AI-ENABLED RAPID GENERATION OF MULTI-COUNTRY PAYER AND REIMBURSEMENT LANDSCAPES FOR COLORECTAL CANCER
Author(s)
Sumeyye Samur, PhD1, Turgay Ayer, PhD1, Ismail F. Yildirim, MSc1, Mine Tekman, PhD1, Jag Chhatwal, PhD2;
1Value Analytics Labs, Boston, MA, USA, 2Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
1Value Analytics Labs, Boston, MA, USA, 2Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
OBJECTIVES: Developing a comprehensive payer landscape across multiple jurisdictions requires timely, country-specific insights into payer systems, reimbursement pathways, and HTA criteria. We aimed to evaluate an agentic AI system for rapid generation of payer and reimbursement landscape across major markets, using colorectal cancer as a representative case.
METHODS: An agentic AI platform, ValueGen.AI, was developed as a multi-agent deep research system to synthesize payer, reimbursement, and HTA information across the United States and five European markets (United Kingdom, Italy, Germany, France, and Spain). The tool integrated structured prompts, curated policy frameworks, and domain-specific ontologies encompassing payer structures, screening and diagnostic coverage, reimbursement routes, HTA decision criteria, and managed entry agreements (MEAs). Built in Python using LangGraph, ValueGen.AI used a central agent to decompose queries and coordinate specialized sub-agents that extracted evidence from multiple sources via Model Context Protocol tools, enabling parallel collection and relevance evaluation.
RESULTS: ValueGen.AI generated standardized payer landscapes structured into four comparable country modules: 1) payer structure and screening policy, 2) reimbursement routes, 3) HTA decision criteria, and 4) emerging trends and real-world evidence (RWE). The platform identified key access levers across markets—such as U.S. Medicare national coverage determinations and compendia-supported off-label use; NICE appraisals with a statutory 90-day funding mandate and Cancer Drugs Fund managed access in England; Italy’s AIFA pricing and reimbursement supported by mandatory registries and MEAs; Germany’s AMNOG added-benefit assessments shaping price positioning and access; France’s HAS/CEPS process with hospital “liste-en-sus” financing and early access routes; and Spain’s IPT/CIPM positioning with Autonomous Community implementation heterogeneity—and highlighted the consistent role of biomarker-based eligibility in shaping reimbursement.
CONCLUSIONS: ValueGen.AI enables rapid generation of structured, multi-country payer and reimbursement landscapes with granularity typically requiring extensive manual research. Our approach is indication-agnostic and can substantially support early market access strategy development.
METHODS: An agentic AI platform, ValueGen.AI, was developed as a multi-agent deep research system to synthesize payer, reimbursement, and HTA information across the United States and five European markets (United Kingdom, Italy, Germany, France, and Spain). The tool integrated structured prompts, curated policy frameworks, and domain-specific ontologies encompassing payer structures, screening and diagnostic coverage, reimbursement routes, HTA decision criteria, and managed entry agreements (MEAs). Built in Python using LangGraph, ValueGen.AI used a central agent to decompose queries and coordinate specialized sub-agents that extracted evidence from multiple sources via Model Context Protocol tools, enabling parallel collection and relevance evaluation.
RESULTS: ValueGen.AI generated standardized payer landscapes structured into four comparable country modules: 1) payer structure and screening policy, 2) reimbursement routes, 3) HTA decision criteria, and 4) emerging trends and real-world evidence (RWE). The platform identified key access levers across markets—such as U.S. Medicare national coverage determinations and compendia-supported off-label use; NICE appraisals with a statutory 90-day funding mandate and Cancer Drugs Fund managed access in England; Italy’s AIFA pricing and reimbursement supported by mandatory registries and MEAs; Germany’s AMNOG added-benefit assessments shaping price positioning and access; France’s HAS/CEPS process with hospital “liste-en-sus” financing and early access routes; and Spain’s IPT/CIPM positioning with Autonomous Community implementation heterogeneity—and highlighted the consistent role of biomarker-based eligibility in shaping reimbursement.
CONCLUSIONS: ValueGen.AI enables rapid generation of structured, multi-country payer and reimbursement landscapes with granularity typically requiring extensive manual research. Our approach is indication-agnostic and can substantially support early market access strategy development.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
HPR142
Topic
Health Policy & Regulatory
Topic Subcategory
Coverage with Evidence Development & Adaptive Pathways, Reimbursement & Access Policy
Disease
SDC: Oncology