsphysiologically based pharmacokinetic (PBPK) modeling

Identifiers

PMID41700635
PMCPMC12910638

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.