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Background <p>Early detection of drug-induced liver injury (DILI) during drug development is crucial for reducing drug attrition and ensuring the safety of patients. A versatile, biologically interpretable, and dose-dependent screening approach is therefore needed to inform early stop/go decisions and therapeutic margins.</p> Methods <p>We have developed AEGIS (Apoptotic Effector Genes In Safety), a preclinical DILI risk screening and prioritization tool that quantifies dose dependent perturbation of apoptosis-regulating transcription factors from transcriptomics data. We profiled transcriptomic responses after short exposures across primary human hepatocytes (PHH), HepG2/C3A cells, RAW 264.7 cells, and an acute Balb/c mouse study. From these profiles, AEGIS provides quantitative risk scores to rank and prioritize compounds and exposures.</p> Results <p>Here we show that AEGIS distinguishes compounds with different degree of DILI concern, achieving 86% specificity, 75% sensitivity and 90% precision in PHHs. We demonstrate versatility in data type usage and clinical translation of AEGIS with accurate predictions across species, in vitro and in vivo models, and therapeutic modalities. In addition, we apply AEGIS in a precision medicine context during drug-development within the pharmaceutical industry and investigate the contribution of underlying liver disease on DILI severity. Our findings indicate that cells from patients with metabolic dysfunction-associated steatotic liver disease (MASLD) develop more severe DILI from treatment with troglitazone, aligning with preclinical observations.</p> Conclusions <p>Using AEGIS early in drug discovery exemplifies a more efficient approach to identify and mitigate potential safety concerns. This can reduce the need for animal testing, and accelerates drug discovery, ultimately providing the right medicines to patients more quickly.</p>

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Apoptotic signatures allow early and rapid screening of drug-induced liver injury to accelerate drug discovery

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月24日

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  • John Hellgren,
  • Bhavik Chouhan,
  • Aydar Uatay,
  • Ramy Elgendy,
  • Julia Lindgren,
  • Naoko Toki,
  • Alessandro Bonetti,
  • Aditi Chaudhari,
  • Kenneth Pryde,
  • Patrik Andersson,
  • Marie Kalm,
  • Fredrik Karlsson,
  • Johanna Sagemark,
  • Dominic P. Williams,
  • Jennifer Y. Tan,
  • Bino John,
  • John Gallon

摘要

Background

Early detection of drug-induced liver injury (DILI) during drug development is crucial for reducing drug attrition and ensuring the safety of patients. A versatile, biologically interpretable, and dose-dependent screening approach is therefore needed to inform early stop/go decisions and therapeutic margins.

Methods

We have developed AEGIS (Apoptotic Effector Genes In Safety), a preclinical DILI risk screening and prioritization tool that quantifies dose dependent perturbation of apoptosis-regulating transcription factors from transcriptomics data. We profiled transcriptomic responses after short exposures across primary human hepatocytes (PHH), HepG2/C3A cells, RAW 264.7 cells, and an acute Balb/c mouse study. From these profiles, AEGIS provides quantitative risk scores to rank and prioritize compounds and exposures.

Results

Here we show that AEGIS distinguishes compounds with different degree of DILI concern, achieving 86% specificity, 75% sensitivity and 90% precision in PHHs. We demonstrate versatility in data type usage and clinical translation of AEGIS with accurate predictions across species, in vitro and in vivo models, and therapeutic modalities. In addition, we apply AEGIS in a precision medicine context during drug-development within the pharmaceutical industry and investigate the contribution of underlying liver disease on DILI severity. Our findings indicate that cells from patients with metabolic dysfunction-associated steatotic liver disease (MASLD) develop more severe DILI from treatment with troglitazone, aligning with preclinical observations.

Conclusions

Using AEGIS early in drug discovery exemplifies a more efficient approach to identify and mitigate potential safety concerns. This can reduce the need for animal testing, and accelerates drug discovery, ultimately providing the right medicines to patients more quickly.