Integrating Human Intestinal Organoids into FDA's New Approach Methodologies for Drug Discovery.

Area of Science:

• Biomedical Engineering
• Drug Discovery
• Toxicology

Background:

• Traditional toxicity testing relies on animal models, which exhibit significant physiological and genetic differences from humans, leading to high drug attrition rates.
• Complex diseases like inflammatory bowel disease (IBD) face over 85% attrition in clinical trials due to species-specific differences in preclinical models.
• Regulatory bodies like the FDA are promoting New Approach Methodologies (NAMs) to enhance human-relevant testing systems.

Purpose of the Study:

• To highlight the potential of human intestinal organoids (HIOs) as advanced, human-relevant models for preclinical drug toxicity testing.
• To demonstrate how HIOs can bridge the gap between in vitro assays and clinical outcomes in drug development.
• To support the FDA's NAMs roadmap by showcasing HIOs for improved drug safety assessment and reduced animal model reliance.

Main Methods:

• Utilizing human intestinal organoids (HIOs) that replicate human gut architecture, function, and cellular diversity.
• Employing HIOs to study drug absorption, metabolism, and toxicity in a controlled in vitro environment.
• Leveraging patient-derived intestinal organoids (PDOs) in emerging clinical trials to validate preclinical findings.

Main Results:

• HIOs faithfully replicate human intestinal complexity, enabling accurate study of drug effects.
• HIOs facilitate the prediction of toxicokinetics and pharmacokinetics, offering a more reliable assessment than traditional methods.
• Patient-derived organoids (PDOs) show promise in clinical trials, confirming the translational potential of organoid technology.

Conclusions:

• Human intestinal organoids (HIOs) represent a transformative tool for preclinical drug safety assessment in intestinal diseases.
• HIOs provide a human-relevant platform that aligns with regulatory trends and can significantly reduce reliance on animal models.
• The integration of HIOs and PDOs into drug development pipelines promises to improve prediction accuracy and decrease clinical trial attrition rates.