Home›Oncology› Adaptive Phase I/II designs for drug combinations remain methodologically diverse but rarely implemented
Adaptive Phase I/II designs for drug combinations remain methodologically diverse but rarely implementedNew trial designs could speed up testing drug combinations
Frontiers in MedicinePublished September 22, 2026Study authors: Junying Wang, Song Wu, Jie YangDOI ↗Editorial oversight: Dr. Julia Lee, PhD · Oncology, Genomics & Drug Development
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Key Takeaway
Interpret adaptive Phase I/II combination designs as promising but under-implemented methods.
This narrative review examines adaptive Phase I/II clinical trial designs for drug combinations. It catalogs design frameworks across model-based, model-assisted, utility-based, and response-adaptive randomization approaches, covering both discrete and continuous dose settings. The review is methodological in scope and does not report clinical outcomes, effect sizes, or safety data for any specific drug or regimen.
The authors identified multiple design frameworks but found few published real-world implementations. They also note that software directly tailored to seamless Phase I/II combination trials remains limited. No sample size, follow-up duration, or comparator data are reported, consistent with the review's focus on trial methodology rather than trial results.
Key limitations acknowledged by the authors include the limited real-world implementations and the limited availability of tailored software. Funding sources and conflicts of interest are not reported. The review identifies methodological frameworks rather than clinical outcomes of specific drugs, so no conclusions about efficacy or safety can be drawn.
For practice, broader use of these designs would require clearer design-selection guidance, accessible software, robust delayed-outcome extensions, and protocol templates. Clinicians should interpret this as a methodological overview that highlights infrastructure gaps rather than as evidence supporting any particular combination regimen.
How this fits prior evidence
This review addresses a methodological gap rather than a clinical finding, so it does not directly confirm or contrast with prior coverage of biophotonic imaging, the Divide-Survive Matrix, photoacoustic imaging, the CXCL16/CXCR6 axis, or Tumor Treating Fields. Prior items focused on imaging translation, tumor assessment tools, and biological pathways. This review instead maps adaptive Phase I/II design frameworks for drug combinations and notes limited real-world implementation and limited tailored software, extending the theme of early-stage tools that remain unvalidated or under-implemented in practice.
When doctors try to find new ways to treat cancer, they often have to test multiple drugs at the same time. This can make the testing process complicated and slow. New trial designs, called adaptive designs, aim to make this process smoother by adjusting the study as it goes.
Researchers identified several frameworks to help manage these types of trials. These methods can handle different ways of measuring doses and help researchers decide how to group patients. These designs are intended to make the jump from early testing to more advanced trials easier for drug combinations.
While these frameworks exist, there are still hurdles to clear. Currently, there are very few examples of these designs being used in the real world. Also, there is a lack of software specifically built to manage these complex trials. More tools and clearer guidelines are needed before these methods can become common practice.
What this means for you:
New trial designs can help test drug combinations for cancer, but more tools and real-world use are needed.
Common questions
What are adaptive trial designs?
Adaptive designs are trial frameworks that allow researchers to make changes to a study based on the data they collect. In this case, they are used to test combinations of drugs for cancer. These designs can adjust for different dose settings and help manage the complexity of testing multiple drugs at once.
Are these designs being used in hospitals now?
While the frameworks for these designs have been identified, there are currently very few real-world implementations. The study noted that there is a lack of software specifically tailored to manage these types of trials seamlessly, which means they are not yet common in everyday practice.
How do these designs help with cancer treatment?
These designs help by providing a structured way to test drug combinations. They offer different frameworks, such as model-based or response-adaptive randomization, to help researchers move from early testing to later stages more effectively. However, more clear guidance and templates are still needed for widespread use.
Adaptive Phase I/II designs can jointly use toxicity and efficacy information to guide dose allocation and regimen selection. These designs are particularly relevant for oncology drug-combination trials, where the optimal regimen may not coincide with the maximum tolerated dose.
We conducted a structured narrative review of adaptive Phase I/II designs for oncology drug combinations that use both toxicity and efficacy information for adaptive allocation or final regimen selection. PubMed was searched through April 16, 2026 using terms related to Phase I/II, seamless design, drug combinations, dose-finding and efficacy, optimal biological dose, dual-agent, efficacy-toxicity trade-off, utility-based dose-finding, and adaptive randomization. Google Scholar and reference lists were used for supplementary citation chasing, and ClinicalTrials.gov was searched for illustrative real-trial applications.
Adaptive Phase I/II designs for drug combinations were identified across model-based, model-assisted, utility-based, and response-adaptive randomization frameworks for both discrete and continuous dose settings. Across designs, the main trade-offs involved assumptions on monotonicity and ordering, the ability to handle delayed outcomes, transparency of decision rules, computational burden, and software availability. Our targeted search identified few published real-world implementations, and software directly tailored to seamless Phase I/II combination trials remained limited.
Adaptive Phase I/II designs for drug combinations are methodologically well developed but remain difficult to implement routinely. Broader use will require clearer design-selection guidance, accessible software, robust delayed-outcome extensions, and protocol templates that communicate operating characteristics to clinical and regulatory stakeholders.
