In silico modeling offers a promising alternative to animal testing in drug discovery, though further advancements are needed before computational methods can fully replace animal models.
Over the past decade, increasing emphasis on ethical considerations has driven the development of innovative alternatives to animal testing. Across diverse industrial sectors, including cosmeceuticals, pharmaceuticals, medical-and food-grade chemicals, there is a growing demand for affordable, reliable, and robust protocols that can reduce or replace the use of animal models. While no single alternative can serve as a complete one-to-one substitute for assays dependent on complex physiological processes, approaches such as in vitro assays, high-throughput screening, organ-on-a-chip models, and in silico modeling have shown significant potential. These methods can provide complementary data, enabling researchers to extrapolate potential animal responses to various treatments.1 In silico modeling refers to the experiments conducted using computational platforms, mathematical models, and simulation tools/software, such as PyRx, Schrödinger, MolSoft, and Molecular Solutions, to replicate the complex biological systems. These models are recognized as the part of the “new approach methodologies” or “nonanimal methods.”2 Fundamentally, these theoretical computational predictions are based on the structural chemistry of chemical entities, such as ligands and target proteins in the case of drug discovery, to establish quantitative structure–activity relationships (QSAR). This relies on the premise that structurally similar chemicals produce similar biological responses, enabling the activity of one chemical or group to inform predictions about the properties and mechanisms of related compounds. Although the “similarity paradox,” where structurally similar molecules exhibit differing biological activities, remains a challenge, in silico modeling has proven highly valuable. It is particularly effective in validating in vitro results and in optimizing the drug candidates through computer-aided drug design.3–5 For instance, a study by Passini et al. demonstrated that in silico simulation models not only outperformed animal models in predicting clinical pro-arrhythmic cardiotoxicity but also offered greater speed, accuracy, cost-efficiency, and effectiveness.6 The extent to which such computational studies can be performed are wide, wherein they may be employed based on the structure-based or ligand-based categorization of the approach.7 While the structure-based drug design approach includes techniques such as molecular docking, molecular dynamics simulations, and homology modeling,8 ligand-based drug design relies more on the establishment of QSAR relationships and ligand-based pharmacophore modeling.9 Apart from de novo ligand designing and computational toxicology to design new drugs from the scratch and to predict potential toxicity of drug molecules, respectively.10 In addition, there exist established computational algorithms to determine the (Absorption, Distribution, Metabolism, and Excretion)11 as well as gastrointestinal absorption and brain penetration of the small molecules.12 Nevertheless, these methods are still evolving and have yet to achieve universal adoption, pending the establishment of globally accepted benchmarks. The capabilities of artificial intelligence and computational simulations, while expanding, remain limited in replicating the full complexity of human physiological processes. Further advancements in mathematical modeling and biological understanding will be necessary before in silico methods can fully replace animal testing. The purpose of this editorial is to throw light on an impending issue related to the use of animals in research, a scientific concern that is likely to grow in importance in the coming years, significantly reshaping the future of research methodologies and encourage the researchers globally to adapt and adopt these emerging trends in drug testing.
Prasad et al. (Wed,) reported a editorial. In silico modeling vs. Animal testing was evaluated. In silico modeling offers a promising alternative to animal testing in drug discovery, though further advancements are needed before computational methods can fully replace animal models.