Virtual Control Groups in Non-clinical Toxicity Studies: Impacts on Toxicologic Clinical Pathology Data...

Area of Science:

• Toxicology
• Drug Development
• Animal Welfare

Background:

• The use of virtual control groups (VCGs) is an emerging strategy to reduce animal use in non-clinical toxicology studies.
• VCGs generate control data from historical datasets to match specific study designs, aiming to replace concurrent control groups (CCGs).

Purpose of the Study:

• This review critically examines two proof-of-concept studies on VCGs in rat toxicology models.
• To identify and discuss challenges associated with VCG implementation, particularly concerning data reproducibility.

Main Methods:

• Focus on two recent proof-of-concept studies utilizing VCGs in rat models.
• Analysis of quantitative endpoints, with a specific emphasis on clinical pathology parameters.

Main Results:

• Non-reproducibility of quantitative endpoints was a consistent issue, most notably with clinical pathology parameters.
• Inconsistencies between VCG and CCG data were observed across the reviewed studies.

Conclusions:

• Observed inconsistencies in clinical pathology may lead to misconceptions about biomarker accuracy and impact safety monitoring.
• Challenges include difficulties in identifying organ dysfunction, interfering with weight-of-evidence approaches, and causing data interpretation issues.
• Alternative methods like blood microsampling and justified use of recovery animals are also considered to reduce animal use.