Novel Lipidomic-based Approach to Liver Drug Safety

Hepatotoxicity is the leading cause for drug withdrawal from market and clinical trial. Traditionally, liver safety risk assessment studies for humans have been conducted in animals during advanced preclinical or clinical phases of drug development.

However, the incredible costs associated with these late-stage drug failures have compelled the research community to screen for toxicity earlier in the drug discovery phase.

Furthermore, the ethical concerns and often poor predictivity around using animal models have encouraged researchers to validate human-based models for toxicity screening. The introduction of complex 3D liver spheroids this past decade has greatly improved predictive screening capabilities, as they can include several cell types and be maintained for several weeks.

Numerous endpoints are possible, but typically in high-throughput screens, only metabolic cell health (ATP) is measured. The ‘omics’, such as genomics, proteomics, and metabolomics, have recently entered pharmaceutical research in both drug discovery and drug development, but few attempts in applying omics in high-throughput safety risk assessment have been attempted to date. The omics approach is quite attractive, because in addition to its sensitivity, it allows for generation of a massive amount of data from a small quantity of cellular material.

Compared to traditional, low-density screening methods, this novel approach allows for multiple interconnected variables (lipids) to be measured simultaneously, providing a snapshot of the cellular status from the lipid perspective at the molecular level.

In this webinar, InSphero Director of Business Development Dr. Sue Grepper described a complex and high throughput 3D human liver model for assessing hepatotoxicity of therapeutics, along with a multitude of endpoints that can be assessed. University of Perugia Professor Laura Goracci showcased an innovative lipidomic method that can be applied to these liver organoids to predict adverse drug effects in an early discovery phase.

A case study dataset highlighting 20 drugs belonging to five different therapeutic chemical classes was presented.

In this webinar, we covered:

  • The advantages of using a 3D human liver model for identifying liver risk assessment
  • A novel lipidomics approach for hepatotoxicity assessment at an early phase in drug discovery
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