The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
Early stage Phase 2 clinical trials are often designed as multi-stage single arm trials, which quickly identify inefficacious molecules and interventions, without subjecting too many patients to treatments with questionable standard of care. As the primary purpose of these designs is the early stopping for futility, it is often the case that very small cohorts enroll in early stages of the design. A larger cohort is only allowed to enroll when results from earlier enrollment suggest that there is clinical benefit to the new treatment.
The rise of Bayesian methods has meant that predictive power can be used to assess efficacy during these single arm Phase 2 studies, but how do they differ from traditional designs and when should they be used?
Most people know that clinical drug discovery is usually conducted using either Frequentist or Bayesian methods. These two statistical paradigms have enjoyed a degree of competition historically, with some statisticians tauting the statistical rigor of Frequentist designs and others the intuitiveness and flexibility of Bayesian clinical trials. Recently, though, a number of hybrid methods have arisen, that leverage the benefits of both paradigms for singularly powerful clinical trials. A new Cytel article outlines the benefits of these combined methods.
In the world of clinical trials, the pace of innovation is accelerating, and approaches such as Bayesian methods are gaining traction. These methods bring flexibility and speed to clinical trial design and analysis, and with increased access to the necessary computational power, are transforming today’s clinical research . However, the number of simulation and modeling tools necessary to perform Bayesian computations requires statisticians to be well-resourced technologically. Many biostatisticians may not readily have access to the cloud computing power to make these design approaches practical within the time constraints afforded for statistical design.
There are many dose-finding designs that have been developed over the past 30 years and several more are anticipated . Sponsors often face the dilemma of choosing from the various design options available today. Finding the right dose in Phase 2 gives a potential new therapy its best chance to demonstrate efficacy during Phase 3, and Bayesian techniques prove to be useful for optimal dose-finding.
The convergence of several distinct trends has made wearables an increasingly attractive option for use in confirmatory clinical trials. A number of considerations arise, though, when sponsors choose this route, from how to construct clinically meaningful digital biomarkers, to how to determine the quality of the data they collect.
A recent Cytel webinar illustrated how wearables have been used in Parkinson’s disease, as well as in studies where actigraphy became a vital endpoint. Here are three considerations for utilizing wearables in clinical studies that emerged during this study.
In a previous post, I discussed the importance of proper use of CDISC Controlled Terminology (CDISC CT) in SDTM. However, the CDISC-CT is not the only submission terminology you need to be familiar with when building SDTM datasets to be submitted to the FDA (and similarly to the PMDA). As per the FDA Data Standards Catalog, when submitting datasets to the agency, you need to follow not only the CDISC standards (SDTM, ADAM, define-xml and CDISC-CT) but also a number of other submission terminologies. For example, this is the case of MedDRA when your SDTM package contains Adverse Events data, or WHO Drug Dictionary for Medications, but there are also a number of other submission terminologies you need to apply, particularly in the TS – Trial Summary Dataset.
A number of presentations and papers have been published discussing TS domain and clarify requirements that are not always fully clear in the SDTM IG or in the agencies Technical Conformance Guide.
In this blog, I focus on TS and discuss some specific parameters that you need to submit in TS using various “external” dictionaries, and help you understand how to find the correct term (and code).
C-Suite and R&D Decision-Makers are always striving to make evidence-driven decisions. Yet the rules by which evidence is evaluated can bias these decisions, even when the method of decision-making seems objective. Our Chief Scientific Officer, Dr. Yannis Jemiai, has worked extensively on how to operationalize decision theoretic tools for clinical development decision-making. Here he introduces three quantitative frameworks that life-sciences decision-makers can quickly incorporate into their selection process when selecting an optimal design for their next clinical trial.
In the last few years, there has been a growing interest in historical borrowing or augmented trials. There is an increasing level of comfort in using these methodologies even in confirmatory trials setting. The key challenge in borrowing external information is the selection of appropriate historical studies or external data sources. There are benefits to historical borrowing but also potential risks (for example, Type I error and power can be impacted by the drift).
However, despite the risks, several projects submitted to the FDA’s Complex Innovative Designs (CID) initiative aim at using historical controls in Phase III studies. Many data-sharing initiatives such as, TransCelerate, Project Datasphere and others, are all working towards making clinical trial data available for repurposing and reuse across the industry. There are also several working groups such as, the European EFSPI/PSI Historical Data Special Interest Group and DIA Bayesian Working Group who are interested in this area. This blog aims to introduce the concepts of evidence synthesis and Bayesian dynamic borrowing.
