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Updated: Jun 26, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

Are animal models predictive for humans?

Niall Shanks¹, Ray Greek, Jean Greek

¹Americans For Medical Advancement, 2251 Refugio Rd Goleta, CA 93117, USA. niall.shanks@wichita.edu

Philosophy, Ethics, and Humanities in Medicine : PEHM

|January 17, 2009

Summary

This summary is machine-generated.

Animal models in toxicology and pathophysiology often fail to accurately predict human responses to drugs and chemicals. Empirical analysis reveals significant limitations in their predictive power for human outcomes.

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Area of Science:

Philosophy of Science
Toxicology
Pathophysiology
Evolutionary Biology
Developmental Biology
Genomics

Background:

The philosophy of science aims to clarify scientific terms and their applications.
A key scientific term under scrutiny is 'predict' and its use in research.
The reliability of animal models for predicting human outcomes is a contentious issue.

Purpose of the Study:

To critically evaluate the scientific evidence for using animal models to predict human outcomes, particularly in toxicology and pathophysiology.
To assess the predictive validity of animal models in biomedical research.

Main Methods:

Empirical analysis of animal models using scientific tools.
Critical examination of the term 'predict' within scientific contexts.
Review of findings from evolutionary and developmental biology, gene regulation, epigenetics, complexity theory, and comparative genomics.

Main Results:

Empirical analysis demonstrates that animal models significantly fall short of accurately predicting human responses.
The predictive limitations are consistent with established knowledge in related biological fields.

Conclusions:

Animal models, especially in toxicology and pathophysiology, lack credible evidence for reliably predicting human outcomes.
Understanding of evolutionary biology, genomics, and epigenetics underscores the inherent challenges in interspecies prediction.