January 13, 2021
Lakshmi Santhosh Maithel
Over the last five years, clinical trials in oncology have become increasingly driven by biomarkers rather than defined by the tissue where the tumor was found. This demonstrates an understanding that cancers which share common mutations or other molecular characteristics may be responsive to the same treatments even if identified in different parts of the body. It also represents the precision medicine trend towards more targeted and eventually individualized treatments. Based on this approach, Merck successfully developed the first tissue-agnostic therapy, Keytruda (Pembrolizumab), an immunotherapy drug in 2017. More recently, Bayer’s Vitrakvi (Larotrectinib) targets NTRK gene fusions, a known oncogenic driver mutation, in tumors across tissues.
To meet this shift in scientific conceptualization of disease heterogeneity, clinical researchers have developed the master protocol trial design which includes basket trials, umbrella, and platform trials. Master protocols allow multiple sub-groups defined by molecular profile to run simultaneously in one study. The standard fixed-sample randomized control trial does not account for such patient stratification and is also much more expensive than targeted trials. But while novel master protocols are promising in accelerating therapy development, they also present difficulties related to data management. Scientists need to process, analyze, and visualize various data while collaborating with several parties within a validated, secure environment. Without the right data infrastructure, these challenges can hinder the adoption of innovative trial designs for precision medicine.
Emergence of Master Protocol Trials
A 2015 publication in a journal presenting practical reviews on the latest developments in cancer research, highlights how genome sequencing has enabled a shift towards the master protocol design and also mentions five major studies pioneering this concept. Three were biomarker driven trials including the NCI-Match program specifically for patients with solid tumors and refractory lymphoma of any origin stratified by biomarkers, as well as the I-SPY 2 trial which was not biomarker driven but employed the same trial design. By 2019, a landscape analysis identified 83 master protocols undertaken over the last five years of which the majority (76) were in oncology.
Then last year, another publication on the evolution of trial design described “an exponential increase in publications in this domain during the last few years in both planned and conducted trials”. The same publication described the various categories of master protocols including the basket, umbrella, and platform design. During a basket trial, a single investigational treatment or combination therapy is used to target several diseases with a shared biomarker. Umbrella trials are adopted when multiple treatments are applied to different patient subgroups under the same disease indication. Platform trials also assess responses to multiple treatments but allows for changes in study design according to the discovery of new biomarkers or the success of one treatment, essentially making it an adaptable version of umbrella trials.
Though more biopharma companies are adopting the master protocol design, due to the advantages in cost effectiveness and de-risking clinical candidates, it was actually a leading institute for oncology that piloted molecular characterization in clinical trials. The early IMPACT study in 2007 by University of Texas MD Anderson Cancer Center focused on improving outcomes for solid tumors through targeting treatment based on genetic variants. This was followed by the IMPACT 2 study, exploring molecular profiling for metastatic cancers, and then by an international trial through the World Innovation Network. These programs made the case for master protocols based on patient stratification using biomarkers. More recently, novel trial designs are being applied even outside oncology by researchers in the UK as seen in a preprint from September 2020 which showed potential to improve trial efficiency in immune-mediated inflammatory diseases.
Addressing Data Management Challenges
While it is heartening to see the uptake of master protocol trials as an outcome of increasingly personalized medicine, there are also new challenges. A recent research article on trial design in precision oncology describes how the increased specificity gained from smaller subpopulations also comes with statistical challenges in drawing robust actionable conclusions. The data collected must be managed consistently across studies so that researchers can refer to data from previous trials and learn from the aggregate outcomes. Another publication on precision trials for clinicians, highlights biological plausibility or underlying mechanisms, biomarker prevalence when recruiting, and sample size assumptions as factors that will need to be considered during statistical analysis.
Typically, when identifying trends in data, bioinformaticians generate and share visualizations generated on tools such as RStudio or Tableau. However, using several software solutions in a non-continuous manner also makes it difficult to maintain a full chain of custody. In addition, high dimensional and multimodal data needs to be harmonized across sources whether from internal departments or external CRO partners. Genedata Profiler provides a flexible solution for bringing together disparate data. In addition, it also improves collaboration and data security through defined access roles. Customizable workflows for condensing NGS data and integrating molecular data with patient outcomes enable smarter trial design. Genedata Profiler, as a data management platform, addresses the complexity of translational research, allowing the conversion of data into actionable insights to accelerate the development of precision therapies.
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