Simulate Real-world Stakeholders. Accelerate Better Decisions.
Synthetic Users are AI-generated representations of physicians, patients, caregivers, and other healthcare stakeholders that participate in dynamic, interview-based research. Built using advanced AI, healthcare-specific knowledge, and proprietary behavioral frameworks, Synthetic Users provide lifelike responses that mirror how people think, feel, and make decisions.
With up to 93% parity to human respondents, life sciences teams can test ideas, pressure-test assumptions, and generate insights in days instead of months.
Why Synthetic Users?
Traditional qualitative research is powerful – but recruiting, scheduling, interviewing, and analyzing respondents can take months.
Synthetic Users dramatically compress that timeline, allowing teams to explore questions, evaluate opportunities, and iterate in real time. Rather than waiting weeks for feedback, teams can test ideas, challenge assumptions, and refine strategies in days.
Speed
Generate stakeholder feedback in days, not months.
Human-like Responses
Built to reflect both rational thinking and emotional reactions - the two key drivers of decision-making - not just factual knowledge.
Flexible & Scalable
Create any type of stakeholder across specialties, geographies, languages, experience level, and stages of the patient journey.
Proven Parity
Achieve up to 93% alignment with human respondents across themes, reasoning, emotional responses, and behavioral drivers.
Commercial Impact
Reduce uncertainty and improve decision-making across research, strategy, commercialization, and business development.
What You Receive
Every Synthetic User engagement is tailored to your objectives and may include:
Interactive stakeholder interviews that can respond to stimuli in any language
Interview transcripts and verbatims
Key themes and strategic insights
Drivers and barriers analyses
Opportunity and risk identification
Audience comparisons
Optimization recommendations
Executive-ready summaries and implications
The result is actionable insight - not just AI-generated output.
One Platform. Every Stakeholder.
Synthetic Users can be configured to represent virtually any audience involved in healthcare decision-making.
01
Healthcare Professionals
01
Healthcare Professionals
- Specialists
- Primary care physicians
- Nurses
- Advanced practice providers
- Key Opinion Leaders
02
Patients & Caregivers
02
Patients & Caregivers
- Chronic disease patients
- Rare disease populations
- Care partners
- Advocacy perspectives
03
Internal Stakeholders
03
Internal Stakeholders
- Commercial teams
- Medical Affairs
- Clinical Development
- Business Development teams
Built for Every Stage of the Product Lifecycle
Sample Applications Include:
1. Market Research
Generate hypotheses, optimize discussion guides, pressure-test concepts, and accelerate learning before and after fieldwork.
2. Competitive Intelligence
3. Business Development & Licensing
4. New Product Planning
5. Marketing & Brand Strategy
6. Biotech & Emerging Companies
7. Sales Enablement & Training
How Synthetic Users Are Different
Most AI tools generate answers. Synthetic Users generate perspectives.
Unlike generic AI chatbots, Synthetic Users are designed to behave like
respondents – not search engines. Each persona combines:
- Healthcare-specific knowledge sources
- Multiple advanced AI models
- Proprietary psychometric frameworks
- Emotional-state modeling
- Behavioral decision-making patterns
- Multi-agent architectures designed to create more nuanced and realistic responses
The result is a more realistic simulation of how stakeholders think, feel, prioritize, and make decisions.
Designed to Mirror How People Think, Feel, and Decide
Synthetic Users are evaluated against human respondents using a structured parity framework that examines not just what people say, but how they think and make decisions.
These dimensions combine into a holistic measure of synthetic-organic parity, helping teams understand how closely Synthetic User responses align with real-world stakeholder feedback.
Up to 93% synthetic-organic parity.
AI-powered. Research-led.
Technology alone does not create meaningful insights.
Synthetic Users are most powerful when guided by thoughtful research design, expert moderation, and deep life sciences expertise. SAI combines advanced AI capabilities with decades of experience helping healthcare organizations answer complex strategic questions.
This means clients benefit from the speed of AI while maintaining the rigor of research best practices.
A Powerful Complement to Traditional Research
Synthetic Users are designed to reduce research waste – not research rigor. They help teams:
Generate stronger hypotheses
Prioritize opportunities earlier
Optimize materials before fielding
Answer follow-up questions between research waves
Explore strategic questions when traditional research is not feasible
For critical business decisions, Synthetic Users work best alongside traditional market research and stakeholder engagement.
The result is faster learning, sharper strategy, and more confident commercialization decisions.
Ready to See Synthetic Users in Action?
Discover how Synthetic Users can help your organization make faster, smarter, and lower-risk commercialization decisions.
Frequently Asked Questions (FAQs)
What are Synthetic Users?
Synthetic Users are AI-generated representations of healthcare stakeholders that participate in interactive, interview-based research. They are designed to simulate how physicians, patients, caregivers, and other audiences think, feel, and make decisions, allowing teams to generate insights faster and explore ideas before, after, or alongside traditional research.
How are Synthetic Users different from ChatGPT or other AI tools?
Unlike general-purpose AI tools, Synthetic Users are specifically designed to simulate stakeholder perspectives. They combine multiple advanced language models, healthcare-specific knowledge sources, and proprietary psychometric frameworks to create more realistic, emotionally grounded responses that reflect how real stakeholders evaluate information and make decisions.
How accurate are Synthetic Users?
Synthetic Users have demonstrated up to 93% parity with human respondents across dimensions such as thematic alignment, reasoning structure, emotional response, and behavioral drivers. While no AI model can perfectly replicate human behavior, Synthetic Users provide a highly credible way to generate hypotheses, test ideas, and explore stakeholder reactions.
When should I use Synthetic Users instead of traditional market research?
Synthetic Users are most valuable when you need rapid, directional insights, want to test multiple ideas quickly, or need to answer questions that arise between research waves. They can help generate hypotheses, optimize stimuli, explore competitive scenarios, and pressure-test strategic decisions. For high-stakes decisions, Synthetic Users are best used alongside traditional market research rather than as a replacement.
What audiences can Synthetic Users represent?
Synthetic Users can be customized to represent a wide range of healthcare and commercial stakeholders, including physicians, nurses, patients, caregivers, health system decision-makers, and other specialized audiences. Personas can be tailored by geography, specialty, knowledge level, experience, personality traits, and other characteristics relevant to the research objective.
Can Synthetic Users help with competitive intelligence and business development decisions?
Yes. Synthetic Users can be used to explore reactions to competitive launches, evaluate target product profiles, assess potential drivers and barriers to adoption, test positioning strategies, and generate directional feedback on business development opportunities. They provide a fast and scalable way to pressure-test assumptions before making larger investments in research or commercialization activities.
Is my data secure?
Yes. Synthetic Users operates within a closed, SOC 2-compliant environment designed to protect confidential research and business information. Client data remains secure, is not used to train external AI models, and is managed using enterprise-grade security, privacy, and governance practices.