The ideal model in atherosclerosis and dyslipidaemia - does it exist?

Area of Science:

• Pharmacology and Toxicology
• Translational Medicine
• Drug Discovery and Development

Background:

• Preclinical drug discovery relies heavily on animal models for decision-making.
• A significant challenge in drug development is the poor translation of animal study results to human clinical trials.
• Specific disease models, such as those for dyslipidemia and atherosclerosis, may set unrealistic expectations.

Purpose of the Study:

• To critically evaluate the utility of animal models in preclinical drug discovery.
• To propose an alternative approach for improving the translation of drug discovery findings to human studies.
• To address the limitations of current animal models in predicting human responses.

Main Methods:

• This is an editorial, not an experimental study.
• The author's perspective is based on existing literature and experience in drug discovery.
• Discussion focuses on the conceptual framework of disease modeling.

Main Results:

• Animal models for diseases like dyslipidemia and atherosclerosis frequently fail to predict human outcomes.
• The reliance on traditional animal models can lead to inflated expectations and wasted resources.
• A shift towards mechanistic understanding is suggested.

Conclusions:

• The current paradigm of using animal models for specific diseases in drug discovery may be flawed.
• A 'bottom-up', mechanistic approach is advocated to enhance the predictive validity of preclinical research.
• Adopting a mechanistic strategy could improve the success rate of drug development and reduce attrition in clinical trials.