The COVID-19 Pandemic prompted the rapid surge in the generation of clinical data that has been scattered across multiple platforms, making it challenging to measure comparative treatment effects across trials. Last year, Cytel launched a COVID-19 Trial Tracker, an Open Access tool to track the global response to the pandemic. We talk to Louis Dron, Director - Real World Analytics at Cytel, about the evolution of Cytel’s Trial Tracker and the vision for its future developments.
In recent times, Single arm trials are being increasingly used to assess new treatment interventions. They establish clinical benefit by demonstrating the effects of a new therapy or treatment, without the need to use placebo or standard of care as a control. Instead, an alternative approach known as external controls or synthetic control arms (SCA) are being used that leverages real world data and historical datasets. Technical knowledge of Bayesian methods is key to being able to design and implement such trials.
Breakthrough treatments in oncology and rare diseases are now commonly approved based on a pivotal single arm trial – however this is not always optimal. Use of single arm trials in oncology or rare diseases requires appropriate comparisons to be developed to document the benefits of the new treatment. Deriving such comparisons from real world or historical trial data is not straightforward and requires data source and methods expertise.
Wearables-based Clinical Trials: The biostats and clinical overview of a growing clinical development strategy
The past two years have witnessed a heightened interest in the use of wearables in clinical development. The unexpected changes to the industry ushered in by the COVID-19 pandemic has highlighted the need for remote monitoring and patient-centric outcomes and accelerated the changes in the trials conduct.
Below we identify six elements critical to integrating wearables into your clinical development program.
New Meta-Analysis in JAMA Uses Novel Quantitative Techniques to Demonstrate Baseline Characteristics Informing Response to Common Therapy for Kidney Cancer
Recent years have witnessed improving survival outcomes for those struggling with a range of common kidney cancers. Scientists at Cytel recently published findings aiming to identify those baseline factors which influence a positive response to an established therapy. Such an investigation is critical to ensure that future treatment is informed by biomarker driven strategy.
The past decade has witnessed the rise of simulations-based clinical trial optimization in a manner unimaginable to most only a few years ago. Such optimization has become an integral aspect of strategic clinical trial design. The initial techniques of operationalizing Monte Carlo methods within a study design setting have increased and transformed in the landscape of cloud-powered computing. Nowadays, technology can produce innumerable simulations within a short space of time. Cytel’s Solara, for example, recently ran 1.5 million simulations within a fifteen minute period to identify trial designs optimized over speed, trial cost and probability of success. Why is it then, that some trial sponsors still struggle to make use of such simulations?
As the use of master protocols becomes more prevalent in drug development, Bayesian methods are extensively used to ensure optimal use of data and flexible trial designs.
Master protocols are used for umbrella trials, basket trials and other clinical trial designs that enable multiple therapies to be tested at once. They provide the rules for adding and dropping arms on clinical trials where standards of care might constantly be changing, thus requiring special tools for updating comparator arms, adding new therapies and so forth.
Cytel’s COVID-19 Trial Tracker continues to provide real time updates to the status of COVID-19 clinical trials worldwide. Funded by the Gates Foundation, the COVID-19 Trial Tracker uses machine learning technology to ensure that registries across the world feed into the Trial Tracker.
Historically, advances in the statistical design of clinical trials have accompanied progress within the science and practice of computation. The early 1990s witnessed increased exploration of adaptive and group sequential methods, in no small part due to the enhanced calculations made possible by software that had been developed a decade prior. The similar expanse of designs and methods throughout the past two decades, and the novel departures from the traditional two-arm design, have come with the ability to quickly compute more intricate and complex algorithms. By the beginning of the 2010s, the alignment of biostatistics and computation had grown close enough for educators and academics to begin advocating that biostatisticians needed to be well-grounded in computational reasoning, to equip themselves for unchartered terrains of drug discovery .
The Christmas break presented an opportunity to make my first concrete steps into the CDISC Library. Overall, it was a pleasant “promenade”.
The CDISC Library forms the foundation of an ongoing transformation in the way we will access and make use of the CDISC standards to facilitate the long awaited and desired, end-to-end data process implementation (see also the CDISC 360 project).
With the availability of the CIDSC Library, vendors can now develop software which you can use to instantly access standards i.e., Standards Controlled Terminology or data standards (for example SDTM). Standards are now available in machine readable and non-proprietary format.
