The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
In this blog, Adam Hamm, PhD, Director Biostatistics at Cytel shares some of the most important knowledge he uses in his day to day work as a biostatistician working extensively in oncology research. Adam has broad experience with statistical analysis and methodology over all phases (I-IV) of development, in particular working in the oncology arena.
As a Director of Biostatistics at Cytel, I work on design, statistical analysis and reporting projects for a range of biotechnology and pharmaceutical sponsors. During my career, I’ve developed a particular focus on oncology trials, so in this blog I’ll share some insights into the knowledge which I have found particularly vital as a biostatistician working in this area. This knowledge spans specific statistical methodologies and understanding of the clinical issues across the phases of clinical development. The summary is not exhaustive, but provides a glimpse into the broad exposure which is needed for a biostatistician to develop a fully rounded understanding in the area. To learn more, read on...
Single ascending dose (SAD) and multiple ascending dose (MAD) studies are typically the first in human studies. They seek to gain information on safety and tolerability, general pharmacokinetic (PK) and pharmacodynamic ( PD) characteristics, and of course identify the maximum tolerated dose (MTD).
Conventionally, SAD and MAD studies were conducted separately, but increasingly are combined into an ‘umbrella’ protocol which addresses both SAD and MAD objectives.
At the recent JSM meeting in Chicago, Cytel's Jim Bolognese presented the results of work he has conducted evaluating the T-Statistic ( or T-Stat) method for adaptive dose finding of MTD. In this blog we'll provide a brief summary of Jim's findings, and share his slides with our blog readers.
At a recent PhUSE SDE, Cytel’s Chitra Tirodkar presented how East PROC MCPMod could be used to help solve the problem of uncertain true dose-response relationship in a bronchodilator study. In this blog we summarize some of the issues, and make Chitra's slides available for download.
When approaching a Phase 3 clinical trial, the need to ‘de-risk’ the massive investment often leads sponsors on a quest for the perfect risk mitigating adaptation. While a strategically planned clinical trial design can be an important step in giving a new medicine its best possible chance of success, there are a number of other ways that a trial sponsor can minimize study risk.
When testing certain types of new drugs it is known in advance that the adverse side-effects of the medication will limit dose selection. For example, it is well-established that for many new pain medications, the side effects of nausea and vomiting will place constraints on the selection of higher dose levels.
The Journal of the American Medical Association recently published an article entitled ‘The Anatomy of Medical Research: US and International Comparisons.’ The stated objective of the study was to “quantify total public and private investment and personnel (economic inputs) and to evaluate resulting patents, publications, drug and device approvals, and value created (economic outputs)“ 
Amongst the many findings of this comprehensive study, a vital observation is the reduction of early phase spending by about 4% per year from 2004 to 2012. One attribution for this decline involves the financial constraints placed upon proof-of-concept trials, particularly when compared to the expected financial benefits of Phase 3 trials and medical devices. According to the authors, “Many new basic discoveries that have probable clinical value are stymied by financial constraints at the critical proof-of-concept stage, where utility in humans is demonstrated.”  They add that the number of new discoveries that will be underfunded at the proof-of-concept stage is expected to increase.