AI-powered workflows for evidence generation, economic modeling, literature intelligence, and outcomes analysis — accelerating insights while preserving methodological rigor.
ValueGen.AI builds and adapts health-economic models across cost-effectiveness, budget impact, and scenario analysis — with country-specific threshold logic embedded.
Builds Markov models, partition survival models, and decision trees for incremental cost per QALY/LYG. Supports probabilistic sensitivity analysis (PSA), one-way tornado diagrams, and country-specific threshold analyses.
Estimates net budget impact for payers adopting a new therapy — accounting for market uptake, patient share, cost offsets, and real-world adherence patterns.
Ensure existing models are technically sound, transparent, and fit for purpose through verification and validation aligned with ISPOR-SMDM guidance.
ValueGen.AI's modeling engine is purpose-built to mirror the structure of submission-grade economic evaluations across jurisdictions.
An agentic framework that conducts multi-source retrieval across published literature, HTA databases, and regulatory documents — with citations and confidence scores.
Generates comprehensive disease-area landscape reports in 48 hours — synthesizing HTA reports, guidelines, and published literature across 7+ markets in original language, summarized in English.
Algorithmically pinpoints gaps in the evidence base that may affect market access. Ranks gaps by strategic priority to guide clinical study design and real-world evidence collection.
Analyzes payer database data, RWE studies, and observational research to build supplementary evidence packages. Supports comparative effectiveness and adherence analyses.
Tailored analytical outputs aligned with the evidentiary expectations of each HTA body and regulator.
QALY thresholds, SMC adaptations, and reference case framing.
Subgroup analyses and IQWiG methodology alignment.
Evidence requirements and medico-economic dossier support.
Value-based price benchmarks and scoping analysis.
CDR submission requirements and reimbursement context.
Regional reimbursement and price negotiation insight.
Synthesized HTA comparison reports across markets — surfacing differences in comparator choice, modeling assumptions, and decision outcomes.
Drafts clinical sections of regulatory dossiers, value-of-information analyses, and evidence summaries for advisory committee meetings.
Identifies the top clinical, humanistic, and economic value drivers for a therapy — mapped to HTA body priorities and payer decision criteria.
Designed in line with the ISPOR Working Group Report on Generative AI for Health Technology Assessment (Chhatwal et al., 2025), including standards for transparency, traceability, and human oversight (Fleurence et al., 2025).
From early economic scoping to submission-ready dossiers — ValueGen.AI compresses timelines without compromising methodological rigor.
Request a Demo