Seonghwa Song 1, Thanh Thi Tran 1, Ngoc-Anh Thi Vu 1, Seongwon Park 1, Hwi-yeol Yun 1,2,3, Jung-woo Chae 1,2,3, Soyoung Lee 1
1 College of Pharmacy, Chungnam National University (Daejeon, Republic of Korea), 2 Senior Health Convergence Research Center, Chungnam National University (Daejeon, Republic of Korea), 3 Department of Bio-AI convergence, Chungnam National University (Daejeon, Republic of Korea)
Introduction / Objective
Abrocitinib is an oral selective Janus kinase 1 (JAK1) inhibitor approved for the treatment of moderate-to-severe atopic dermatitis (AD), a chronic inflammatory disease requiring long-term systemic therapy1. Abrocitinib is primarily metabolized by cytochrome P450 enzymes (CYP2C19, CYP2C9, and CYP3A4), and systemic exposure may vary according to inter-individual variability, CYP genotype, ethnic differences, and concomitant medications 6. However, a mechanistic PK approach to characterize these drug-specific properties has not been fully integrated with exposure–response modeling. Therapeutic benefit in AD is determined not only by systemic exposure but also by sustained clinical improvement over time. Clinical data indicate that treatment response does not occur immediately following changes in plasma concentration and exhibits delayed pharmacodynamic characteristics 2,7. Therefore, plasma concentration alone may be insufficient to account for the time-dependent nature of clinical response. These considerations highlight the need for a structural pharmacokinetic–pharmacodynamic (PK–PD) model linking systemic exposure to clinically relevant endpoints such as the Eczema Area and Severity Index (EASI) and Investigator’s Global Assessment (IGA) 5. This study aimed to establish a PK–PD framework that structurally integrates exposure–response relationships based on a human physiologically based pharmacokinetic (PBPK) model developed via interspecies extrapolation, enabling quantitative evaluation of exposure variability and its impact on treatment response in AD.
Methods
Preclinical PK data were obtained from male Sprague–Dawley rats (n = 6) following a single oral dose of abrocitinib (10 mg/kg). Plasma concentrations were quantified using validated ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS), and exposure parameters (Cmax, AUClast) were derived by non-compartmental analysis. A rat PBPK model was developed in PK-Sim® (version 12.0) to reproduce observed exposure profiles 4. The model was translated to a healthy human PBPK model through interspecies scaling incorporating species-specific physiology, fraction unbound, and CYP-mediated clearance pathways (CYP2C19, CYP2C9, CYP3A4). The human PBPK model was evaluated against published clinical PK data across oral doses ranging from 3 to 800 mg under single and multiple dosing. Predictive performance was assessed using predicted-to-observed (P/O) ratios for Cmax and AUClast, mean relative deviation (MRD), and geometric mean fold error (GMFE), applying a predefined 2-fold criterion. The validated PBPK model was exported to MoBi® (version 12.0) to construct a profile-driven PK–PD framework. PBPK-predicted plasma concentration–time profiles were mechanistically linked to EASI dynamics through an effect-site delay component and an indirect response (turnover) model. Responder endpoints (EASI-50, EASI-75, and EASI-90) were defined based on baseline-normalized improvement.
Results
The rat PBPK model was developed to characterize systemic exposure following a single oral dose (10 mg/kg), achieving robust predictive accuracy within the predefined two-fold criterion(MRD 1.06; GMFE 1.47 for Cmax and 1.05 for AUClast). Based on the structure of the rat PBPK model, a human PBPK model was established via interspecies extrapolation incorporating fraction unbound, specific intestinal permeability, and species-specific CYP-mediated metabolic clearance. For 100 mg and 200 mg multiple-dose regimens, P/O ratios for Cmax and AUClast were within 0.5–2.0. Overall prediction accuracy satisfied the predefined two-fold criterion (MRD 1.29 and 1.41; GMFE 1.27 and 1.29). The validated human PBPK model was implemented in MoBi® to construct a mechanism-based PK–PD framework. Within this framework, PBPK-predicted plasma concentration–time profiles were mechanistically linked to dynamic EASI trajectories and corresponding responder endpoints (EASI-50/75/90) under clinically relevant 100 mg and 200 mg dosing regimens, thereby laying the groundwork for subsequent exposure–response analyses and long-term simulation.
Conclusions
An interspecies-scaled PBPK model of abrocitinib was successfully validated and integrated into a profile-driven PK–PD framework linking systemic concentration–time profiles to dynamic EASI response and responder endpoints. This integrated platform establishes a mechanistic basis for future exposure–response quantification and long-term clinical scenario simulation in atopic dermatitis.
References:
References
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Reference: PAGE 34 (2026) Abstr 12262 [www.page-meeting.org/?abstract=12262]
Poster: Drug/Disease Modelling - Other Topics