DyNaSynth™ is Kingfish’s dynamic synthetic control platform. It builds a comparator cohort from curated external data, historical trials, and real-world evidence, using adaptive statistical modeling to help evaluate a treatment when a traditional control arm may be impractical or inappropriate.
In many trials, researchers compare patients receiving an intervention with a separate control group. For some conditions or procedures, withholding treatment can be ethically or practically difficult. A carefully designed external comparator can help provide context for interpreting outcomes from a single-arm or hybrid study.
The platform combines relevant patient data from multiple sources. Its empirical Bayesian information-borrowing and adaptive weighting methods are designed to align the comparator with the treatment population while accounting for differences among source datasets. Kingfish then validates the cohort and prepares an analysis suited to the study’s objectives.
The suitability of an external control depends on the disease, available data, study design, and regulatory question. Randomized trials remain appropriate for many applications. Kingfish works with sponsors to plan the evidence strategy and discuss proposed designs with regulators through the relevant pathways.
Tell us about your study, the comparator challenge, and the data available. We can discuss whether DyNaSynth may fit your program.
