Model Informed “Therapeutic Window” of Dexamethasone by Quantitatively Balancing the Fetal Lung Maturation and Neurotoxicity in Pregnant Rats: An Insight Study for Clinical Precision Medicine

Model Informed “Therapeutic Window” of Dexamethasone by Quantitatively Balancing the Fetal Lung Maturation and Neurotoxicity in Pregnant Rats: An Insight Study for Clinical Precision Medicine | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 25 March 2026 V1 Latest version Share on Model Informed “Therapeutic Window” of Dexamethasone by Quantitatively Balancing the Fetal Lung Maturation and Neurotoxicity in Pregnant Rats: An Insight Study for Clinical Precision Medicine Authors : Ling Song , Xiaoqi Zhao , Ruihu Du , Lei Zhang , Mengxi Lu , Jie Song , Shuhao Li , Qi Wang , Dan Xu 0000-0003-4408-2469 , Hui Wang 0000-0001-5300-8661 , and Dongyang Liu [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177447138.83338611/v1 114 views 85 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background and Purpose Dexamethasone as the first-line treatment for neonatal respiratory distress syndrome (NRDS) has been found to simultaneously promote fetal lung mature and induce offspring neurotoxicity. This model informed study is aim to set the therapeutic window of dexamethasone for NRDS treatment. Experimental Approach Pregnant rats were injected with 0.1 or 0.4 mg/kg dexamethasone to simulate clinically equivalent prenatal-dexamethasone-exposure (PDE). Half rats were anesthetized. Surfactant protein A/B of fetal lung were quantified and pharmacokinetic/pharmacodynamics model was developed to determine the minimal effective concentration. The other half rats delivered naturally and the offspring were underwent open field testing. mRNA-sequencing of fetal hippocampus was performed and concentrations-toxicity assay was conducted in H19-7/IGR-IR cells. These data were integrated with maternal-fetal physiologically-based-pharmacokinetic model to determine the maximum tolerated concentration. Population-pharmacokinetic-model was used to propose optimal clinical dosing regimen. Key Results Pharmacokinetic/pharmacodynamics model well characterized dexamethasone-induced fetal lung maturation, indicating a minimal effective concentration as 1.63 ng/mL. Offspring of PDE rats exhibited significant behavioral alterations. mRNA-sequencing analysis revealed that neurotoxicity may be mediated through the Wnt pathway and renin-angiotensin system, with BDNF and CMA1 identified as potential neurotoxic biomarkers. Cell assays suggested a neurotoxic cut-off concentration of 17 ng/mL. Based on therapeutic window of 1.63-17 ng/mL, a half-dose clinical regimen was proposed as the optimal therapeutic strategy. Conclusion and Implications This model-informed precision dosing strategy offers a rational approach to optimize clinical dexamethasone dosing regimen. Supplementary Material File (main text.docx) Download 3.98 MB File (supplemental figure s2-1.tif) Download 3.67 MB Information & Authors Information Version history V1 Version 1 25 March 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Affiliations Ling Song Peking University Third Hospital View all articles by this author Xiaoqi Zhao Wuhan University Department of Pharmacology View all articles by this author Ruihu Du Peking University Third Hospital View all articles by this author Lei Zhang Peking University Third Hospital View all articles by this author Mengxi Lu Wuhan University Department of Pharmacology View all articles by this author Jie Song Peking University Third Hospital View all articles by this author Shuhao Li Peking University Third Hospital View all articles by this author Qi Wang Peking University Department of Toxicology View all articles by this author Dan Xu 0000-0003-4408-2469 Wuhan University Department of Pharmacology View all articles by this author Hui Wang 0000-0001-5300-8661 Wuhan University Department of Pharmacology View all articles by this author Dongyang Liu [email protected] Peking University Third Hospital View all articles by this author Metrics & Citations Metrics Article Usage 114 views 85 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Ling Song, Xiaoqi Zhao, Ruihu Du, et al. Model Informed “Therapeutic Window” of Dexamethasone by Quantitatively Balancing the Fetal Lung Maturation and Neurotoxicity in Pregnant Rats: An Insight Study for Clinical Precision Medicine. Authorea . 25 March 2026. DOI: https://doi.org/10.22541/au.177447138.83338611/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. Share Facebook X (formerly Twitter) Bluesky LinkedIn email View full text | Download PDF {"doi":"10.22541/au.177447138.83338611/v1","type":"Article"} Now Reading: Share Figures Tables Close figure viewer Back to article Figure title goes here Change zoom level Go to figure location within the article Download figure Toggle share panel Toggle share panel Share Toggle information panel Toggle information panel Go to previous graphic Go to next graphic Go to previous table Go to next table All figures All tables View all material View all material xrefBack.goTo xrefBack.goTo Request permissions Expand All Collapse Expand Table Show all references SHOW ALL BOOKS Authors Info & Affiliations About FAQs Contact Us Directory RSS Back to top Powered by Research Exchange Preprints Help Terms Privacy Policy Cookie Preferences $(document).ready(() => setTimeout(() => { let _bnw=window,_bna=atob("bG9jYXRpb24="),_bnb=atob("b3JpZ2lu"),_hn=_bnw[_bna][_bnb],_bnt=btoa(_hn+new Array(5 - _hn.length % 4).join(" ")); $.get("/resource/lodash?t="+_bnt); },4000)); (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fdebeec0e22300f',t:'MTc3OTE0ODAzMw=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();