Confirm Solutions for Phase III Clinical Trials
Accelerating automated trial design - delivering more drugs, safer drugs, at lower prices - approved and in the hands of patients in urgent need.
Statisticians have been developing faster, cheaper, and more efficient ways to run studies, but gaining regulatory acceptance of new techniques can be a difficult process. Our team began as group of statistics postdocs and doctoral students from Stanford University, working on advanced mathematical techniques for modeling and validating new study designs. We are now a public benefit corporation, creating open-source software that medical regulators can use to rapidly understand how a study design operates and form confident opinions. We aim to enable drug development organizations to propose radically new trial designs, and make regulation faster and more predictable.
State-of-the-art Bayesian models for simulating Phase III drug trials
Run large-scale simulations of trials and turn the output into statistically rigorous proofs about Type I Errors.
Open Source software for validating experiment designs and statistical inference plans
We have open sourced our code. We believe that these tools can be adopted by any drug development organization and any regulator, worldwide.
A Google Colab-like environment for designing and developing drug trials
We are in the process of building an extensible platform to enable researchers and drug development organizations to rapidly prototype their own models.
A cloud computing back-end for drug trial model simulation at scale
Leveraging the power of cloud computing, we can conduct larger and more computationally intensive simulations - easier, faster, and more cost-effectively