Synthetic data enriches clinical datasets and simulates alternative scientific scenarios through computer-generated subject data, synthetic placebo groups, digital twins, and more. Combined with AI across target identification, trial design, and sample size modeling, a new toolkit is emerging that could shorten the time from idea to decision, and animal health may be better placed than human pharma to use it.

• AI-driven target identification, trial design, and exploration of inclusion criteria
• Synthetic placebo groups, digital twins, and enriching underpowered datasets
• Real-world evidence and PIMS data as a development input
• Addressing small, fragmented datasets in guiding product development decisions
• Replacing, reducing and refining animal use through computational approaches

Climate volatility, policy instability, and structural labor shortages are raising operational risk and reducing investment confidence across livestock production. This session explores how animal health innovation and agtech can serve as genuine strategic tools, building resilience and helping producers navigate a rapidly changing global market.

• How tight-margin decision-making shapes what producers actually adopt
• How animal health and agtech reduce operational risk and deliver visible financial return
• How coordinated supply chains and verified quality reduce systemic risk and unlock the global protein opportunity
• What collaboration, associations, and policy need to do to stabilize the commercial environment and make long-term investment rational

This session will share specific examples of how data is unlocking economic and medical advancement across the value chain and for the pet owners we serve.

• Product Launch: Derrick will share how they leveraged their data to undertake a product launch roll out with a partner. How expectations were aligned and how ROI was achieved for both practice and partner
• Clinical Outcomes: Jennifer will discuss how Arista are combining PIMS data with client and clinical team surveys to measure clinical outcomes.
• Operational Effectiveness: Paula will share how data is at the heart of their client communication and engagement strategy

In 2025, only four of the top ten animal health companies made acquisitions, the joint lowest on record. M&A spend fell from $8.8bn to $1.7bn. Deal volume dropped, but diligence quality 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 pulls back the curtain on what drives deal decisions, and what founders and development teams need to build in from day one.

• What a diligence-ready data package looks like
• What kills deals: the most common data gaps, red flags, and avoidable mistakes
• Licensing vs acquisition vs co-development: which structure fits which stage
• How acquirers are pricing development-stage assets as valuations shift from revenue to data
• What investors are underwriting and how to de-risk your development plan before the pitch

A decade of sustainability commitment has not built a functioning financial model. Costs sit at the farm level, consumer premium has not materialized, and verification is too expensive. Yet the context is shifting. Financial regulation, mandatory climate reporting, and financed are creating genuine new commercial urgency. Despite this, the model that makes sustainability economically rational and practically achievable for producers at farm level has not yet been built. This session explores what a commercial architecture that actually works looks like. It will explore:

• Why commitment has failed to build a functioning financial model, and what a viable producer value proposition actually looks like
• How the industry distributes cost and reward proportionately across the value chain
• How inset, offset, and credit markets need to be structured to protect rather than squeeze producers
• What verification infrastructure is needed to support credible claims and reduce cost burden at scale
• How the industry builds durable producer and public trust at a moment of growing institutional skepticism

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

This session examines where the inefficiencies are, what's actually changing, and what a best-in-class development program looks like today. The adoption gap is just as important: designing a trial without thinking about how the product will be used in practice builds in a commercialization problem from day one.

• Where the biggest time and cost sinks in trial design are structural versus fixable
• Real-world evidence and PIMS data as a supplement to traditional clinical trials
• What regulators, acquirers, and licensees actually need from your data package
• Designing for adoption: building clinical utility and practice-readiness from the start
• The CRO landscape: what's available, what's missing, and where the bottlenecks are

Category creation requires more than great science. Andria Beale shares how EpiPaws used pilot data, strategic partnerships, and industry visibility to build credibility and commercial traction across consumer, veterinary, nutrition, and diagnostics markets, and what it takes to scale beyond the vet channel through retail, corporate, and reseller partnerships.