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Open research questions in Statistical Methods in Clinical Trials

116 unresolved questions extracted from the limitations and future-work sections of 720 Statistical Methods in Clinical Trials papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • One challenge is the lack of standard options or targetable biomarkers for rare and ultra-rare cancers. Another challenge is the high biological heterogeneity of rare and ultra-rare cancers, which limits the utility of traditional drug repurposing approaches. The paper also mentions the challenge of combinatorial complexity in in silico drug screening, which limits the utility of these approaches in oncology workflows.

    Off-target drug repurposing for rare and ultra-rare cancers: towards a scalable therapeutic framework · 2026 · DOI

  • Traditional drug repurposing approaches are limited by the availability of biologically well-characterised tumours or validated experimental tissue models - In silico drug screening is constrained by combinatorial complexity as drug libraries expand and more disease-targets are discovered - Rare and ultra-rare cancers cannot be studied within the context of randomised trials due to shortage of cases and high biological heterogeneity

    Off-target drug repurposing for rare and ultra-rare cancers: towards a scalable therapeutic framework · 2026 · DOI

  • The challenge of selecting the restriction time for restricted mean survival time, as a small time may overlook late-emerging benefits, while a large time can inflate variance. The need for a data-driven, adaptive procedure that balances effect size and estimation precision. The lack of a rigorous theoretical foundation that accounts for the additional variability introduced by adaptive selection.

    Beyond Fixed Restriction Time: Adaptive Restricted Mean Survival Time Methods in Clinical Trials · 2026 · DOI

  • The reporting of platform features and the availability of results were insufficient.

    Characteristics, Progression, and Output of Randomized Platform Trials · 2024 · DOI

  • Therapeutics that are granted breakthrough therapy designation can receive accelerated or traditional approval; however, little is known about those approved through the latter pathway, where postmarketing confirmatory studies are typically not required, regardless of the end point used.

    Premarket Pivotal Trial End Points and Postmarketing Requirements for FDA Breakthrough Therapies · 2024 · DOI

  • The design of bioequivalence studies often demands careful compromises between practical considerations of ethics and statistical reliability. The lack of large samples and broad confidence intervals limits the effectiveness of bioequivalence studies. The use of WGANs may not be suitable for all types of bioequivalence studies.

    The Use of Generative AI to Create Hybrid Populations for Bioequivalence Trials · 2026 · DOI

  • The study is limited to three randomized, single-dose, 2 × 2 crossover bioequivalence studies. The study does not explicitly outline the drawbacks of synthetic data alone. The use of WGANs may not be suitable for all types of bioequivalence studies.

    The Use of Generative AI to Create Hybrid Populations for Bioequivalence Trials · 2026 · DOI

  • The development of new methods for sample size determination is needed. The evaluation of the effectiveness of the methods used for sample size determination is needed.

    A systematic review of sample size determination in Bayesian randomized clinical trials: full Bayesian methods are rarely used · 2026 · DOI

  • The use of fully Bayesian methods for sample size determination is rare. There is a need for improved translation of methods for Bayesian sample size determination into practice.

    A systematic review of sample size determination in Bayesian randomized clinical trials: full Bayesian methods are rarely used · 2026 · DOI

  • Lack of standardized international criteria for AI-based solutions - Limited clinical translation of patient-centered AI models - Insufficient standardization of data formats, model validation, and performance assessment

    Patient-Centered Artificial Intelligence Approaches in Pharmaceutical Formulation Development: A Review · 2026 · DOI

  • Future research should investigate the factors contributing to the increase in issues raised over time. Further studies should examine the impact of regulatory pathways on the development of new oncology medicines.

    Trends in EU regulatory assessment of oncology medicines · 2026 · DOI

  • The study identifies a gap in the understanding of the trends in EU regulatory assessment of oncology medicines. The research gap is related to the lack of comprehensive analysis of the impact of application characteristics on procedural metrics.

