From reactive to predictive: Advancing biologic dosing in dermatology

Biologic therapies are targeted immunomodulators that have revolutionised the treatment of chronic inflammatory dermatoses, including psoriasis, hidradenitis suppurativa and atopic dermatitis, offering high efficacy and safety for moderate-to-severe disease. However, standardised dosing regimens fail to account for inter-individual heterogeneity, leading to non-optimal drug exposure in certain patients. This may, in part, explain why primary non-response, secondary loss of response or adverse effects are observed in real-world practice. While empirical off-label adjustments are commonly employed, data-driven 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-exposure-response correlations. Although TDM provides reactive or proactive optimisation approaches, its threshold-based adjustments are limited by an inability to predict individual pharmacokinetic variability or future clinical outcomes. Model-informed precision dosing (MIPD) represents an evolution beyond conventional TDM by integrating population pharmacokinetic-pharmacodynamic models, patient-specific characteristics and Bayesian forecasting to deliver personalised, adaptive dosing recommendations. This approach captures inter-individual variability while linking serum drug concentrations to clinical response, enabling proactive dose adjustments using sparse or non-steady-state data. Emerging digital tools, point-of-care testing and integration of pharmacogenomics and biomarker profiling are expected to enhance MIPD's precision and accessibility. Once implemented in routine care, MIPD has the potential to transform biologic therapy dosing using a dynamic, patient-centric system that maximises clinical response, minimises overtreatment and supports sustainable healthcare delivery.

Authors

Institutions

Publication Details

Journal
Journal of the European Academy of Dermatology and Venereology
Published
2025-11-14
DOI
https://doi.org/10.1111/jdv.70147
Citations
1
Primary Topic
Psoriasis: Treatment and Pathogenesis
Type
article
Field-Weighted Citation Impact
0.80
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From reactive to predictive: Advancing biologic dosing in dermatology

Rani Soenen, Jo Lambert, Satveer K. Mahil, Joseph Frank Standing et al.
1 citations
Journal of the European Academy of Dermatology and Venereology
Psoriasis: Treatment and Pathogenesis
0.80
article

From reactive to predictive: Advancing biologic dosing in dermatology

Rani Soenen, Jo Lambert, Satveer K. Mahil, Joseph Frank Standing, Catherine Smith, Anke Eylenbosch, Ran Wei
article en
1 citations

Abstract

Biologic therapies are targeted immunomodulators that have revolutionised the treatment of chronic inflammatory dermatoses, including psoriasis, hidradenitis suppurativa and atopic dermatitis, offering high efficacy and safety for moderate-to-severe disease. However, standardised dosing regimens fail to account for inter-individual heterogeneity, leading to non-optimal drug exposure in certain patients. This may, in part, explain why primary non-response, secondary loss of response or adverse effects are observed in real-world practice. While empirical off-label adjustments are commonly employed, data-driven 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-exposure-response correlations. Although TDM provides reactive or proactive optimisation approaches, its threshold-based adjustments are limited by an inability to predict individual pharmacokinetic variability or future clinical outcomes. Model-informed precision dosing (MIPD) represents an evolution beyond conventional TDM by integrating population pharmacokinetic-pharmacodynamic models, patient-specific characteristics and Bayesian forecasting to deliver personalised, adaptive dosing recommendations. This approach captures inter-individual variability while linking serum drug concentrations to clinical response, enabling proactive dose adjustments using sparse or non-steady-state data. Emerging digital tools, point-of-care testing and integration of pharmacogenomics and biomarker profiling are expected to enhance MIPD's precision and accessibility. Once implemented in routine care, MIPD has the potential to transform biologic therapy dosing using a dynamic, patient-centric system that maximises clinical response, minimises overtreatment and supports sustainable healthcare delivery.

Journal of the European Academy of Dermatology and VenereologyVol. 40(3)
King's College London (GB), Ghent University Hospital (BE), Institute of Infection and Immunity (CA), University College London (GB)
Openalex Percentile: Top 22%
Psoriasis: Treatment and Pathogenesis
0.80
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.