Bayesian models offer a flexible way of incorporating historical controls in the analysis of trial data (whether single arm and randomized), and with increased access to the necessary computational power, they are transforming today’s clinical research. In a recently published article, Cytel’s scientific community members review the main Bayesian methods used in clinical trial design. Continue reading this blog for a brief overview.
COVID-19 has transformed the pharmaceutical industry in a manner that few could have predicted only a year ago. One of the potential effects of these changes is the more strategic use of real world evidence to support evidence generation for regulatory approval of clinical trials.
Dr. Radek Wasiak, Chief Data Officer at Cytel and Sreeram V Ramagopalan, Roche, recently co-authored a publication in the Journal of Comparative Effectiveness Research (JCER) on this likely development. The mix of delayed trials, missing data, and other challenges to traditional statistical design has meant that new tactics need to be deployed to salvage otherwise critical trials.
Outlining the true potential of RWE made Dr. Wasiak’s article one of JCER’s top ten most widely read in 2020.
One of the most difficult challenges facing Research and Development teams involves determining how to make tradeoffs between the speed, savings and success of a clinical trial. While some sponsors have to forego improved power in order to remain within strict resource limits, others sometimes increase their clinical development budget to accommodate unexpected gains in statistical power.
Complicating the picture is the fact that different members of an R&D team might have differing values that they place on speed, savings and success. While all three of these parameters affect the expected revenue from a trial (sometimes called the expected net present value or eNPV), we often find some members of the R&D team more concerned about completion dates, and others about investments in clinical operations, and so forth.
As we enter 2021 with new COVID-19 vaccines and greater optimism about the pipeline of drugs and devices positioned for approval, there remains the question of how this global pandemic has left permanent changes to clinical research and development. We know for example, that more clinical trials have become virtual and that decentralization is going to be a new challenge for clinical data management. Questions about equity and access have also arisen, with new ideas about how the pharmaceutical industry can contribute to greater equality. New quantitative models have also played an important role in expedited data analyses for prediction.
Effective use of the right outsourcing solution can enable sponsors to respond to market needs and change course where necessary, while ensuring a pool of highly qualified personnel are available to work on clinical trial projects. Whether you are a global pharmaceutical company or a virtual biotech, you deserve the dedicated and experienced A-team that can ensure that your projects are executed accurately, on-time and on-budget.
In this blog, we share a Cytel success story to explain how to create a high-quality, globally distributed biometrics team: minimizing recruitment timelines by up to 50% and expanding the team itself by 40% over a two year period
The rapid pace of technology has opened up numerous avenues for advanced innovative clinical trial design, but how can we use this to propel clinical development goals like maximizing revenue, or ensuring a commercially viable product? When operational constraints are limiting, how do we achieve the best possible trial design? What should we do if a competitor is edging us out of the market?
While we know that the statistical design of clinical trials can shorten trials or set realistic enrollment goals, there is still a growing need to tie these features of trial design directly to commercial revenue. Clinical development teams would ideally know how much they are willing to spend for an incremental gain in statistical power, or the marginal financial gains in waiting a week to unblind data.
The good news is the industry is getting there. Here are 5 Questions to help you begin your journey towards the Re-imagined Clinical Trial:
In April 2020, Cytel launched an open-access global COVID-19 Clinical Trial Tracker to help facilitate greater collaboration between researchers, policymakers, clinicians, journalists, philanthropists, and other critical stakeholders. Funded in part by The Bill and Melinda Gates Foundation, a leader in global health solutions, this live dashboard offers an overview of all the clinical trials taking place in the international effort to tackle the pandemic.
We have been posting regular updates on the clinical development of COVID-19 therapy and vaccines, on Cytel’s Blog page. The following details are based on an updated data search accessed on January 11.
At Cytel, we have been diligently working to become an organization deeply committed to uplifting and enriching society. The core purpose of our business is to help our clients in their endeavor to improve human health. Our employees are committed to upholding the highest standards in our interactions with customers, our colleagues and the communities in which we live and work.
Each year, we have several sustainable programs planned around providing education in healthcare and statistics. However, this year with the pandemic disrupting the socio-economic circumstances of the whole world, we were quick to implement new drives to support the fight against COVID-19.
2020 has been an unusually difficult year as the global pandemic impacted all of our lives. This year, the Cytel blog saw a lot of activity as we tried to keep our readers abreast with the latest updates on the COVID-19 clinical trials, and covered other trending and important topics such as, the growing adoption of Synthetic Control Arms, master protocols, Head to Head Comparisons and Bayesian methods. We also collaborated with several experts from both within and outside the company to conduct several series of webinars and provided summaries through our blogs.
