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When the US Food and Drug Administration announced it would begin phasing out animal studies in April, many in the scientific community were stunned.
For decades, animal testing has been considered a regulatory cornerstone, and an essential step before drugs reach human trials.
But at Certara — a company that has spent the past 20 years using biosimulation to accelerate drug discovery and development — the announcement was less of a surprise and more of a signal.
“We’d been preparing for this moment for a long time.”
Patrick Smith, Certara
“I couldn’t have imagined the FDA making this decision two years ago, but we’d been preparing for this moment for a long time,” said Patrick Smith, Certara’s senior vice president of translational science. “The science has gotten to the point where mathematical models can do a very good job of predicting clinical outcomes in the absence of clinical trials. That’s where AI and biosimulation start to change everything.”
Within days of the FDA’s announcement, Certara launched the Non-Animal Navigator (NAM) — an artificial intelligence platform designed to help pharmaceutical companies replace or reduce animal testing.
Certara also created a dedicated website for this service, positioning itself as the first major company offering a comprehensive platform to guide pharmaceutical developers through the post-animal testing era. And investors took notice: Certara’s stock jumped nearly 30% that week.
But the speed wasn’t a coincidence. It was the result of global teamwork and years of groundwork.
A two-decade head start on biosimulation
Certara’s Non-Animal Navigator didn’t appear overnight.
Long before AI took center stage, Certera was using computer models to simulate how drugs behave inside the body.
The company’s roots stretch back to the early 2000s, when it first started building software to model pharmacokinetics (PK) and pharmacodynamics (PD) — fields of study that respectively predict what happens to a drug once it enters the body, and the effects drugs have on the body.
Since then, the FDA and many other regulatory agencies have started officially recognizing modeling and simulation as legitimate scientific methods for drug evaluation. Guidance documents began encouraging model-based drug development, and the FDA ramped up its formal use of pharmacometrics analyses.
As computing power grew throughout the decade, PK/PD modeling rose alongside it. These models simulate how drugs are absorbed, distributed, metabolized and excreted. This approach helps researchers identify the “therapeutic window” — where a drug is effective without causing side effects.
“There’s a certain concentration in the blood above which you’ll get the effect that you’re looking for,” said Smith. “But, if you get too far above that level, then you start to get side effects. So our objective becomes determining the optimal dose across a large population of individuals that threads that needle.”
These advancements laid the foundation for Certara’s biosimulation technology.
By the mid-2010s, Certara had established partnerships with major biopharmaceutical companies, academic institutions and regulatory agencies worldwide. And the company’s extensive software suite became the industry standard for modeling and simulation.
The proof is in the pudding: From 2014–2024, Certara’s customers have received 90% or more of all novel drug approvals by the FDA.
Traditionally, building models has been a manual, painstaking process for engineers and statisticians. But Certara is changing that by developing machine learning systems capable of analyzing huge datasets, identifying patterns and generating predictive models in a more automated fashion.
Although predictive modeling has come a long way, Smith stressed that validation remains the main barrier to broader adoption of NAMs. To combat this, Certera’s team of regulatory consultants works closely with clients to ensure their approaches align with FDA expectations.
These developments, paired with the rise of AI, culminated in what would become the NAM.
The next generation of drug development tools
When the FDA announced its shift away from animal studies, Certara’s global teams — spread across the US and Europe — immediately mobilized.
Four key teams joined forces: software engineering, regulatory and drug development science, toxicology and modeling and simulation.
“It was one of those moments where everyone dropped what they were doing,” Smith said. “By Monday morning, we wanted to make sure Certara was leading the conversation.”
The announcement centered on monoclonal antibodies — a class of therapeutics with highly specific biological targets and limited unintended effects. Since these drugs are often not relevant to animal biology and tend to be safer and more predictable in humans, the FDA said it would eliminate or reduce nonhuman primate studies for monoclonal antibodies and launch a pilot program to determine how to further minimize animal use.
While the move was framed as a step toward modernizing drug safety testing, the FDA’s statement didn’t end animal testing overnight. Instead, it opened the door for companies like Certara to lead the next generation of drug development tools.
Certara’s Non-Animal Navigator combines in vitro methods, organ-on-a-chip assays, biosimulation and regulatory strategy into one streamlined solution. It essentially provides a step-by-step framework for identifying when and how non-animal methods can replace animal studies while ensuring alignment with FDA expectations.
The first component of a typical engagement with a company using the NAM involves setting a strategy for which animal studies are needed and assessing the requirements for a clinical trial.
Certara also runs this established pathway by the FDA to ensure there are no hiccups.
FDA as ‘partner and the umpire’ for AI-assisted pathways
The execution of this plan may involve experiments with NAMs and animal studies.
Certara applies its modeling across the board to either the animals or NAMs and compiles all the findings. It uses that data to file an IND with the FDA, which is a submission to request permission to test an investigational drug in humans. Once it’s approved, the respective client can move forward with clinical studies.
Smith described the FDA as a “scientific partner” in the drug development process due to its stake in advancing these studies, but he stressed that it’s a complex relationship.
“The FDA is both a partner and the umpire,” Smith said. “They have the final say… Everyone’s learning together.”
Another key element in this shift will be the role AI plays in helping Certara remain a mainstay in this space.
Artificial intelligence has become the backbone of Certara’s biosimulation technology. Traditionally, creating predictive models was a manual, time-intensive process. Software engineers and statisticians had to build each model from scratch.
Now, Certara’s AI systems can automate model generation and sift through vast databases of toxicology and clinical studies to help researchers unearth patterns linking animal data, in vitro results and human outcomes.
“If we have a huge database of toxicology studies, AI helps us connect what was seen in animals with what actually occurred in humans,” Smith said. “That’s incredibly powerful for improving predictions and for knowing when animal tests aren’t adding much value.”
AI is also helping Certara’s tools read and interpret scientific reports. Kevin Snyder, Certara’s director of nonclinical innovation and emerging technologies, and his team are experimenting with large language models that can ingest raw data and study reports, extract key findings and automatically annotate datasets.
“It’s about making our systems not just faster, but smarter,” he said.
A call to innovators: Join a team of 1,600 across 70 countries
For Certara, the goal isn’t just to align with the FDA’s vision — it’s to spearhead industry-wide advancements.
“Animal studies aren’t as predictive as we’d like,” Smith said. “Ninety percent of all drugs that go into humans fail, and every one of them showed safety and efficacy in animals. That tells you something.”
The inefficiency is not just staggering in a scientific sense, but financially as well. A single primate for a toxicology study can cost well over $30,000, and most studies require dozens of animals. Certara’s NAM technology has already shortened or replaced some of these studies, saving clients millions.
“We have numerous examples where we didn’t eliminate animal studies entirely, but made them shorter and reduced the number of animals required,” Smith said. “That still translates into a significant benefit.”
Today, Certara employs more than 1,600 people across 70 countries, serving over 2,400 clients, from biotech startups to major pharmaceutical firms and global regulators.
The company’s success with launching the NAM underscores its broader mission of accelerating medicines through technology and improving patient outcomes worldwide.
In an industry defined by caution, the NAM represents both a technological leap and a moral one — a sign that the future of drug development may depend less on the animals tested, and more on the algorithms taught.
And as the field evolves, Certara is inviting more technologists and scientists to join its mission.
“We want to attract people who are passionate about solving problems at the intersection of biology, technology and AI,” Smith said. “This is one of those rare moments when science and software can reshape how we discover and develop medicine.”
