The future of biomedical research is animal-free
As a scientist focused on tangible data and results, it’s easy to be sceptical about the impact of legislative acts: the path from Congress to the lab is long and winding. Despite the subtle change and lack of immediate impact on patients, the FDA Modernization Act 2.0 is anything but inconsequential. I think, in truth, that it may be the spark needed to ignite the next era of animal-free drug discovery.
Animal testing has been required by the US Food and Drug Administration (FDA) since 1938, before any new drug can proceed through clinical trials and receive approval for human use. This 84-year-old requirement is one reason why biotechs have had little incentive to develop alternatives to animal models, despite the fact that the industry has desperately needed more biologically relevant alternatives for years.
Making animal models obsolete
Passed by the Senate last September, the FDA Modernization Act 2.0 (S.5002) opens new doors to biomedical advances that can make animal models obsolete. The amendment swaps out mentions of animal tests with “nonclinical tests,” described as “animal tests, or non-animal or human biology-based test methods, such as cell-based assays, microphysiological systems, or bioprinted or computer models.”
I can see why using animal models in research to test a new drug’s toxic effects made sense nearly 100 years ago. But, perhaps not surprisingly, and given what we now know about the differences between animal and human physiology, this approach has many limitations.
Depending on which source you read, 92-96% of drugs that “pass” animal tests fail in clinical trials. We’ve become increasingly good at curing cancer and other diseases in mice, but not at benefitting human patients – patients like my dad, who was diagnosed with and later passed away from the untreatable disease frontotemporal dementia, and hundreds of thousands more like him with untreatable diseases.
The poor translatability of animal models
It is estimated to cost up to USD $2.8 billion to bring a new drug to market. Though preclinical studies represent nowhere near the majority of these costs, poor translatability of animal models to humans can impede drug development much further down the line – leading researchers to pursue ineffective drug targets for years based on early results in animal models.
Increasing the likelihood that a drug will succeed in clinical trials and proceed to market is expected to significantly reduce the total costs associated with modern drug development. Replacing animal models with alternatives to more accurately identify effective treatments without severe side effects for human diseases is a huge opportunity. Organs-on-a-chip and computational modelling have been introduced as promising alternatives. Both have potential to reduce the cost of drug development and speed the delivery of new drugs to market – not to mention improve the lives of both animals and humans.
A monumental path forward
However, the development of these alternatives has been handicapped by the strict requirement to use animal models. Why invest in unique alternatives if, at the end of the day, there is no opportunity for a path forward without animal models? The FDA Modernization Act 2.0 provides a path forward. While incremental, it is monumental.
Practically, it will take time for animal models to be fully optional. The act begins to align incentives for companies that previously viewed investing in the development of animal model alternatives as investing in low-value supplemental technology. Furthermore, it expands opportunities for new companies to form that focus on the development of these alternatives in their own right, including cell-based assays, organs-on-a-chip, and computational modelling.
The drug discovery industry now has a legislative stamp of approval to justify investing the dollars and hours necessary to optimise animal model alternatives. But animal models will remain the status quo until alternatives truly outperform them. Eventually, the number of animal models has the potential to dwindle down to zero. The groundwork has been laid, but there is still a lot of research and optimisation that lay ahead.
The benefits of computational models
Given where the industry is now, I believe the approach to eliminate animal models in drug development will change over time: initially animal models will be complemented by other models, such as organs-on-a-chip and computational models. As these alternative approaches become more scalable, and enough data and clinically relevant results are available to validate their use, the shift away from animal models will occur.
Animals have more built-in restrictions, such as needing food and healthcare. Practical limitations, like the time required to grow the animals to the necessary developmental stage, also impact experiments with animals. Computational models – once they work – are free from these constraints. As such, the speed at which these alternatives can potentially allow us to iterate can facilitate unprecedented rates of drug development at a far lower cost. Drugs for untreatable diseases could finally become profitable, and thus many more companies would approach disease areas that typically have low return on investment on drug discovery efforts. We could see a shift from curing laboratory animals to actually saving human lives.
Major pharmaceutical companies are in a unique position to drive this transformation. To establish the biological relevance – and strength – of animal model alternatives, it's imperative that we continue to test these models in tandem with traditional methods. While many innovative start-ups are developing technologies that can support drug development from discovery to manufacturing, they infrequently (read: nearly never) have the resources to test animal model alternatives in real-time against animal models themselves. Pharmaceutical companies possess the infrastructure and resources, and can work side by side with nimble start-ups that move fast to enact meaningful change.
The FDA Modernization Act 2.0 aligns incentives between large pharmaceutical companies and small start-ups. With a call to invest in and explore these technologies sooner rather than later, pharmaceutical decision makers can make this transformation happen. In this case, a legislative act can motivate a giant leap forward in scientific discovery and treatments for patients without options. The pace at which we realise this future ultimately depends on how clever and invested we are in ushering in this new paradigm.
