Frequently Asked Questions

Epi Fractals provides Real-World Evidence, Health Economics and Outcomes Research, AI-assisted evidence generation, systematic reviews, network meta-analysis, HTA support, economic modelling, pharmacovigilance, policy analysis, and training services for life sciences and healthcare organizations.

Epi Fractals works with pharmaceutical and biotech companies, medical device and diagnostics companies, hospitals and health systems, payers and HTA bodies, CROs, academic and research institutions, government and regulatory organizations, digital health companies, NGOs, AYUSH organizations, and nutraceutical companies.

Real-World Evidence is clinical evidence generated from the analysis of Real-World Data. It helps organizations understand how a medical product, intervention, or health technology performs outside controlled trial settings.

Real-World Data refers to routinely collected health information such as electronic health records, claims data, registries, wearable data, and digital health data. Real-World Evidence is the insight generated after analyzing that data to answer clinical, regulatory, payer, or policy questions.

Real-World Evidence can support disease burden assessment, patient population analysis, protocol optimization, site and country selection, external or hybrid control arms, long-term safety evaluation, treatment pattern analysis, and post-launch evidence generation.

Yes. Epi Fractals can support the use of high-quality Real-World Data to build external or hybrid control arms, especially where conventional randomized control groups are difficult, limited, or impractical.

Health Economics and Outcomes Research evaluates the clinical, economic, and humanistic impact of healthcare interventions. HEOR helps decision-makers understand whether a product or intervention delivers measurable value for patients, payers, providers, and health systems.

HEOR is important because payers and HTA bodies often need evidence on clinical value, cost-effectiveness, budget impact, patient outcomes, and real-world performance before making reimbursement or access decisions.

Health Technology Assessment is a structured evaluation of the clinical, economic, social, ethical, and policy impact of a health technology. It is commonly used to support reimbursement, pricing, adoption, and healthcare policy decisions.

Yes. Epi Fractals supports HTA dossier preparation, value proposition documents, reimbursement support dossiers, objection handler documents, HTA support for new product development, and scientific medical writing.

A strong HTA submission usually requires a clear clinical value story, comparative evidence, health economic analysis, budget impact assessment, real-world evidence where relevant, uncertainty analysis, and payer-focused communication materials.

Evidence synthesis is the process of identifying, evaluating, and combining evidence from multiple sources to answer a focused healthcare question. It can include systematic reviews, meta-analysis, qualitative evidence synthesis, and population health data analysis.

A systematic literature review is a structured and transparent method for identifying, screening, appraising, and summarizing published evidence on a specific research question. It is widely used in clinical research, HEOR, HTA, and market access work.

Network meta-analysis compares multiple interventions across a connected evidence network. It is useful when direct head-to-head trial evidence is limited or when decision-makers need comparative efficacy, safety, or tolerability insights across several treatment options.

Yes. Epi Fractals supports comparative efficacy work, including indirect treatment comparisons, network meta-analysis, efficacy and safety assessments, GRADE assessment, PRO assessment, and qualitative evidence synthesis approaches such as CERQual.

Health economic modelling estimates the clinical and financial value of healthcare interventions. It can include cost-effectiveness analysis, budget impact analysis, predictive modelling, econometric modelling, cost per outcome metrics, and microsimulation.

Budget impact analysis estimates how adopting a healthcare intervention may affect healthcare spending over a defined time period. It helps payers and decision-makers understand whether a product is financially sustainable in a specific setting.

Cost-effectiveness analysis compares the cost and outcomes of one healthcare intervention against another. It helps decision-makers assess whether the added benefit of a product or intervention justifies its cost.

Epi Fractals uses AI-assisted workflows to support evidence generation, unstructured data extraction, cohort development, predictive analytics, causal inference support, evidence synthesis, data extraction, reporting, and model harmonization, with human oversight and validation.

Yes. AI can help accelerate literature screening, data extraction, summarization, report drafting, and workflow organization. For high-stakes evidence work, AI should be combined with human review, validation, documentation, and audit-ready processes.

Epi Fractals emphasizes fit-for-purpose data and study design, robust data provenance, clear curation processes, validation, sensitivity analysis, and interdisciplinary collaboration across public health, health economics, biostatistics, data science, and clinical domains.

Yes. Epi Fractals supports pharmacovigilance and post-market surveillance for pharmaceutical products, medical devices, alternative health system interventions, and clinical trial coordination.

Real-World Data can help identify safety signals, monitor product performance, evaluate adverse events, understand treatment persistence, assess adherence, and generate long-term safety and effectiveness insights after product launch.

Yes. Epi Fractals applies HTA methods to AYUSH and alternative systems of medicine, including regulatory documentation, scientific validation of AYUSH interventions, pharmacovigilance for AYUSH products, and impact assessment.

Yes. Epi Fractals can support nutraceutical companies with evidence generation, real-world studies, health economics, impact assessment, safety monitoring, and scientific validation where appropriate.

Yes. Epi Fractals offers hands-on HTA training and capacity-building programs for research professionals, medical students, healthcare professionals, nursing faculty, pharmacy students, pharmacy faculty, institutions, and universities.

Yes. Epi Fractals can design customized training and capacity-building programs for institutions, universities, healthcare organizations, and research teams that want to build practical skills in HTA, evidence synthesis, and health economics.

You can start by sharing your project objective, target geography, disease area or intervention, available data sources, timelines, expected deliverables, and intended decision use. Epi Fractals can then help define the right evidence generation approach.

Share the project type, research question, product or intervention, target audience, decision context, preferred methodology, available datasets or literature scope, timeline, and whether the output is needed for HTA, reimbursement, publication, regulatory, policy, or internal strategy use.

Choose Epi Fractals when you need a lean, responsive, methodologically rigorous evidence partner with expertise across RWE, HEOR, advanced modelling, systematic reviews, network meta-analysis, biostatistics, AI-assisted workflows, and health policy translation.