Live Insights: 45% Believe The NAMs Industry Should Expand Pre-Competitive Data Sharing Programs

By Ray Dogum, Chief Editor, Drug Discovery Online

The global conversation around new approach methodologies (NAMs) has shifted from if to how fast. With regulatory agencies in the U.S. and Europe accelerating their timelines to reduce reliance on animal testing, the pressure is now on industry to match that pace with credible, scalable, and standardized solutions.

But momentum alone isn’t enough. As Zaher Nahle, Ph.D. pointed out in our recent DDO Live session titled “The NAMs Revolution: Smarter, Safer, More Ethical Drug Testing”, “the [NAMs] fanfare happened in the United States recently,” but the European Union began laying the groundwork years ago, calling for not just technological innovation, but legislative and educational frameworks to support it.

The question now is can the field build the trusted infrastructure needed to make NAMs the default tools for drug discovery. That means data sharing, human-relevant benchmarking, and pre-competitive collaboration must become standard practice, not side projects.

Regulatory Shifts: EU Talk, US Action?

Global regulatory agencies are moving, but not always in sync. Zaher highlighted the early leadership lessons from Europe:

“You see, the EU has started talking about this before the US. Yes, there are some recent changes since April of 2025 (a reference to the FDA’s announcement to phase out animal testing). But let's not forget that the first European Union decision, which is a major decision in 2021, was a resolution that was adopted with majority support to establish frameworks or ask participating countries or member states to start developing frameworks for NAMs, not only in technology, but in education and integration and legislative changes, in policy updates and legal frameworks.”

He added, “I read an editorial the other day saying that ‘EU talks and the United States takes action.’ So, it's a funny title prodding the EU, but … yes, the United States has been faster at adopting [NAMs] starting in April.”

Zaher also pointed to political dynamics as a key factor:

“The change in government and administration in the United States has played a big role in that as well. Let's not forget that during the Biden administration, the changes that happened at the EPA to develop a particular timeline for phasing out animal testing were tabled. Now this is reinstated. So again, new blood coming into the system of governance and a new outlook from the administration has helped accelerate the process in the United States.”

Data Sharing: The Confidence Catalyst

Samantha Atkins, Ph.D. emphasized that the biggest hurdle to widespread adoption of NAMs is not just technical, it’s cultural:

“There is an initiative ongoing between the NIH and NCATS and the FDA where they do want to make an MPS data portal where everything will be standardized and shared. So I think the hurdle there, and one of the big hurdles to the field in building confidence, is not having this shareable data platform where you can go in and look at results across the board.”

She continued:

“A lot of companies are very protective of their IP, and they're very sensitive to their toxicology data because if something fails and doesn't move to the clinic, a lot of the times they don't talk about it. So I think this open sharing mindset is a paradigm that needs to be shifted in the field as well—where if you fail fast and fail forward using a NAM and you can publish that data so other companies, even your competitors, can see this and look at the data and take precedence from it.”

Samantha also pointed to collaborative models that are already working:

“There are consortiums like the IQ MPS, where there's maybe close to 30 pharma companies that all come together and their IP is protected to share openly about their strategies with NAMs—how they're employing them in either efficacy or safety, what hurdles they're currently facing—and write white papers and publish those. So you can get some hints about the pulse of the industry and what people are feeling internally, either internal pressure to get the fast NAMs data or external pressure to stop testing on animals.”

I added, “data sharing is something that the industry is starting to appreciate more and more, especially as AI models become more important in their work as well. You're going to want more and more accurate, better data to produce those results.”

Benchmarking Against Human Data

Zaher stressed that the real benchmark for NAMs should be human clinical data, not legacy animal models:

“Very important for benchmarking, because we have a long history of data in humans, right? Fifty-year history of clinical trials. Some failed, some didn't fail, but the negative results must be out there so that they can benefit from benchmarking new drugs using NAMs against the human data, not against animal data. And they exist. There are plenty of these. There are thousands and thousands of trials that accumulated over the years, over the decades. Those would be vital for benchmarking NAMs against the real gold standard, which is human data.”

Poll: How Should the Industry Respond?

We closed the session with a poll: How should industry respond to regulatory shutdowns to maintain NAM momentum? (N=31)

The results:

• 14%: Invest in self-validation by generating robust data for internal decision-making
• 17%: Strengthen global partnerships by leveraging EU/OECD frameworks for continuity
• 24%: Diversify funding sources by reducing reliance on federal programs
• 45%: Expand pre-competitive consortia by sharing validation data and best practices to reduce duplication and accelerate acceptance

The majority favored expanding pre-competitive consortia, reinforcing the idea that shared knowledge builds collective confidence. Although I agree that sharing data is usually a win for broader science and patients, the line separating pre-competitive and competitive research is blurry. Stay tuned for a future editorial on establishing pre-competitive ground rules in drug discovery.

Moving Forward

To accelerate the adoption of new approach methodologies, the field must:

• Benchmark NAMs against human clinical data, not animal models
• Push for government-led coordination and investment
• Shift cultural norms around sharing failure data
• Build FAIR-compliant, intelligible data platforms
• Embrace pre-competitive collaboration and data transparency, when and where possible

The tools are here. The regulatory winds are shifting. The question now is whether we can align our strategies—and our data—to meet the moment.

You can access the full Live replay including audience Q&A and highlights,