Chief Scientific Officer Cellworks Research India Pvt Limited Bangalore, Karnataka, India
Disclosure(s):
Ansu Kumar, Master of Science: No financial relationships to disclose
Objectives: Hyperbilirubinemia, characterized by elevated total blood bilirubin levels including both unconjugated and conjugated forms, serves as an important diagnostic marker for drug-induced liver toxicity associated with a wide range of medications. This study aims to develop a mechanistic model for assessing the risk of hyperbilirubinemia, using genetic markers.
Methods: We developed an ordinary differential equations (ODE) based mechanistic model of human bilirubin metabolism incorporating key biological processes such as the synthesis of unconjugated bilirubin, its hepatic uptake, conjugation, and elimination through hepatic and renal pathways. The model includes hepatic transporters and enzymes, such as OATP1B1, MRP2, MRP3, and UGT1A1, which are involved in the hepatic uptake and elimination of bilirubin. The model was parametrized using in-vitro and published human data and validated using bilirubin disposition in healthy subjects as well as individuals with genetic diseases such as Gilbert’s and Dubin-Johnson syndromes. The impacts of genetic mutations and therapies on these enzymes and downstream bilirubin levels were assessed using the mechanistic model.
Results: A 90% reduction in OATP1B1 activity increased both unconjugated and conjugated bilirubin (1.58-fold and 2.2-fold respectively), mimicking data from individuals with mutations in OATP1B1. Sensitivity analysis of OATP1B1, MRP2, and UGT1A1 revealed increased OATP1B1 sensitivity in the presence of low UGT1A1 activity. Model simulations linked nilotinib-induced hyperbilirubinemia to UGT1A1 mutations, and were also used to assess the risk of hyperbilirubinemia associated with varying doses of nelfinavir, atazanavir, and TAK-875, based on their off-target effects on transporters. The results demonstrated that uncertainty in free drug concentration could be a crucial factor in hyperbilirubinemia, especially for highly protein-bound drugs.
Conclusions: We used a mechanistic model of human bilirubin metabolism to identify critical factors involved in drug-induced hyperbilirubinemia. This approach may help determine risk assessment for hyperbilirubinemia, using drugs inhibitory in vitro data coupled with patient pharmacogenetic data associated with OATP1B1, UGT1A1 and MRP2 mutations. Patient-specific pharmacogenetic data is necessary for further validation of this approach to assess the risk of drug-induced hyperbilirubinemia.
Citations: 1. Devarbhavi H. (2012). An Update on Drug-induced Liver Injury. Journal of clinical and experimental hepatology, 2(3), 247–259. 2. Abumiya, M., Takahashi, N., Niioka, T., Kameoka, Y., Fujishima, N., Tagawa, H., Sawada, K., & Miura, M. (2014). Influence of UGT1A1 6, 27, and 28 polymorphisms on nilotinib-induced hyperbilirubinemia in Japanese patients with chronic myeloid leukemia. Drug metabolism and pharmacokinetics, 29(6), 449–454. 3. Tan, Y., Ye, Y., & Zhou, X. (2020). Nilotinib-induced liver injury: A case report. Medicine, 99(36), e22061.
