Can alternatives to animal testing yield useful information regarding biological mechanisms and drug discovery?

Abstract

Establish alternative strategies to standard animal experiments decrease animal utilization and simultaneously enhance the reliability of biological and disease models. This review highlights advancements in three areas: in vitro culture platforms, disease modeling, and in silico simulations. We first discuss the innovative in vitro approaches, including 2D coculture systems, 3D spheroids, organoids, and organ-on-chip models, which facilitate the creation of physiologically relevant environments. Then, we focus on cell selection and characterization in disease modeling, with a particular focus on bone fracture healing and inflammation. We further review the potential of in silico simulations, including molecular docking, machine learning (ML) approaches, and pharmacokinetics-pharmacodynamics (PK/PD) modeling, to predict drug efficacy, interactions, and biological outcomes. These alternative strategies provide the potential for obtaining accurate and consistent results, thereby enhancing biomedical research and decreasing dependence on animal models. The Translational Potential of this Article: This review examines in vitro organoids, microphysiological systems, and computational models as alternatives to animal testing. These methods enhance our understanding of biological mechanisms. They also reduce the requirement for animal models. Ultimately, they help accelerate drug discovery that can directly benefit patients.