New publication addresses critical issues in ultra-orphan indications

Posted by Cytel

Nov 5, 2018 7:01:00 AM


Cytel biostatisticians Cyrus Mehta and Lingyun Liu, together with Charles Theuer, CEO of TRACON Pharmaceuticals have recently co-authored a publication in the journal Annals of Oncology: “ An Adaptive Population Enrichment Phase 3 Trial of TRC105 and Pazopanib Versus Pazopanib Alone in Patients with Advanced Angiosarcoma (TAPPAS Trial)”. The paper explores the features of this innovative population enrichment, adaptive sample size re-estimation trial and how it overcomes some fundamental challenges of clinical development in ultra-orphan oncology indications. The publication is timely, in the context of the August 2018 news that the FDA has launched a complex and innovative designs pilot program to facilitate and advance the use of complex adaptive, Bayesian, and other novel clinical trial designs in late-stage drug development. The initiative seeks to further innovation by allowing the FDA to publicly discuss those trial designs that are being considered through the pilot program. Indeed, the TAPPAS trial incorporated regulatory input from both the FDA and EMA and received a Special Protocol Assessment from the FDA. As of the date of publication, the authors were not aware of any other pivotal population enrichment trial that has been implemented in oncology, and therefore the paper’s deconstruction of the design’s key elements will be invaluable to researchers considering similar innovative approaches.

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For context, angiosarcoma is an extremely rare tumor type, and as with other such orphan diseases, it is not feasible to conduct multiple trials in multiple settings that characterize the more typical drug development paradigm in oncology. The rarity of the tumor type inherently brings scarcity of patient resources and sample size challenges. Specifically, the TAPPAS trial design needed to take into account the fact that the estimates of clinical benefit brought to the Phase 3 trial were not based on randomized phase 2 data. By incorporating an adaptive sample size re-estimation, the design protects the power from deteriorating due to the uncertainty of the treatment effect.


Importantly, angiosarcoma is a heterogeneous tumor type, and researchers working in such indications face a dilemma when deciding if they should enroll patients to their trial irrespective of their biomarker status, or restrict to the targeted subgroup. Often, by the time this decision needs to made, there is insufficient evidence that the new medicine isn't, in fact, effective in the non-target subgroup and so using the narrow subgroup might mean patients not receiving a potentially beneficial treatment. On the other hand, moving forward with a larger trial in a broader population could expose trial subjects unnecessarily to a potentially ineffective treatment, as well as diluting the treatment effect- meaning that a therapy that could be effective in the target subpopulation doesn't ultimately get approval. The TAPPAS design accounts for the possibility that a more pronounced drug effect might be seen in patients with the cutaneous form of angiosarcoma, than its non-cutaneous form by also using a population enrichment adaptation. If the combination of TRC105 and Votrient appears to be effective in cutaneous patients, with limited activity in non-cutaneous patients, then following the interim analysis, the design enters an “enrichment zone” and enrolls only cutaneous patients going forward.


To learn more about the design, click the button below to read the publication in Annals of Oncology.
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Cytel’s industry-leading East software will be launching a new module ENRICH in version 6.5 to facilitate population enrichment trial design. Click here to request information about this module when it is available later in 2018. 

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 Further reading

Addressing Critical Unmet Needs in the Era of Precision Medicine

 

 

Topics: clinical research, clinical trials, Oncology, Precision Medicine, adaptive trials, adaptive designs, adaptive sample size re-estimation, population enrichment

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