Continue reading to learn about the top 10 Cytel blogs that resonated most with our community in 2020.
Can I submit software programs other than SAS? What software programs should I submit? Are sponsors required to submit executable programs?
Do I need to rename my software programs so that they all have the same extension e.g. “.txt”?
Can I make use of macros in my software programs and if so, should macros be part of the submission package?
What kind of documentations for software programs should I include in the submission package?
Do I need to follow any particular style and conventions when writing software programs that will be part of a submission package?
A single topic generates so many questions! Get the answers in this blog.
As Chief Scientific Officer, Dr. Yannis Jemiai plays a pivotal role in maintaining Cytel’s well-established reputation for statistical excellence and our track-record of bringing innovative analytic approaches to the development of medicines for human health. In this blog, we ask Yannis for his favorite Cytel events from 2020.
As we prepare to close the door on 2020, we asked Pantelis Vlachos, Principal/Strategic Consultant for Cytel, to share his favorite Cytel events of this year. Continue reading this blog for a summary of Cytel’s 2020 contributions around adaptive designs and Bayesian methods.
When designing clinical trials, biostatisticians and clinical development teams are often faced with a conundrum. Given the parameters of their clinical study, they usually begin with five or six possible design options and begin to explore the most promising ones. The likelihood is that none of these trials will be optimal designs. Rather, they meet certain criteria that are “good enough” at which point, clinical development teams might begin to lead one way or another.
Sachin Sobale began his career with Cytel as a young statistician. He has been associated with the company for more than 13 years and is now based in the US. In this blog we talk to Sachin about his journey so far, his current role, and achievements; and we get some tips from him for young statisticians who are interested in pursuing a career in this field.
As a part of Cytel’s Advanced Design Framework, a new Framework for the statistical design of clinical trials, Cytel discovered that a specific combination of process changes and technological advances has the potential to increase clinical development productivity by 10-20%. The Framework summarizes these as Thoroughly Explore, Decide Together and Communicate Tradeoffs. Here are 7 key features of this improved strategic framework. Alternatively, watch the webinar of our Chief Scientific Officer Yannis Jemiai discussing this Advanced Design Framework.
The Cytel COVID-19 Trial Tracker brings you an up to the minute, real time dashboard about COVID-19 trials around the world. This snapshot gives you a quick briefing on the current state of COVID-19 therapy and vaccines development.
Increasing Clinical Development Productivity Using Statistics and Cloud-Computing
The need for Re-imagining Clinical Trials: A recent survey conducted by Cytel found that only 42% of respondents reported using any complex or innovative clinical trial designs beyond the familiar group sequential approach. Although regulators respond quite favorably to such designs, sponsors have remained hesitant to use them.
A combination of technological and process advances are necessary to overcome mechanisms that contribute to stagnating statistical innovation in clinical development. Cytel responded by creating this new whitepaper that provides a new strategic framework that can help Clinical Development teams leverage cloud-computing and begin to initiate process changes, necessary to increase development productivity by 10-20%.
Significant advances have been made to enhance the efficiency of clinical trial designs. However, the traditional methods deployed by many pharmaceutical companies are fraught with challenges. Much less consideration is given to the value of decisions in the context of development programs or portfolios.
Cytel recently launched the “C-Suite Webinar Series”, an online initiative to help pharmaceutical executives drive commercial success with strategic insight from statistics. As a part of this series, Zoran Antonijevic, Head of Biometrics at MedSource, conducted a webinar where he describes methods for maximizing the value of programs and portfolios. This event was attended by numerous biopharma leaders.
Continue reading this blog to understand the concepts of program and portfolio optimization and learn about the benefits and opportunities presented by them.
An extraordinary amount of global research is underway as the COVID-19 pandemic continues to evolve and spread. As several entities develop curative and preventive responses against COVID-19, alignment with regulatory recommendations is key for developing effective and safe intervention. Moreover, fast regulatory approval will translate into early availability of interventions to address unmet needs.
Continue reading to get an overview of the registered COVID-19 clinical trials landscape, with a story on the special attention received by Hydroxychloroquine treatment.
Virtual ISPOR 2020, held November 16 to 19, presented new opportunities for scientific interaction amongst HEOR community. Cytel and Ingress Health, now a Cytel company, contributed to a range of events including interactive workshops, issue panels, on demand podium presentations and virtual poster presentations.
Continue reading for discussions on tracking COVID-19 trials, reflecting on the successes, opportunities and failures of real world solutions, and bridging the gap between real world data and clinical development.
