The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.

Relative Clinical Efficiency and Phase 2 Biomarker Studies

April 9, 2015

Last year. Nature Reviews Drug Discovery asked the FDA’s Tatiana Prowell (Hematology & Oncology Products Division) about the most common pitfalls confronting clinical trials in oncology. She cited the late stage evaluations of biomarkers as one of three critical issues leading to regulatory failure [1]. The primary lesson: those who want to test biomarkers need to start earlier.  

OncoMed’s Eric Holmgren recently expanded on the nature of the problem, at a Cytel and ASA sponsored symposium on Statistical Innovations in Clinical Development. According to Holgren, the use of biomarker testing during Phase 2 can satisfy many forward-looking objectives. The objectives to prioritize, however, should depend quite significantly on a clinical trial sponsor’s resource constraints and asset value, and in particular on pre-Phase 2 costs. He considers three scenarios to illustrate how the investment undertaken in pre-Phase 2 studies should shape the objectives of Phase 2.

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Translational Statistics: How to Move Beyond the Comfort Zone

November 6, 2014

Professor LJ Wei holds that rules are for lawyers, not (necessarily) clinicians. When designing modern clinical trials, the impetus is often to use “efficient and reliable procedures, to obtain clinically interpretable results with respect to risk-benefit analysis…” Yet these efficient and reliable procedures are often just conventions and rules that provide information that is incomplete or difficult to make clinically interpretable.

In a presentation to the East User Group Meeting, Professor Wei identifies 11 problematic areas that currently challenge trial designers. After giving an overview of the challenges that arise in each, Professor Wei provides a few simple solutions about how to overcome them. All the solutions, however, require moving beyond the comfort zone of conventional procedures.

In the slides attached Wei discusses:

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5 Reasons to Invest in Adaptive Designs for Population Enrichment

July 8, 2014

Predictive_Enrichment

The above graphic is from Cyrus Mehta's slides on 'Adaptive Population Enrichment for Oncology Trials with Time to Event Endpoints.'


 

Recent advances in precision medicine have meant that therapeutic treatments can now target subsets of a population that are most likely to respond well to treatment. Identification of such subsets largely relies on the presence or absence of particular biomarkers. In order to determine whether or not such biomarkers have predictive diagnostic capabilities, the biomarkers must first be validated as reliable predictive indicators, and thereafter as responding efficaciously to treatment.

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Overcoming Prowell's Pitfalls: Cytel Weighs in on Strategies for Oncology Development

June 10, 2014

 East: Learn More

The FDA’s Tatiana Prowell (Breast Cancer Scientific Lead in the Office of Hematology  & Oncology Products) recently gave an interview to the Nature Review Drug Discovery, in which she discusses the top three pitfalls faced by drug developers in oncology. Issues which Prowell cite include: selection of appropriate dosage, trial designs without sufficient thought given to interim data, and untimely decisions on the use of biomarkers.

According to the article, “some 90% of drugs that enter phase 1 eventually fail.” The prevalence of these pitfalls is noteworthy for oncology drug development, not least becaues of how easy they are to avoid.When coupled with innovative trial design can achieve significant benefits in efficacy and cost-effectiveness. For example, model-based dose-escalation methods can be used to improve the model dose toxicity profile of the drug in question. Cytel Statistician Charles Liu shows how simple it is to use Cytel’s software to select the optimal dose to carry forward.

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