Health research runs on rigor. Every survey, every respondent, every data point carries weight because the decisions on the other end affect real patients. Cutting corners is not an option.
Thera-Business, a health research and scientific company supporting medical device and pharmaceutical organizations, has spent years proving that rigor and speed can coexist. How they’re using AI is the clearest example of that yet.
The problem with hard-to-reach respondents
Thera-Business operates in a niche where the respondents needed for a given study are often the hardest people to find. Patients living with rare diseases. Physicians performing uncommon procedures. Highly specific criteria that eliminates most of the population before a study even begins.
Finding those respondents used to mean grinding through a manual, time-consuming and costly process - and building study timelines around that reality.
It was very labor intensive work to find very specific niche respondents, hard to reach respondents. Finding the exact combinations was very manual and it would take time to bring all of this together.
— Red Thaddeus Miguel, CEO, Thera-Business
With Qualtrics, Thera-Business can now access the scale and respondent reach required to move quickly on complex studies, without sacrificing the methodological rigor their clients depend on.
A laboratory before the real work begins
When early access to Qualtrics’ synthetic data panels became available, Thera-Business approached it the way they approach everything: with a rigorous testing process. In a field where AI hype is common and accuracy is non-negotiable, they needed to verify for themselves how well the synthetic data reflected the actual populations before putting it to use.
Their initial findings were promising to keep going. As the underlying model improved, accuracy improved with it to the point where Thera-Business found a genuinely useful application: using synthetic data as a pre-study testing ground.
It’s been like a research laboratory for us to try different approaches and see if it’s actually possible to make things more efficient before we do the real surveys.
— Red Thaddeus Miguel, CEO, Thera-Business
The use case is practical and specific. When a methodological approach has potential to make a survey run faster or surface richer insights, Thera-Business can stress-test it against synthetic data first. If it holds up, it goes into the real study. If it doesn't, the cost is minimal. For clients operating in a highly regulated environment like healthcare, that de-risking translates directly into faster turnaround and lower costs, without any compromise to data quality.
Rigor at scale
Thera-Business is growing rapidly, and the complexity of their projects is growing with them. The ability to scale survey services without compromising on quality is what makes that growth sustainable, and it’s where the partnership with Qualtrics has become essential.
Health research is a field where the cost of a flawed study is high and the pressure to move quickly is relentless. A testing environment that lets research teams validate their approach before committing to a full study changes the economics of the work, and the confidence behind it.
For health research teams where every result has downstream consequences, that kind of infrastructure from reaching niche respondents to testing methodologies to scaling complex regulated studies makes a real difference.
