{"title":"1型ifn介导的系统性红斑狼疮炎症的综合机制模型。","authors":"Alina Volkova, Victor Sokolov, Florencia Tettamanti, Meghna Verma, Yaroslav Ugolkov, Kirill Peskov, Weifeng Tang, Holly Kimko","doi":"10.1002/psp4.70043","DOIUrl":null,"url":null,"abstract":"<p><p>Type I interferon (IFN1) pathway-targeting therapies represent a highly promising class of remedies for the treatment of systemic lupus erythematosus. However, the overall clinical benefit of these compounds is afflicted by marked variability. In this study, we developed a quantitative systems pharmacology model of type I IFN-mediated inflammation and applied it for an indirect comparison of anifrolumab, sifalimumab, daxdilimab, and litifilimab pharmacodynamic response, represented in the model by the change in IFN1 gene signature (IFNGS). The model consists of 20 ordinary differential equations and 68 parameters, among which four systemic parameters (including one random effect) were estimated using patient-level data from Phase IIb anifrolumab clinical trial. Within-target and within-pathway validation was performed using study-level pharmacokinetics, IFNα, and/or IFNGS data from five anifrolumab, four sifalimumab, one daxdilimab, and one litifilimab trials. The model successfully captured overall trends in IFNGS at clinically relevant doses of these compounds and discriminated IFNGS response between patients with low (< 2.75) and high (≥ 2.75) baseline IFNGS. Overprediction of treatment benefit was observed for the low range of anifrolumab doses (100-150 mg every 4 weeks). In contrast, IFNGS response under 150 mg of daxdilimab was underpredicted, despite the accurate description of plasmacytoid dendritic cells and IFNα biomarkers. Results of the global sensitivity analysis revealed baseline IFNGS, IFNα, and IFNα fraction as key factors affecting treatment benefit the most. In terms of maximum IFNGS reduction, anifrolumab showed superior potential compared to sifalimumab, daxdilimab, and litifilimab (ΔIFNGS~25%), which was further enhanced in patients with high baseline IFNGS or IFNα (ΔIFNGS~50%-60%).</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Integrative Mechanistic Model of Type 1 IFN-Mediated Inflammation in Systemic Lupus Erythematosus.\",\"authors\":\"Alina Volkova, Victor Sokolov, Florencia Tettamanti, Meghna Verma, Yaroslav Ugolkov, Kirill Peskov, Weifeng Tang, Holly Kimko\",\"doi\":\"10.1002/psp4.70043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Type I interferon (IFN1) pathway-targeting therapies represent a highly promising class of remedies for the treatment of systemic lupus erythematosus. However, the overall clinical benefit of these compounds is afflicted by marked variability. In this study, we developed a quantitative systems pharmacology model of type I IFN-mediated inflammation and applied it for an indirect comparison of anifrolumab, sifalimumab, daxdilimab, and litifilimab pharmacodynamic response, represented in the model by the change in IFN1 gene signature (IFNGS). The model consists of 20 ordinary differential equations and 68 parameters, among which four systemic parameters (including one random effect) were estimated using patient-level data from Phase IIb anifrolumab clinical trial. Within-target and within-pathway validation was performed using study-level pharmacokinetics, IFNα, and/or IFNGS data from five anifrolumab, four sifalimumab, one daxdilimab, and one litifilimab trials. The model successfully captured overall trends in IFNGS at clinically relevant doses of these compounds and discriminated IFNGS response between patients with low (< 2.75) and high (≥ 2.75) baseline IFNGS. Overprediction of treatment benefit was observed for the low range of anifrolumab doses (100-150 mg every 4 weeks). In contrast, IFNGS response under 150 mg of daxdilimab was underpredicted, despite the accurate description of plasmacytoid dendritic cells and IFNα biomarkers. Results of the global sensitivity analysis revealed baseline IFNGS, IFNα, and IFNα fraction as key factors affecting treatment benefit the most. In terms of maximum IFNGS reduction, anifrolumab showed superior potential compared to sifalimumab, daxdilimab, and litifilimab (ΔIFNGS~25%), which was further enhanced in patients with high baseline IFNGS or IFNα (ΔIFNGS~50%-60%).</p>\",\"PeriodicalId\":10774,\"journal\":{\"name\":\"CPT: Pharmacometrics & Systems Pharmacology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-05-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CPT: Pharmacometrics & Systems Pharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/psp4.70043\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CPT: Pharmacometrics & Systems Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/psp4.70043","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
An Integrative Mechanistic Model of Type 1 IFN-Mediated Inflammation in Systemic Lupus Erythematosus.
Type I interferon (IFN1) pathway-targeting therapies represent a highly promising class of remedies for the treatment of systemic lupus erythematosus. However, the overall clinical benefit of these compounds is afflicted by marked variability. In this study, we developed a quantitative systems pharmacology model of type I IFN-mediated inflammation and applied it for an indirect comparison of anifrolumab, sifalimumab, daxdilimab, and litifilimab pharmacodynamic response, represented in the model by the change in IFN1 gene signature (IFNGS). The model consists of 20 ordinary differential equations and 68 parameters, among which four systemic parameters (including one random effect) were estimated using patient-level data from Phase IIb anifrolumab clinical trial. Within-target and within-pathway validation was performed using study-level pharmacokinetics, IFNα, and/or IFNGS data from five anifrolumab, four sifalimumab, one daxdilimab, and one litifilimab trials. The model successfully captured overall trends in IFNGS at clinically relevant doses of these compounds and discriminated IFNGS response between patients with low (< 2.75) and high (≥ 2.75) baseline IFNGS. Overprediction of treatment benefit was observed for the low range of anifrolumab doses (100-150 mg every 4 weeks). In contrast, IFNGS response under 150 mg of daxdilimab was underpredicted, despite the accurate description of plasmacytoid dendritic cells and IFNα biomarkers. Results of the global sensitivity analysis revealed baseline IFNGS, IFNα, and IFNα fraction as key factors affecting treatment benefit the most. In terms of maximum IFNGS reduction, anifrolumab showed superior potential compared to sifalimumab, daxdilimab, and litifilimab (ΔIFNGS~25%), which was further enhanced in patients with high baseline IFNGS or IFNα (ΔIFNGS~50%-60%).