Frequently asked questions

Health Technology Assessment (HTA) is the evidence-based process that national payers use to decide if new medicines, devices, or diagnostics deliver enough clinical and economic value to justify coverage. Clear HTA evidence speeds reimbursement, reduces launch risk, and shortens patient wait times. Loon's AI tools automate the research steps that feed HTA dossiers, so life-science teams move from manual reviews to decision-ready evidence in days.

Health Economics and Outcomes Research (HEOR) evaluates the clinical, economic, and humanistic outcomes of healthcare interventions. It's crucial for demonstrating value to payers, securing reimbursement, and ensuring timely patient access to innovative treatments and therapeutics.

Loon's proprietary Neurosymbolic Ensemble AI Systems orchestrate hundreds of specialized agents that screen literature, extract data, and run economic models with high reproducibility. This end-to-end automation cuts human workload by up to 90 percent, raises sensitivity to 99 percent, and frees HEOR teams to focus on strategy and interpretation rather than repetitive data tasks.

Each Loon module is validated against human gold standards and peer-reviewed benchmarks. The platform logs every action, keeps an auditable trail, and meets Good Machine Learning Practice (GMLP) guidance. These controls allow submissions to regulators, health ministries, and payers with full confidence in method transparency.

Loon supports all major therapeutic areas including oncology, rare diseases, immunology, neurology, metabolic, and cardiovascular. Our AI models are designed to operate with comprehensive medical literature spanning all clinical domains.

Yes, all Loon outputs are designed to meet FDA, EMA, NICE, and other regulatory standards. Our systematic reviews follow PRISMA guidelines, and our economic models comply with ISPOR best practices.

All Loon AI systems undergo rigorous scientific validation with preprints, conference papers, and peer-reviewed publications in journals like Value in Health. Our models are calibrated against expert systematic reviewers and validated across multiple therapeutic areas.

Global pharmaceutical companies, national health systems, contract research organizations, and top academic institutions across North America, Europe, and Asia rely on Loon to accelerate evidence generation and reduce reimbursement uncertainty.

Loon Lens™ achieves 99.0% sensitivity, 99.0% accuracy, 99.1% specificity, and 89.9% precision in systematic literature review screening, with calibrated confidence scoring routing ~5% of lower-confidence outputs to human review. This regulatory-grade performance and calibration is extensively validated through scientific publications and real-world comparative studies.

Loon Lens™ automates the entire Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) workflow: search string generation, deduplication, screening, data extraction, and report assembly. Reviews that once took eight to 24 months can now be completed and fully quality-checked by HEOR experts in under two weeks.

Yes. Loon Waters™ combines historical HTA decisions, pricing policies, and market analogs to forecast and optimize probability of approval, likely conditions/restrictions, and timeline for each target market. Early adopter biopharma clients report up to 50 percent improvement in launch-window planning accuracy.

Our Loon Waters™ platform simulates 1000s of payer scenarios with high accuracy, helping reduce the 25-50% HTA rejection rates. We model real payer decision-making processes and HTA requirements across multiple jurisdictions.

Yes, our AI systems can rapidly assess indirect treatment comparison feasibility by analyzing available evidence, identifying data gaps, and recommending optimal comparison strategies. We provide comprehensive feasibility reports within days, not months.

The platform draws from peer-reviewed biomedical journals, clinical-trial registries, HTA body archives, and real-world evidence repositories. Data are refreshed continuously, and each agent uses task-specific models fine-tuned on domain-curated corpora to maintain high relevance and low hallucination risk.

Loon currently supports export in the RIS file format—the standard used by EndNote, Zotero, Mendeley, and many other reference managers. After screening or data extraction is complete, you can download a RIS file with one click and import it directly into your preferred tool. Additional formats are on our roadmap, but today RIS ensures quick hand-off to most literature-management workflows.

Multiple validation studies have been presented at ISPOR and published in open-access journals. These papers detail methodology, performance metrics, and comparisons with manual methods. Links and citations are provided on our Validation and Publications page.

Click "Request a demo" anywhere on this site to schedule a call with our HEOR team. We can also arrange custom pilot projects using your own research question and data to demonstrate real-world value before you commit to a full subscription.

Most clients are up and running within 2-4 weeks. This includes team training, protocol setup, and integration with your existing research databases and workflows. Our Customer Success team provides white-glove onboarding support.

We provide comprehensive training including live webinars, step-by-step tutorials, and dedicated Customer Success managers. Our team includes PhD-level HEOR experts who understand the nuances of evidence synthesis and can provide methodology guidance.

We offer flexible subscription models based on team size and usage volume. Pricing includes unlimited technical support, regular platform updates, and access to our full product suite. Contact us for a custom quote based on your specific needs.

Traditional HTA submissions can take 8-24 months to prepare. With Loon's AI-powered SLR tools, reimbursement forecasting, and value dossier optimization and simulation, we can reduce this timeline to 2-6 months while improving submission quality and success rates to de-risk commercialization.

Organizations typically see 60-80% reduction in evidence synthesis time, 40-60% faster HTA preparation, and significantly improved submission success rates. ROI is often realized within the first major project.

We implement enterprise-grade security with SOC 2 compliance, end-to-end encryption, and strict data governance protocols. Your proprietary data never leaves our secure environment and is never used to train our models without your permission. We have strict zero-day data retention policy agreements with all foundational model providers.

Loon Lens™ achieves 99.0% sensitivity, 99.0% accuracy, 99.1% specificity, and 89.9% precision at Level One screening with confidence-guided review of ~5% of outputs, outperforming both human reviewers and other tools on a 3,796-article benchmark. Full peer-reviewed studies, ISPOR papers, and preprints—detailing datasets, methods, and comparative metrics—are available in the Validation section of our website.