Quantitative in vitro to in vivo extrapolation for human toxicology and drug development

TL;DR

This paper reviews the current state and challenges of quantitative in vitro to in vivo extrapolation (QIVIVE) methods, highlighting their potential to improve toxicity prediction, reduce animal testing, and advance safety assessment in drug development.

Contribution

It provides a comprehensive overview of QIVIVE techniques, addressing dosing, timing, individual variability, and integration of methods for complex toxicity predictions.

Findings

QIVIVE can predict in vivo toxicity from in vitro data.

Advances in toxicogenomics are bridging the gap between cell responses and organism effects.

Challenges remain in standardization, validation, and modeling of long-term toxicity.

Abstract

Traditional animal testing for toxicity is expensive, time consuming, ethically questioned, sometimes inaccurate because of the necessity to extrapolate from animal to human, and in most cases not formally validated according to modern standards. This is driving regulatory bodies and companies in backing alternative methods focusing on in silico and in vitro approaches. These are complex to implement and validate, and their wide adoption is not yet established despite legal directives providing an imperative. It is difficult to link a cell level response to effects on a whole organism, but the advances in high-throughput toxicogenomics towards elucidating the mechanism of action of substances are gradually reducing this gap and fostering the adoption of Next Generation Safety Assessment approaches. Quantitative in vitro to in vivo extrapolation (QIVIVE) methods hold the promise to reveal how to use in vitro -omics data to predict the potential for in vivo toxicity. They could improve lead compounds prioritisation, reduce time and costs, also in numbers of animal lives, and help with the complexity of extrapolating between species. We provide a description of QIVIVE state of the art, including how the problems of dosing and timing are being approached, how in silico simulation can take into account the variability of individuals, and how multiple techniques can be integrated to face complex tasks like the prediction of long term toxicity, including a close look into the open problems and challenges ahead.