    Trends in EU regulatory assessment of oncology medicines · 2026 · DOI

  • The classical derivation of confidence intervals introduces a small but systematic error, particularly for small n or larger α. The paper's method is limited to certain events, such as the probability of success in repeated trials.

    Beyond the Rule of Three: A Simple Lower Confidence Bound for Certain Events · 2026 · DOI

  • Future research can apply the paper's method to other real-world problems involving certain events. Future research can explore the limitations of the paper's method and potential extensions. Future research can compare the paper's method to other methods for confidence bounds.

    Beyond the Rule of Three: A Simple Lower Confidence Bound for Certain Events · 2026 · DOI

  • The traditional oncology dose selection strategy has proven inadequate for targeted and immunotherapies. Doses lower than MTD may provide similar efficacy benefit with reduced toxicity.

    A Two-Stage Dose Optimization Framework for Oncology Drug Development with Multiple Efficacy and Safety Endpoints via an Integrated Benefit-Risk Assessment · 2026 · DOI

  • Further investigation of the use of RMP in other contexts, such as rare diseases and pediatric trials. Development of more efficient and robust hyper-parameter elicitation routines.

    On the Interplay Between Prior Weight and Variance of the Robustification Component in Robust Mixture Prior Bayesian Dynamic Borrowing Approach · 2026 · DOI

  • The current practice of fixing the variance of the robustification component to a unit-information variance can lead to suboptimal performance. The lack of a comprehensive understanding of the interplay between prior weight and variance of the robustification component.

    On the Interplay Between Prior Weight and Variance of the Robustification Component in Robust Mixture Prior Bayesian Dynamic Borrowing Approach · 2026 · DOI

  • The gap in understanding how parameters affect the system's output in systems biology models. The need for effective methodologies for sensitivity analysis in these models.

    Determining parameter impact in systems biology models via sensitivity analysis: a comparative approach · 2026 · DOI

  • However, when the normality, linearity, or the random-intercept assumption is violated, the validity and efficiency of the mixed-model ANCOVA estimators for estimating the average treatment effect remain unclear.

    On the Mixed-Model Analysis of Covariance in Cluster-Randomized Trials · 2026 · DOI

  • Lack of clear interpretability in existing ranking methods. Failure to adequately account for uncertainty in existing ranking methods. Overinterpretation of minor differences in existing ranking methods.

    Producing treatment hierarchies in network meta-analysis using probabilistic models and treatment-choice criteria · 2026 · DOI

  • Existing ranking methods in network meta-analysis have limitations. There is a need for a more reliable and clinically meaningful treatment hierarchy.

    Producing treatment hierarchies in network meta-analysis using probabilistic models and treatment-choice criteria · 2026 · DOI

  • To evaluate the performance of the proposed method in real-world applications. To explore the use of non-parametric models for the cumulative distribution function. To investigate the applicability of the method to other types of clinical trials.

    Literature-based meta-analysis of adverse events accounting for heterogeneous follow-up duration in oncology clinical trials · 2026 · DOI

  • Standard meta-analysis techniques are limited by heterogeneous follow-up durations. Prior methods do not account for the dependence between the follow-up duration and the time until the first occurrence of the adverse event.

    Literature-based meta-analysis of adverse events accounting for heterogeneous follow-up duration in oncology clinical trials · 2026 · DOI

  • Network meta-analysis has limitations in synthesizing evidence across multiple treatment doses and timepoints. There is a need for a framework that can combine dose-response and time-course relationships.

    Model-based network meta-analysis: Joint estimation of dose–response and time–course relationships · 2026 · DOI

  • The review is limited to pairwise meta-analyses of oncology therapies. The review only includes meta-analyses published since 2021.

    Treatment switching in evidence synthesis in oncology: A systematic review of current meta-analytical practices · 2026 · DOI

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116 open questions have been extracted from the limitations and future-work passages of 720 Statistical Methods in Clinical Trials papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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