New Approach Methodologies (NAMs): Connecting predictive models to regulatory workflows

Global and national regulatory frameworks are undergoing a decisive shift toward New Approach Methodologies (NAMs)—prioritizing in silico computational modeling and targeted in vitro assays to reduce, refine, and replace vertebrate animal testing across chemical industries.

However, adopting predictive models in highly regulated sectors requires more than academic accuracy metrics. Regulatory affairs and product safety leaders need reproducible, auditable evidence that translates seamlessly into technical dossiers.

Bridging Research Models and Operational Compliance

Across Iterchem’s core application domains, teams use computational prioritization to address sector-specific safety milestones:

• Pharmaceuticals & Biotechs: Early screening of lead series and candidate molecules to flag potential endocrine liabilities before preclinical investment.
• Agrochemicals & Crop Protection: Evaluating active ingredients and formulation alternatives to anticipate hormonal and environmental safety risks across MAPA, IBAMA, and ANVISA pathways.
• Cosmetics & Personal Care: Substantiating ingredient safety through cruelty-free, animal-free computational evidence aligned with international NAMs guidelines.
• Food Contact & Industrial Chemicals: Assessing migrants, non-intentionally added substances (NIAS), and functional ingredients with structured risk and exposure context.

“A predictive model only creates real enterprise value when its outputs are traceable, version-locked, and structured for the teams making regulatory and investment decisions.”

Built for Auditability from Day One

EndoXplain was architected specifically to close the gap between computational chemistry research and regulatory documentation. Every screening job records the exact model version, input standardization parameters, uncertainty bounds, and explainable rationale—exporting clean PDF technical reports ready for internal governance and regulatory review.