April 27-29, 2026

All Speakers

Dog and cat food research experts who will present at Petfood Forum & Petfood Essentials

Ana Rita Monforte
S&T Global Flavor & Data Sciences Manager
AFB International
Ana Rita Monforte, Ph.D., leads research and development initiatives at AFB, connecting flavor generation with data-driven modeling to improve speed and reliability of palatant development. She holds a Ph.D. in chemistry and has directed scientific strategy for Maillard-based and hydrolysis-derived palatants. In parallel, Monforte has established internal AI-assisted frameworks that combine palatability outcomes, formulation metadata, analytical descriptors and trial context into predictive models that help rank candidates before live testing. She also drives internal capability building in statistics and machine learning for non-data scientists, advancing the shift from intuition-driven exploration to evidence-assisted design.
Date/TimeTitle
Tue Apr 28
3:10 PM - 4:15 PM
Pet food regulatory, safety and technology: 3:10-4:15 p.m.
KCCC Room 2504
  • Auditing the future: Digitalization and data analytics in pet food quality assurance

Jennifer Lott, technical development director, SGS North America, explores how digitalization is transforming food safety auditing in pet food manufacturing and supply chains from reactive to proactive through digital platforms that enable real-time document exchange, remote verification and data analytics supporting continuous assurance and early risk detection. Drawing on field data from more than 300 remote and hybrid audits conducted between 2021 and 2024, her study evaluates measurable impact of digital tools on audit efficiency, accuracy and risk visibility, showing an average 25% reduction in total audit cycle time, improved traceability of corrective actions and enhanced consistency of findings.

  • AI-powered analytics for pet food: Price elasticity, forecasting and decision-making in Latin America

Iván Franco, founder and independent advisor, Triplethree International, introduces an applied framework using advanced analytics and AI to optimize pricing and forecast demand in the pet food market. Leveraging models of price elasticity, distributed lag effects and demand forecasting, he demonstrates how data transforms into actionable strategies for portfolio management and channel execution. Case studies from Latin America illustrate how predictive analytics uncovers hidden inefficiencies and improves profitability while reshaping competitive dynamics in pet food and offering a scalable blueprint for data-powered growth.

  • Leveraging AI to predict pet food palatability: Integrating recipe, analytical and pet data

Ana Rita Monforte, Ph.D., global flavor and data sciences manager, AFB International, evaluates the use of AI to anticipate palatability outcomes of palatant systems prior to in vivo (animal) exposure, enabling earlier failure identification and reduced trial burden. Palatability remains one of the strongest commercial differentiators in pet food, yet its prediction still relies predominantly on empirical, animal-based testing. Beyond trial reduction, this AI framework informs ingredient selection during formulation, constrains design of experiments search space and supports design of next-generation palatants tuned for specific recipe architectures and processing conditions. By converting historically siloed data into decision-quality signals, AI enables a shift from intuition-led iteration to evidence-assisted design.