When basket trial designs started gaining traction in oncology, biomarker enrichment was the structural logic that made them work. Define the patients most likely to show a drug effect, stratify by molecular subtype, and give the signal somewhere to land. That same thinking is now moving into the development of autoimmune and immune-mediated diseases, and the implications extend well beyond the basket design itself.
Biomarker eligibility criteria shape outcomes in any immunology or inflammation protocol in which the eligible patient population is smaller than the screened population. In this therapeutic area, that is nearly every trial.
What Basket Trial Design Gets Right About Eligibility
Early phase basket trials in immunology must be explicit about biomarker logic in ways that single-indication trials often aren’t, as the design depends on it. Our white paper on basket trial methodology in immune and autoimmune conditions maps four ways biomarkers function in these programs, and each warrants examination on its own terms.
The first is cohort selection and trial eligibility. Biomarker-based enrichment increases the likelihood of observing a drug effect by aligning the enrolled population with the drug’s mechanism of action. The goal is to define, based on the protocol, who is likely to respond, and to establish the conditions for signal detection before a single patient is screened.
The next function is endpoint anchoring. Consistent biomarker assessment across cohorts creates a shared study readout. Biomarkers can serve as primary or key secondary endpoints, enabling meaningful comparisons that early clinical endpoints often cannot provide.
The third is adaptive decision-making. In a multi-cohort setting, biomarker signatures serve as early signals of efficacy or futility. Robust early biomarker activity supports cohort expansion. The absence of an expected biomarker change can justify redirecting resources away from an indication that isn’t responding. That’s the design working as intended.
The fourth is within-disease patient stratification. Not every patient within a given indication presents the same way. Identifying the subgroup most likely to respond and enrolling specifically in that subgroup produces a more efficient trial and a more defensible one from a regulatory standpoint.
Why This Logic Matters Beyond Design
These four functions, eligibility enrichment, endpoint anchoring, adaptive signaling, and within-disease stratification, apply to any immunology and inflammation protocol. Basket trials make them visible because the multi-indication structure forces explicit decisions about biomarker rationale. In single-indication trials, the same decisions are often implicit, under-specified, or deferred.
That gap tends to show up during enrollment. Screen failures in immunology and inflammation trials frequently stem from eligibility criteria written for regulatory tidiness rather than real-world patient presentation. The patients exist. The criteria just don’t find them.
Getting those decisions right is a protocol design question that needs to be answered before enrollment opens. The biomarker-enrichment logic that underlies basket trials is a useful framework for asking that question in any trial context.
For a closer look at how biomarker precision connects to enrollment outcomes across autoimmune indications, download our white paper: Advancing Immunology Research Through Early Phase Basket Trials: Opportunities and Pitfalls.
