Ahenk Zeynep Sayin1, Lars Kuepfer1
1Institute for Systems Medicine with Focus on Organ Interaction, University Hospital RWTH Aachen
Introduction: Bilirubin plays a crucial role in the body’s elimination of hemoglobin and heme-containing proteins. Following its initial synthesis in the reticuloendothelial system, bilirubin is conjugated in hepatocytes and excreted to the bile before it is again converted to urobilinoids in the gastrointestinal tract. Bilirubin metabolism can be affected by genetic and metabolic conditions, resulting in abnormal levels of bilirubin. Disorders like Gilbert syndrome, Crigler-Najjar syndrome, and Dubin-Johnson syndrome involve different types of hyperbilirubinemia. Gilbert syndrome results from decreased activity of UDP-glucuronosyltransferase 1A1 (UGT1A1) enzyme, leading to mild unconjugated hyperbilirubinemia [1]. Crigler-Najjar syndrome involves a near-complete (Type 2) or complete absence (Type I) of UGT1A1 activity, resulting in more severe unconjugated hyperbilirubinemia [1]. In contrast, Dubin-Johnson syndrome results from impaired bile excretion, causing conjugated hyperbilirubinemia [2]. Understanding the functional consequences of these disorders in bilirubin metabolism is necessary for accurate diagnosis and treatment, as they can significantly affect neurological health and overall health status [3]. Objectives: This study builds on current knowledge of bilirubin metabolism and associated disorders, with the aim of creating an accurate physiologically-based computational model for analysis of various clinical questions in bilirubin metabolism. The primary goals are to characterize bilirubin levels in health and disease, and to thus explain the interindividual variability in disorders of bilirubin metabolism using real-world data along with the data from literature. Methods: Our model was developed with PK-Sim® and MoBi® from the Open System Pharmacology (OSP) Suite [4]. To determine the kinetic parameters of the model, previously published experimental data, including baseline measurements of plasma bilirubin concentrations, conjugated bilirubin fraction, and excretion rates, in healthy individuals as well as patients with different disorders were used. This included in particular patient data from the Explorys database which is a commercial database comprising electronic health records collected from health institutions in the United States. Altogether, the Explorys database involves data of almost one million unique patients with liver-related health conditions. To replicate the bilirubin levels reported in the literature and Explorys database, the Vmax of the enzyme or transporter affected in each disorder were adjusted, focusing on the bilirubin form that changes the most significantly in each syndrome: unconjugated bilirubin for Gilbert and Crigler-Najjar syndrome, and conjugated bilirubin for Dubin-Johnson syndrome. For the population simulations, a virtual population of 1,000 individuals was created. To account for variability in biological processes, a normal distribution of Vmax values was applied, with a standard deviation of up to 25% of the mean [6]. Results: The model includes bilirubin synthesis, hepatic uptake, conjugation, and biliary excretion. It also involves systemic efflux, reduction of conjugated bilirubin to unconjugated bilirubin and further to urobilinogen. Additionally, the model incorporates fecal and urinary excretion, as well as enterohepatic circulation. The model simulates bilirubin levels in both healthy individuals and patients with bilirubin disorders. The predictions of our model for healthy-state closely matches the observed levels. Population simulations conducted to replicate the bilirubin levels of each disorders show that Gilbert syndrome requires a moderate reduction in UGT1A1 activity, while Crigler-Najjar syndrome needs a severe reduction. In contrast, Dubin-Johnson syndrome is characterized by an extreme impairment of multidrug resistance-associated protein 2 (MRP2) activity, nearly eliminating its function. Conclusion: In this study, a physiologically-based computational model is developed to represent the bilirubin metabolism, involving key enzymatic and transport processes. Unlike previous studies that used experimental data sourced from controlled studies, this work integrates real-life clinical data from health institutions in the United States, extracted from Explorys database. Overall, this study offers a clinically relevant model which could improve the understanding of bilirubin homeostasis and hepatic function in bilirubin metabolism disorders.
1. Ascher Bartlett, J.M. and J. Shah, Disorders of Bilirubin Metabolism, in Benign Hematologic Disorders in Children: A Clinical Guide, D.M. Kamat and M. Frei-Jones, Editors. 2021, Springer International Publishing: Cham. p. 353-365. 2. Erlinger, S., I.M. Arias, and D. Dhumeaux, Inherited Disorders of Bilirubin Transport and Conjugation: New Insights Into Molecular Mechanisms and Consequences. Gastroenterology, 2014. 146(7): p. 1625-1638. 3. Pranty, A.I., S. Shumka, and J. Adjaye, Bilirubin-Induced Neurological Damage: Current and Emerging iPSC-Derived Brain Organoid Models. Cells, 2022. 11(17). 4. Kuepfer, L., et al., Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model. CPT: Pharmacometrics & Systems Pharmacology, 2016. 5(10): p. 516-531. 5. Willmann, S., et al., PK-Sim®: a physiologically based pharmacokinetic ‘whole-body’ model. BIOSILICO, 2003. 1(4): p. 121-124. 6. Storey, J.D., et al., Gene-expression variation within and among human populations. Am J Hum Genet, 2007. 80(3): p. 502-9.
Reference: PAGE 33 (2025) Abstr 11670 [www.page-meeting.org/?abstract=11670]
Poster: Drug/Disease Modelling - Absorption & PBPK