Evaluating Biologics-induced Liver Injury Using Metabolomics and Computational Modeling

Evaluating Biologics-induced Liver Injury Using Metabolomics and Computational Modeling

Biologics, which include vaccines, gene therapies, and recombinant therapeutic proteins, are a type of drug derived from biological sources. Although highly valuable, their use comes with a significant challenge—the potential for liver injury. For example, the clinical development of cimaglermin alfa (GGF2), which was intended for heart failure therapy, was terminated due to elevated biomarkers indicating liver injury and dysfunction. Other drugs, such as tocilizumab, require liver testing before and during treatment.

Challenges in Testing Biologic-induced Liver Injury (BILI)

Evaluating biologics-induced liver injury during development is challenging because biologics are specific towards human targets. Therefore, these drugs may have limited cross-reactivity in other species, making traditional animal models less effective. Scientists have developed various methods to study biologics-induced liver injury to overcome these challenges.

Methods for Studying Biologics-induced Liver Injury

Metabolomics and Its Role in Biologics Safety Assessment

Metabolomics is a cutting-edge analytical technique that involves the comprehensive profiling of small molecules (metabolites) present in biological samples, such as blood or urine. By characterizing these metabolites, researchers can gain insight into the metabolic changes and the toxicity mechanisms induced by biologics and their impact on the liver. When accessed during preclinical and clinical studies, these biomarkers can serve as early indicators of hepatotoxicity, helping identify potential safety concerns during drug development.

Liver-on-a-chip Models Recapitulate Liver Structure and Function

Liver-on-a-chip models have emerged as a groundbreaking technology that bridges the gap between cell culture and animal studies. These microphysiological systems are engineered to mimic the intricate structure and function of the human liver, enabling researchers to study drug metabolism and toxicity in a more physiologically relevant environment. For example, the Liver Acinus Microphysiology System (LAMPS) recapitulates the liver acinus structure functioning and can be used to evaluate liver responses to drugs.

Computational Modeling for Hepatotoxicity Prediction

Computational algorithms, such as machine learning and artificial intelligence, can integrate diverse data sources, including metabolomic data, genetic information, and clinical parameters, to create predictive models of drug-induced liver injury. Such models include quantitative systems toxicology (QST) platforms that simulate the effects of small molecules (DILIsym®) and the effects of biologics (BIOLOGXsym™) on the liver. The BIOLOGXsym™ platform focuses on macromolecules and represents pathways specifically used with biologics.

By using these models, researchers can assess the potential hepatotoxicity of a biologics before proceeding to expensive and time-consuming clinical trials. This not only saves resources but also enhances patient safety by identifying high-risk candidates early in the drug development process.

A Three-Pronged Approach to Studying Biologics-induced Liver Injury

In a recent study,1 we applied metabolomics, liver-on-a-chip, and computational modeling to evaluate the effects of biologics on the liver. Metabolon’s Global Discovery Panel was used to perform metabolomic analysis from the liver-on-a-chip model after treatment with tocilizumab revealed signatures of increased hepatocyte steatosis, oxidative stress, and tissue remodeling. We then leveraged this metabolomics data and data from physiologically-based pharmacokinetic modeling in BIOLOGXsym™ simulations to reproduce clinically observed liver signals. This integration meant that the response of human liver tissue to biologics can be evaluated in a highly controlled and representative environment. The BIOLOGXsym™ simulation was also used to model concurrent treatments with tocilizumab and acetaminophen, demonstrating that this modeling approach can also be used to test the effect of drug-drug interactions on the liver.

The quest to understand and mitigate biologic-induced liver injury has led to the integration of cutting-edge technologies like metabolomics analysis and liver-on-chip models. Metabolomics analysis has proven invaluable in unraveling the metabolic changes associated with drug-induced liver injury, providing crucial insights into early detection and risk assessment during drug development. Together, these technologies hold the promise of advancing drug development and ensuring the safe and effective use of biologic drugs.


  1. Beaudoin JJ, Clemens L, Miedel M, et al. The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury. Int. J. Mol. Sci. 2023, 24(11), 9692. doi:10.3390/ijms24119692
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