In 2025, only four of the top ten animal health companies made acquisitions, the joint lowest on record. Total M&A spend fell from $8.8bn in 2024 to $1.7bn. But while the volume of deals dropped, the quality of diligence went up. Acquirers and licensees are more selective, more data-driven, and more focused on development-stage risk than at any point in the last decade.

This session will pull back the curtain on what actually drives deal decisions in animal health: what data matters, what kills deals, and what founders and development teams need to build into their programs from day one if they want to be acquirable, licensable, or fundable.

As antimicrobial use declines, genetic complexity rises, and labor and climate pressures mount, nutrition is shifting from a performance input to an integrated management tool across health, immunity, and resilience. The science is advancing. The barrier is proof.

ROI is difficult to demonstrate consistently across variable genetics, geographies, and production systems. The validation models needed to generate commercially credible, farm-level evidence have not been built. This session will explore where functional nutrition is creating the greatest combined value, why the commercial case remains so hard to make in real production settings, and what it takes to construct the validation frameworks that unlock adoption at scale.

While lifetime value isn’t a frequently used measure of the clinic/ owner relationship, we’ll discuss the key elements required to usefully drive a long-term relationship that drives better health and financial outcomes

• Mapping the customer journey from nose to tail
• Key blockers to client centricity
• Communication engagement strategy and trust building
• Predictable revenues
• Moving to metrics that matter. Getting ahead of the lagging measure of retention
• AI guiding CSR development and the use of sentiment analysis and agentic voice
• Improving adherence and decreasing variability of care

Synthetic data is already being used to train diagnostic imaging models for rare conditions, simulate clinical pathology results without live trials, and build digital twins of individual livestock. Combined with AI applications across target identification, trial design, and manufacturing optimization, a new toolkit is emerging that could reshape how animal health products are developed.

This session explores animal health's structural edge over human pharma: lower regulatory burdens, faster trial cycles, rich real-world practice data, and the opportunity for synthetic data to ease the limitations of small, fragmented datasets that have held back AI adoption.