The Virtual PHUSE-EU CONNECT Conference was held from November 8 to 13 and the event was a great success, despite all of us missing the face-to-face contact.
The conference kicked-off on Sunday night with a Social Virtual event with a “Numerologist Show”. Of course this could not replace and compete with the usual “toast” we were used to do live, so we did it virtually (check out my LinkedIn post where I offer some cocktails recommendations and share the recipe of my favorite cocktail “The Negroni” with a bit of history. But please don’t do it before Friday night, you will need the weekend to recover).
Like every year, Cytel significantly contributed to the event as one of the official sponsors, running a workshop (“Predictive Analytics Using R”), chairing and co-chairing two streams (Machine Learning & Connected Health and Scripts and Macros), preparing four on demand presentations (in Application and Development, Coding and Tricks and Data Standards and Governance streams) and two posters.
In this blog, I focus on presentations related to data standards and data submission to agency, in general.
Data Monitoring Committees (DMCs) are groups of independent experts who periodically receive (by-arm) reports created by an independent Statistical Data Analysis Center (SDAC) using interim data from ongoing studies. The role of the DMC is to make recommendations about the continuation of the studies based on their best judgment and sometimes specified guidelines.
The DMC typically includes at least one statistician who votes on the decision to recommend stopping, modifying, or continuing a study. The SDAC typically is represented by at least one independent statistician and these statisticians are intermediaries between the sponsor and the DMC. The SDAC independent statisticians facilitate the efforts of the DMC by preparing and presenting summary data, taking care of meeting logistics, etc. These SDAC statisticians need ‘hard skills’ such as expertise in biostatistics, experience with clinical trial data, and knowledge of the study protocol. But it is essential that these SDAC statisticians also have the ‘soft skills’ for this role. In this blog, we highlight 10 key qualifications for these SDAC independent statisticians that are less technical, but no less essential.
The current state of the clinical trials industry faces a challenge that was only hypothetical three or four years ago. Thanks to the advent of cloud-computing and advances in simulation technology, sponsors can now design hundreds of thousands of clinical trials in less than an hour. Yet how do we choose amongst all of these myriad options in a way that optimizes commercial prospects? Cytel’s Chief Scientific Officer sits down with us to discuss the Re-imagined Clinical Trial.
As a part of Cytel’s "New Horizons Webinar Series", Alind Gupta, Senior Data Scientist, presents case studies from his research on applying machine learning for predictive analysis and evidence generation.
The biopharmaceutical and healthcare industries now collect more data than ever before due to advances in the variety of information sources combined with the ability to store vast quantities of diverse data. Sophisticated machine learning (ML) and AI techniques allow us to access and analyze any combination of a multitude of data sources. The way that traditional controlled sources are viewed is being adapted in light of new evidence that emerges from real-world data. In his presentation, Alind introduces us to the concept of ML and Causal Inference and discusses case studies from randomized clinical trials and real-world data.
Click the button to register for the on demand webinar.
MUCE is a Bayesian solution for cohort expansion trials where multiple dose(s) and multiple indication(s) are tested in parallel. Such methods are particularly important for areas like oncology where several doses and several indications must be tested for successful completion of early phase trials, and optimal choice of dose and population to move on from early phase to a reasonable dosage for Phase 3.
Note that for these situations the number of comparator arms for a trial can increase rather rapidly. Testing three doses with three indications essentially requires 9 different trials. An efficient way to test a higher number of trials is therefore necessary for accelerated clinical development.
Cytel and Ingress Health (now a Cytel company) will be contributing to a range of events at Virtual ISPOR EUROPE 2020, on November 16th – November 19th. Our Real-World analytics teams will be collaborating to deliver a number of interactive workshops, issue panels, posters and podiums to showcase their work and share innovative insights in HEOR, evidence generation, knowledge synthesis and decision analysis.
Click below to download our full list of sessions at ISPOR EUROPE and feel free to share this brochure with any colleagues who may find our sessions insightful.
The widespread use of cloud-computing has altered the clinical trial design process. Whereas three or four years ago, it would take a statistician perhaps two or three days to design five clinical trial designs, a well-resourced statistician can now simulate and model well over 100,000 designs in less than 30 minutes. How does this affect the process of designing clinical trials
According to Yannis Jemiai, Chief Scientific Officer at Cytel, a combination of technology and process changes can establish the foundation for significant increases in productivity. Yannis argues that uncertainty should not be viewed as a challenge but an opportunity. Using statisticians strategically as well as tactically throughout the design process can help R&D teams drive commercial value for greater speed, savings and success.
