Written by: Saira Loane
Edited by: Caroline Babisz, Natasha Barrow & Ariyana Rayatt
Traditional animal models, while historically valuable for understanding biological processes and developing treatments¹, often fail to predict human responses due to species differences. Failures like the thalidomide tragedy, where animal testing missed congenital disabilities, highlight the need for more human-relevant models 2⁻3. Alongside the clinical concerns, are the ethical concerns of using animals for research, with increasing public support for humane research further accelerating the adoption of advanced alternatives.
Scientists frequently use invertebrate models to study biology and disease mechanisms due to their affordability, ease of handling, short lifespans, and simple structures. These models have proven valuable for research on human genes, diseases, and neurodegenerative disorders 4. Genetic modifications and inserted markers allow researchers to observe biological effects, while their short lifespan makes them ideal for studying ageing and disease progression 5
A notable example is the Drosophila (fruit fly) model used to study Parkinson’s disease. Flies engineered with mutated α-synuclein provide insights into neuronal degeneration and serve as platforms for testing potential treatments 6. Despite their usefulness for genetic studies and drug testing, invertebrate models cannot fully replicate mammalian physiology, which remains essential for understanding human diseases and treatments 5.
To complement these invertebrate models, researchers also use, in vitro methods which offer controlled environments that are accessible, cost-effective, and reproducible. These models enable scientists to conduct mechanistic studies and drug screenings using human-derived cells. For example, three-dimensional (3D) liver co-culture systems predict drug-induced liver injury more accurately than traditional methods 7.
However, these in vitro models often oversimplify complex biological systems and lack long-term data, making it difficult to assess the chronic effects of substances 8. For example, traditional 2D in vitro cultures, which consist of flat layers of cells grown on artificial surfaces, lack essential cell-cell and cell-matrix interactions. For instance, 2D cancer cell cultures often fail to replicate tumour heterogeneity and microenvironmental complexity, leading to discrepancies in drug efficacy between lab and clinical settings 9.. These shortcomings of both invertebrate and traditional in vitro models contribute to high failure rates in clinical trials, particularly in oncology, where approximately 97% of drug candidates fail to receive FDA approval, underscoring the need for more predictive preclinical models¹⁰. This has opened the door for the next wave of in vitro models.
This push for New Approach Methodologies (NAMs) aligns with regulatory standards set by Animal Ethical Committees, following the "four Rs": Reduction, Refinement, Replacement, and Responsibility 11,12.
Innovative approaches are transforming drug toxicity assessments, providing ethical, accurate, and cost-effective alternatives. Techniques such as in vitro assays, computational models, and organ-on-a-chip (OoC) technology offer promising solutions 13⁻14. For example, in vitro methods have replaced inhumane tests like the LD50 for BOTOX by using cultured neurons instead of live animals⁷. Additionally, 3D liver co-culture systems more accurately predict drug-induced liver injury, while heart-on-a-chip models replicate cardiac arrhythmias, allowing more profound insights into human-specific drug effects15. These advancements mark a shift toward more reliable, humane, and predictive biomedical models.
In the case of 3D in vitro models, companies like PeptiMatrix and MOMO Biotech are overcoming the limitations of traditional 2D cultures, which lack cell-cell interactions and physiological relevance. PeptiMatrix offers a synthetic 3D peptide hydrogel, while MOMO Biotech’s MEmic replicates the tumour microenvironment for better cancer treatment predictions. These innovations provide more accurate, human-relevant alternatives for drug testing.
Ogan-on-a-chip (OoC) technology integrates cell biology and microengineering to mimic human tissue environments, allowing for real-time monitoring of physiological responses16. This innovation has diverse applications, including drug screening and personalised medicine. For instance, heart-on-a-chip technology models cardiac arrhythmias, providing deeper insights into human-specific drug effects17. The ability of these models to replicate the cell-cell and cell-matrix interactions in a 3D model has driven the development of biomimetic models such as OoCs, replicating human organ functions with enhanced physiological relevance18. Moreover, advancements like 3D printing are making OoC production more cost-effective, paving the way for automation in medical research19.
Alongside these experimental models, in silico approaches refine drug discovery by leveraging computational algorithms to predict molecular interactions with high precision. Virtual drug screening is widely used in silico techniques where molecular docking simulations predict how a drug molecule interacts with a biological target, such as a protein. For example, computational modelling of SARS-CoV-2 spike protein interactions helped identify potential antiviral drugs, accelerating the drug repurposing process20. These advancements demonstrate the growing role of AI-driven simulations in complementing experimental models to enhance preclinical research.
Several startups are pioneering advancements in alternative research models, accelerating the transition away from animal testing:
Jetbio, (2023, UK) – A start-up that has developed reactive jet impingement (ReJI) 3D bioprinting, which creates biomimetic cell-filled gels for drug testing and tissue engineering, improving human organ-like models.
PeptiMatrix (2023, UK) – A University of Nottingham spin-out developing fully synthetic, customisable peptide hydrogels for 3D cell culture, offering an animal-free alternative for drug development and biomedical research.
MOMO-biotech, (2022, London) – This start-up has created MEmic, an in vitro model of the tumour microenvironment, enhancing predictions of cancer treatments and immune cell efficacy.
Nagi-biosciences, (2019, Switzerland) – Nagi-biosciences has developed SydLab™, which integrates OoC technology, robotics, and imaging for automated high-throughput compound screening.
Predictive, LLC, (2019, US) – The US-based biotechnology company, specialises in AI-based in silico testing with tools like STopTOX and PredMD, which predict toxicity and support regulatory compliance, reducing reliance on animal testing.
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