Biostatistics teams are the foundation of every successful trial. Their analyses determine whether studies are credible, reproducible, and regulator-ready. They’re also the ones carrying a growing burden: balancing limited sample sizes with the demand for higher precision, navigating incomplete or messy datasets, and working under increasing pressure to deliver results faster.

Biostatistics teams already bring the rigor and judgment that guide every successful development program. What they deserve are tools that match the growing scale and complexity of today’s clinical research. That’s where Unlearn comes in.

Our AI-powered solutions extend the impact of biostatistics teams. Whether it’s harmonizing fragmented datasets so analyses aren’t constrained by missing values, simulating entire trials before the first patient is enrolled, or generating external controls that strengthen the credibility of open-label designs, the goal is always the same: to give statisticians greater confidence, flexibility, and precision within the frameworks they already use.

What Makes Our Approach Different 

Unlearn’s Digital Twin Generators (DTGs) are disease-specific models designed to integrate with the statistical frameworks biostatistics teams already rely on. Each model is trained to forecast a participant’s clinical trajectory under standard of care, based only on their baseline characteristics. Because these forecasts are generated exclusively from baseline data, they can be incorporated into standard analyses to adjust for baseline risk in ways that are precise, regulatorily familiar, and immediately useful.

In practice, this gives statisticians a powerful new covariate—an individualized prediction that sharpens comparisons between treatment and control groups without requiring changes to trial design or analysis plans. When trials are underpowered, when treatment effects are subtle, or when variability is high, these forecasts provide the additional resolution needed to detect meaningful signals. They also open the door to exploring responder subgroups across endpoints and timepoints, giving biostatistics teams a clearer view of how treatments perform across diverse patient populations.

Extending Biostatistics Without Adding Burden

Unlearn’s solutions are built to make communication across clinical, statistical, and regulatory teams more straightforward. By providing transparent validation, clear documentation, and pre-specification language for SAPs, we give every group the same reference points to work from.

We also bring in scientific, statistical, and regulatory expertise to work alongside your team. That way, questions get resolved faster, expectations are aligned earlier, and outputs are easier for everyone to interpret and trust. Rather than adding to your workload, our role is to extend your team’s capacity, helping biostatistics teams move from design to analysis with fewer roadblocks and greater confidence.

The Right Tools for the Expertise You Already Have

If you’re planning a study and want to explore how AI-powered solutions can support your statistical team—from harmonizing fragmented data, to simulating trial designs, to generating regulator-ready digital twins—let’s talk.

We’ll walk you through exactly how our approach integrates with the frameworks you already use, and how it can extend the impact of your biostatistics group without adding new complexity or requiring years of infrastructure build.

Because your team doesn’t need to build AI solutions from scratch. They just need the right tools to do even more with the expertise they already have.