Tumor-Agnostic Approvals: Insights and Practical Considerations.

Since the first approval of a tumor-agnostic indication in 2017, a total of seven tumor-agnostic indications involving six drugs have received approval from the FDA. In this paper, the master protocol subteam of the Statistical Methods in Oncology Scientific Working Group, Biopharmaceutical Session, American Statistical Association, provides a comprehensive summary of these seven tumor-agnostic approvals, describing their mechanisms of action; biomarker prevalence; study design; companion diagnostics; regulatory aspects, including comparisons of global regulatory requirements; and health technology assessment approval. Also discussed are practical considerations relating to the regulatory approval of tumor-agnostic indications, specifically (i) recommendations for the design stage to mitigate the risk that exceptions may occur if a treatment is initially hypothesized to be effective for all tumor types and (ii) because drug development continues after approval of a tumor-agnostic indication, recommendations for further development of tumor-specific indications in first-line patients in the setting of a randomized confirmatory basket trial, acknowledging the challenges in this area.

Efficiency of a randomized confirmatory basket trial design constrained to control the family wise error rate by indication.

Basket trials pool histologic indications sharing molecular pathophysiology, improving development efficiency. Currently, basket trials have been confirmatory only for exceptional therapies. Our previous randomized basket design may be generally suitable in the resource-intensive confirmatory phase, maintains high power even with modest effect sizes, and provides nearly -fold increased efficiency for indications, but controls false positives for the pooled result only.

Bayesian hierarchical model for safety signal detection in multiple clinical trials.

Clinical safety signal detection is of great importance in establishing the safety profile of new drugs and biologics during drug development. Bayesian hierarchical meta-analysis has proven to be a very effective method of identifying potential safety signals by considering the hierarchical structure of clinical safety data from multiple randomized clinical trials conducted under an Investigational New Drug (IND) application or Biological License Application (BLA). This type of model can integrate information across studies, for instance by grouping related adverse events using the MedDRA system-organ-class (SOC) and preferred terms (PT).

Meta-analysis of blinded and unblinded studies for ongoing aggregate safety monitoring and evaluation.

During the course of clinical development, ongoing aggregate safety monitoring and evaluation are needed to understand the evolving safety profile and to ensure effective risk-management strategies for medicinal products. CIOMS reports and global regulatory guidance (including from ICH, US FDA, and EMA) compel sponsors for assessment of safety based on aggregate data. To identify and characterize the risks of medicinal products at a program level in a more timely and informed manner, aggregate safety evaluations should combine all available information, including from ongoing blinded trials, completed unblinded trials, and other data sources.

Lessons Learned From Multi-regional Trials With Signals of Treatment Effect Heterogeneity.

Inconsistent results across regions have been reported in a number of recent large trials. In this research, by reviewing results from studies that showed inconsistent treatment effects, and summarizing lessons learned, we provide some recommendations for minimizing the chance of inconsistency and allowing more accurate interpretation when such signs of heterogeneity arise, for example: keep the number of regions for consistency evaluation at a minimum to avoid observing false inconsistency signals; proactively address in the protocol the differences in culture, medical practices, and other factors that are potentially different across regions; closely monitor the blinded data from early-enrolled patients to more effectively identify and address issues such as imbalance of baseline covariates or inconsistency of primary outcome rates across regions. For treatments of life-threatening conditions, the stakes for accurate interpretation of MRCT results are high; the criteria for decisions warrant careful consideration.

Bridging blinded and unblinded analysis for ongoing safety monitoring and evaluation.

In order to better characterize the safety profile of investigational new drugs (INDs) during clinical development, more interest and attention have been paid to ongoing safety monitoring and evaluation. The 2015 US FDA IND safety reporting draft guidance compels sponsors to periodically evaluate unblinded safety data. However, maintaining the trial blind is necessary to avoid jeopardizing the validity of study findings.

Periodic benefit-risk assessment using Bayesian stochastic multi-criteria acceptability analysis.

Benefit-risk (BR) assessment is essential to ensure the best decisions are made for a medical product in the clinical development process, regulatory marketing authorization, post-market surveillance, and coverage and reimbursement decisions. One challenge of BR assessment in practice is that the benefit and risk profile may keep evolving while new evidence is accumulating. Regulators and the International Conference on Harmonization (ICH) recommend performing periodic benefit-risk evaluation report (PBRER) through the product's lifecycle.