Lexie Shadix, Campus Carrier deputy news editor
On April 10 the U.S. Food and Drug Administration (FDA) announced they are replacing animal testing in the development of monoclonal antibody therapies and other drugs with more effective, human-relevant methods. Monoclonal antibodies (mAbs) are laboratory-produced proteins that can be used to treat various conditions such as cancer, autoimmune diseases and infections. This 2025 decision builds on the FDA Modernization Act 2.0, which was signed in 2022 and allowed for the use of specific alternatives to animal testing.
Prior to 2022, the FDA required all drugs to go through animal safety testing. Before a drug can be tested in humans, drug creators must show a drug may be able to do what they claim it will, and this is done with animals.
Early in the drug creation process, in vitro assays are used. These are experiments that test the effectiveness of medicines and are conducted outside of a living organism. They typically use isolated cells, tissues or biochemical components and can be completed in a short amount of time These assays allow scientists to test potential drugs, study biological processes, and understand mechanisms of action the drug may have.
“Promising drugs are often then tested in an animal model which provides more in-depth information about the drug’s potential for success in humans,” Professor of Chemistry and Biochemistry Mark Turlington said.
When drugs are developed enough in the discovery process, researchers are given an idea of what results to look for in animal models that would mean the drug working as expected in humans.
“Animal models that are well developed are always more informative than just a cell-based model or [computer] simulation,” Turlington said. “Before you put a drug molecule in a living organism, you really don’t know how it’s going to respond, because living organisms are so complex. Lots of drug molecules work well in cells that don’t work in a living organism.”
Animal testing has been a common practice with roots tracing all the way back to ancient Greece.
“Simply, there was nothing else,” Dr. Thomas Hartung, a professor of toxicology, molecular microbiology, pharmacology and immunology at Johns Hopkins Bloomberg, Georgetown University and the University of Konsantz, said. “The problem is, ethically, you cannot test on humans.”
It was not until the 1970s and 1980s that computational methods, those used in drug testing to predict properties, screen potential targets and optimize drug candidates, became viable alternatives.
Currently, there are many drugs that simply cannot be tested on animals and provide useful results for how they will behave in humans.
“You have to understand that more than half of the new drugs are actually antibodies or human proteins, things which are uniquely human,” Hartung said. “We call them biologicals today. These drugs can simply not be tested in animals because [animals] don’t have these structures, and they produce antibodies against our drugs [and] these antibodies.”
After a few injections of these types of drugs, animals go into anaphylactic shock and the trial is forced to end.
“Sometimes you don’t have an animal model that translates to humans,” Turlington said. “There is a lot of precedent for using animals both for determining if a drug works, and especially for safety, but I think in this particular context it is just not as relevant because of the differences in human and animal immune system responses.”
Previously, all mAbs were required to undergo toxicity studies in animals. However, animal immunogenicity is not able to predict human immunogenicity due to the fact their immune systems have differences. Furthermore, stress that animals face in a lab can impact their immune function and inflammatory responses, among other things, which also yields poor results. Safety risks may also go undetected in animals, which is what happened with the mAb TGN1412, which caused life-threatening cytokine release syndrome in humans but not in monkeys.
Currently, one of the more reliable alternative methods to animal testing is microphysiological systems (MPS). These are “in vitro” models that recreate aspects of human physiology and organ function by using microfluids, cell cultures and 3D tissue engineering.
“What we have been developing over the last twenty years, mainly based on stem cell technology, is [the ability to] reproduce aspects of the architecture and function of an organ, which means a lot of different cells collaborating and doing what an organ should do,” Hartung said. “The lung should breathe, a kidney should carry out some dialysis of fluids and the brain should fire electrical signals. We really need established functions, and this is what is happening at the moment with these complex in vitro systems.”
Artificial intelligence (AI) has also been an up-and-coming alternative to animal testing.
“The progress of AI is really astonishing,” Hartung said. “Since the introduction of deep learning in 2010, AI is doubling its capacity every three months, so this year’s AI is eight times more powerful than last year’s.”
It is only since 2019 that AI has been a viable tool for designing drugs.
“In 2023, we already saw that 18 so-called AI-first drugs, things which were designed by AI, went into human trials,” Hartung said. “That’s a dream time; four years from the design of a drug to preclinical testing to humans.”Last year, the first of the drugs successfully completed Phase 2A, the phase in which testing is done on a limited number of humans, and moved into Phase 2B, which is an extended clinical trial with patients.
It typically takes drugs 10 to 15 years to move from discovery to testing in humans. Furthermore, it is estimated that the cost of developing a successful drug is, at a minimum, $2.4 billion. Companies must produce enough revenue from their drug to recoup and exceed this amount, causing prices of medicines to be high. Alternatives to animal testing could serve to shorten the amount of time a drug takes to get approved and reduce its cost once it is on the market. However, animal testing is unlikely to disappear soon.
“There’s a lot of knowledge that [scientists] can take from what they learn when giving a drug to an animal, and that information can then be extrapolated to a human in a way that is relevant for drug safety in humans,” Turlington said. “I don’t feel like it’s going to go away entirely unless there’s new technologies developed, and I think that’s kind of what this FDA policy is getting at. Monoclonal antibody therapy is one area that animal and human safety data don’t correlate well, and maybe that will be an opportunity to develop new technologies that will one day eliminate the need for animal safety testing.”
However, the FDA seems to be taking action to make alternative methods commonplace.
“This is very unusual in science, that we essentially do the same stuff for such long periods of time, and we’re not advancing to new methodologies as they become available,” Hartung said. “Science is doubling its knowledge at the moment every three years, so you can imagine how much more knowledge we have. We are looking typically where we have a tool that we can measure, and that’s a very dangerous comfort zone because we don’t solve the problem.”