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However, standardised dosing regimens fail to account for inter\u2010individual heterogeneity, leading to non\u2010optimal drug exposure in certain patients. This may, in part, explain why primary non\u2010response, secondary loss of response or adverse effects are observed in real\u2010world practice. While empirical off\u2010label adjustments are commonly employed, data\u2010driven dosing optimisation may enable better disease control and reduce the burden of lifelong biologic treatment by avoiding excessive dosing. Therapeutic drug monitoring (TDM) involves adjusting doses based on serum drug concentrations to maintain therapeutic ranges, relying on established dose\u2013exposure\u2013response correlations. Although TDM provides reactive or proactive optimisation approaches, its threshold\u2010based adjustments are limited by an inability to predict individual pharmacokinetic variability or future clinical outcomes. Model\u2010informed precision dosing (MIPD) represents an evolution beyond conventional TDM by integrating population pharmacokinetic\u2013pharmacodynamic models, patient\u2010specific characteristics and Bayesian forecasting to deliver personalised, adaptive dosing recommendations. This approach captures inter\u2010individual variability while linking serum drug concentrations to clinical response, enabling proactive dose adjustments using sparse or non\u2010steady\u2010state data. Emerging digital tools, point\u2010of\u2010care testing and integration of pharmacogenomics and biomarker profiling are expected to enhance MIPD\u2019s precision and accessibility. Once implemented in routine care, MIPD has the potential to transform biologic therapy dosing using a dynamic, patient\u2010centric system that maximises clinical response, minimises overtreatment and supports sustainable healthcare delivery.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jdv.70147","type":"journal-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T12:06:38Z","timestamp":1763121998000},"page":"404-414","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["From reactive to predictive: Advancing biologic dosing in dermatology"],"prefix":"10.1111","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6342-0923","authenticated-orcid":false,"given":"Anke","family":"Eylenbosch","sequence":"first","affiliation":[{"name":"Department of Head and Skin Ghent University Hospital  Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruoheng","family":"Wei","sequence":"additional","affiliation":[{"name":"St John\u2019s Institute of Dermatology King\u2019s College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rani","family":"Soenen","sequence":"additional","affiliation":[{"name":"Department of Head and Skin Ghent University Hospital  Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9918-1144","authenticated-orcid":false,"given":"Catherine","family":"Smith","sequence":"additional","affiliation":[{"name":"St John\u2019s Institute of Dermatology King\u2019s College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph F.","family":"Standing","sequence":"additional","affiliation":[{"name":"Department of Infection, Immunity and Inflammation University College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Satveer","family":"Mahil","sequence":"additional","affiliation":[{"name":"St John\u2019s Institute of Dermatology King\u2019s College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5303-9310","authenticated-orcid":false,"given":"Jo","family":"Lambert","sequence":"additional","affiliation":[{"name":"Department of Head and Skin Ghent University Hospital  Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,11,14]]},"reference":[{"key":"e_1_2_17_2_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0220868"},{"issue":"1","key":"e_1_2_17_3_1","article-title":"Systemic pharmacological treatments for chronic plaque psoriasis: a network meta\u2010analysis","volume":"1","author":"Sbidian E","year":"2020","journal-title":"Cochrane Database Syst Rev"},{"key":"e_1_2_17_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/jdv.20617"},{"key":"e_1_2_17_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jaad.2017.01.037"},{"key":"e_1_2_17_6_1","unstructured":"European Medicines Agency.Stelara: EPAR \u2013 Product information.2024. 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