The movement to phase out animal testing in scientific research is gaining momentum worldwide. Last November, the UK government announced a plan to eliminate animal testing for skin irritation this year, with further reductions in studies on dogs by 2030. The ultimate goal is to create a world where animals are only used in research under exceptional circumstances.
Similar initiatives are being taken in other countries as well. The US FDA aims to make animal studies the exception rather than the norm in drug safety and toxicity testing within the next 3-5 years. The NIH is also working to reduce animal use in research it funds, while the European Commission plans to release a roadmap to end animal testing in chemical safety assessments this year.
Ethical concerns and advancements in alternative scientific methods are driving this shift away from animal testing. New Approach Methodologies (NAMs) such as organs-on-chips, organoids, and computational models are increasingly being used in research. These methods, which often use human cells and data, are proving to be more effective at mimicking human biology and predicting drug safety and efficacy.
While NAMs show promise, they are not yet capable of replacing all animal procedures in research. Some biological systems are too complex to study without animals, and many alternative methods still require validation to meet regulatory standards. Despite these challenges, efforts to replace, reduce, and refine animal use in research have been ongoing for decades, leading to a decline in the number of animals used in scientific procedures in countries like the UK and the EU.
One major reason for the shift towards alternative methods is the limitations of animal models in predicting human responses to drugs and diseases. For example, many promising therapies for conditions like sepsis have failed in clinical trials after showing efficacy in animal models. Researchers like Joseph Wu at Stanford University are exploring innovative approaches, such as growing organoids from induced pluripotent stem cells to create personalized models for testing potential drugs.
Studies have shown that some NAMs are as effective as, or even better than, animal tests. For instance, Emulate’s Liver-Chip system has demonstrated high accuracy in identifying compounds that cause liver damage, without false positives. These advancements in alternative methods are paving the way for a future where animal testing is no longer the default option in scientific research. In recent years, there has been a significant push to find alternatives to animal testing in drug development and toxicology. One promising development is the Liver-Chip, a specialized chip that can detect liver toxicity caused by drugs. The chips have shown promising results, detecting 12 out of 15 liver-harming drugs that were previously deemed safe for clinical trials using animal models.
The Liver-Chip was accepted into the FDA’s ISTAND pilot program in 2024, which supports the development of new tools for drug testing. If approved, pharmaceutical companies could use the chip to test for toxicity instead of relying on animal models, making the drug approval process more efficient.
Another alternative to animal testing is organoids, 3D living systems that mimic the features of real tissues or organs. Researchers have created a wide array of organoids that can model human diseases and test for toxicity. In a 2021 study, human liver organoids were used to develop a toxicity screening tool that accurately detected substances affecting bile transport and mitochondrial function.
Computational models are also gaining popularity as an alternative to animal testing. In 2021, a virtual test was developed to predict skin sensitization caused by chemicals, eliminating the need for animal tests. Regulatory agencies like the FDA and EMA are working on integrating AI tools into their safety assessment pipelines to further reduce reliance on animal testing.
The pharmaceutical industry is investing more in Non-Animal Models (NAMs) for drug testing. Roche, a multinational drug company, has launched the Institute of Human Biology to develop human model systems like organoids. While animal data is still required for most drug approvals, companies like Roche are using NAMs data for some submissions to regulatory authorities.
The UK and US governments have announced commitments to accelerate the development and adoption of NAMs. The UK government has defined three baskets of animal tests, with targets for their replacement with NAMs. The FDA has published a roadmap to reduce animal testing for monoclonal antibodies, citing the high cost and poor predictability of animal studies for these drugs.
Validation is a key challenge for the adoption of NAMs in drug testing. Researchers must demonstrate that their model systems are accurate and reproducible to validation bodies. Despite these challenges, the shift towards NAMs in drug development and toxicology is gaining momentum, offering a more ethical and efficient approach to testing new drugs. Regulatory agencies rely on models to make informed decisions about the safety and efficacy of new products. However, the process of validating these models can be costly and time-consuming. Natalie Burden, head of NAMs strategy at the National Centre for the Replacement, Refinement & Reduction of Animals in Research in London, notes that validation studies vary depending on the method used.
To address these challenges, the UK and US governments are focusing on accelerating the validation process to ensure that data from alternative methods are accepted by regulators. The UK plans to establish a Centre for the Validation of Alternative Methods to facilitate collaboration between labs, policymakers, and regulators. In a similar vein, the NIH has launched a Validation and Qualification Network and is investing $87 million in a center to develop standardized organoid models.
Kent Lloyd, director of the NAMs Testing Center at the University of California, Davis, emphasizes the importance of rigorous validation for NAMs. He warns that without stringent standards, there could be negative consequences. As the use of NAMs continues to grow, maintaining transparency and rigor is crucial to ensuring their effectiveness.
Researchers have welcomed efforts to accelerate the adoption of alternative models, as traditional animal experiments are still favored by peer reviewers and funders. Valerie Speirs, a cancer biologist at the University of Aberdeen, believes that the shift towards NAMs has been too slow. However, concerns remain about overstating the capabilities of these models and the potential for failures in clinical trials.
Despite advancements in alternative methods, some researchers argue that animal studies are still necessary for studying complex biological systems. Robin Lovell-Badge from the Francis Crick Institute highlights the challenges of recreating intricate organ systems in vitro. Similarly, Sarah Bailey, a neuropharmacologist at the University of Bath, points out the limitations of modeling human behavior and cognition in a lab setting.
In conclusion, while NAMs offer promising alternatives to traditional animal models, there are still areas where animal studies remain essential. It is crucial to strike a balance between advancing alternative methods and recognizing the unique capabilities of animal research. By continuing to improve validation processes and standards, regulatory agencies can make more informed decisions about the safety and efficacy of new products.
