The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
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.
News Medical interviewed Dr. Rajat Mukherjee, Statistician, and Director of Data Science at Cytel to investigate the potential of data science in clinical development.
The Lung-MAP trial is an innovative biomarker driven 'precision medicine' study which evaluates five novel agents for the treatment of patients with advanced squamous cell carcinoma of the lung. As well as exploring therapeutic options for this indication, it also aims to improve the drug development process.
At a Cytel seminar earlier in the year, Antje Hoering of CRAB presented to delegates on some of the practical challenges of the Lung-MAP study.
We were saddened to learn earlier this year, of the passing of Professor David Sackett. Widely recognized as the father of evidence based medicine, Professor Sackett confronted tough criticism in advancing the cause of evidence based medicine during the early nineties. During his four years at the Centre for Evidence Based Medicine at Oxford, Sackett’s team produced an array of books, articles, curricular and pedagogical practices, and software techniques which remain foundational to EBM's teaching and learning.
Evidence based medicine refers to the practice of incorporating “current best evidence” when determining care for individual patients . Clinicians use their clinical expertise to specify the problem and the evidence necessary to solve it; the evidence itself, however, makes reference to biostatistics and epidemiology .More generally, evidence based medicine defends the view that clinicians should use both their clinical expertise and the findings of general clinical research in their practices, and that neither alone is sufficient to provide an appropriate level of care .
In a widely-cited paper, Sackett explains the irony of having to combat criticisms of championing a practice that was simultaneously ‘too old hat’ and yet also ‘too revolutionary’ . In celebration of David Sackett, we consider Evidence Based Medicine in the early 1990s, and consider new developments twenty-five years later.
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 . 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.
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:
A key stage of exploratory drug development is implementing a proof-of-concept study to demonstrate the safety of a drug. Given the importance of accurate dose-finding for Phase 3 success, methodological improvements to proof-of-concept studies in Phase 2 can translate into greater likelihood of getting a drug to market.
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.
The rise of biomarker based treatments in oncology has meant a reconceptualization of what constitutes a particular disease. According to the American Society for Clinical Oncology, “We can no longer think of cancer as one disease. Even something like lung cancer could be hundreds of different cancers, each defined by specific molecular characteristics requiring different treatment approaches.”  This means that many oncology trials are slowly moving from large-scale studies of generic populations, towards a system where targeted therapies are offered to smaller sets of patients who all possess certain genetic characteristics.
Nina Selaru of Pfizer Oncology, recently gave a talk at a Cytel Seminar in San Diego in which she described a trial for Xalkori, a therapy for non-small cell lung cancer (NSCLC). Pfizer conducted two Phase 3 trials for Xalkori, one for patients who possessed anaplastic lymphoma kinase (ALK-positive patients) and another for other ‘unselected’ patients. The ALK-positive patients were found to respond very well to treatment. Unfortunately, the ALK-positive patients also displayed certain characteristics not present in the other patients: they were younger, non-smokers who displayed signs of adenocarcinoma. There was concern that these characteristics were driving the efficacy of Xalkori.