Why is preclinical testing unable to predict human responses perfectly?

Preclinical testing often fails to perfectly predict human responses because current models lack sufficient predictive accuracy. Several factors contribute to this limitation:1

• Biological Differences: Animal models do not always mirror human physiology. Drugs that appear safe or effective in animals may prove ineffective, toxic, or even harmful in humans due to species-specific differences in drug metabolism and biological response.2
• Complexity of Modern Therapeutics: Newer agents, such as those involving genetic modification or cellular substances, often act through complex, indirect mechanisms that are not fully understood, making standardized validation difficult.1
• Human Heterogeneity: Human responses to treatments are multifactorial, influenced by an individual's unique genetic background, environment, and microbiome. Furthermore, factors such as age, existing disease states, and drug interactions cause significant variability in how different people respond to the same dose of a medication.13
• Limitations of Testing Models: The reliance on models that do not accurately simulate human disease processes leads to a high failure rate in clinical trials.21

Translational medicine aims to address these challenges by improving preclinical screening and incorporating direct human observations to better validate new therapies.1