Platform trials are a new type of clinical trials where multiple interventions can be evaluated simultaneously against a common control group within a single master protocol. Platform trial designs are an extension of adaptive trial designs that are sometimes referred to as a multi-arm, multi-stage (MAMS) design, as multiple interventions (‘‘multi-arm’’) undergoing multiple interim evaluations (‘‘multi-stage’’) are part of the design features.
This autumn Cytel has been holding a number of webinars on Platform Trials, ranging from a discussion with Cyrus Mehta on statistical innovations to incentivize more sponsors to consider platform trials, to next week's event with Jason Connor (Confluence) on the use of Bayesian methods for these innovative trial designs.
In a recent webinar Jay Park, Director of Trials Research for Cytel in Canada, presented a webinar to review the concept of platform trials and discuss important design considerations for platform trials. Jay is the author of several leading papers on Platform Trials, including one in CA: A Cancer Journal for Clinicians, the journal with the world's highest impact factor. He has also produced a complimentary primer on the subject which you can download here.
Continue reading this blog to get a summary of his talk. Click the button to access the on demand webinar.
As the evolving COVID-19 pandemic continues, the Cytel COVID-19 Trial Tracker continues to bring you an up to the minute, real time dashboard about COVID-19 trials around the world. In this blog, we bring you the updates from this week.
In oncology, many manufacturers go into niche indications, where there are very specific tumors, and then they opt for a single arm trial. This potentially works for regulatory purposes (EMA/FDA). However, if they go to the local HTA authorities (NICE/CADTH), they will have to answer the question on the relative effectiveness of the new product compared to the standard of care in that country, and then its cost-effectiveness. Hence, typically, a manufacturer will identify a publication on a trial or real-world evidence on standard of care, or perhaps collect individual patient level data in clinical practice. Subsequently, it will conduct comparative effectiveness analyses for HTA purposes, a naïve comparison or an unanchored MAIC/STC/PSM of the single arm trial compared with the control arm.
Cytel Introduces Advanced Design Framework: Part 3 - Communication Techniques to Ensure Alignment on Data-Driven Clinical Trial Designs
Cytel has recently revealed its Advanced Design Framework, a method developed by Cytel’s thought leaders that draws on decades of experience increasing clinical development productivity. The Framework illustrates how advances in design processes and technology can help development teams deliver greater business results, unifying statistics and strategy in the era of cloud computing and making strategic use of well-resourced statisticians.
When an expert statistician is paired with an experienced set of data managers, opportunities to capitalize on quantitative strategy are spotted more quickly. Statisticians can determine whether datasets can strengthen study findings by being presented in a way that uses the available data in a scientifically objective way that is at the same time in line with the clients’ strategic objectives.
The practice of combining statistical needs with the processes of data management and other related services for real world evidence, we will henceforth call RWE-Delivery. There are several models for RWE-delivery that can similarly vary with the needs of a study. Questions about process, management and timelines are just as key for this choice of delivery model, as the objectives of the delivery. Therefore, it is important to work closely with delivery teams to determine the possible needs for study completion.
Measuring treatment effect during a clinical trial is often the source of much debate, particularly during rare disease trials that must stimulate investigations using small samples. Unlike statistically significant results, for which there are many tests, meaningful measures of treatment effect are still under development (Kieser 2012). Cytel statistician Ursula Garczarek wonders whether this holds true in the realm of small samples and small target populations. After all, does the summary statistic in such a small trial rely on many assumptions that might not correlate with reality?
Cytel Introduces Advanced Design Framework: Part 2- The Need for A Quantitative Evaluation Approach for Deciding Together
Cytel has recently revealed its Advanced Design Framework, a method developed by Cytel’s thought leaders that draws on decades of experience increasing clinical development productivity. The Framework illustrates how advances in design processes and technology can help development teams deliver greater business results, unifying statistics and strategy in the era of cloud computing, and making strategic use of well-resourced statisticians.
The framework consists of three parts: Thoroughly Explore, Decide Together, and Communicate Trade-Offs. This week we take a deeper look into the second part of this Framework, revealing how to effectively incorporate varied perspectives to efficiently design innovative clinical trials. Opportunities for quantitative evaluation criteria and design without bias help R&D teams sift through the thousands of trial designs options to optimize for speed, success, and savings.
The Missing Link: Risking your Traceability (and “Credibility”) when your ADaM package is not traceable back to SDTM
About three years ago, Cytel was helping a sponsor on a project where I had to conduct surveillance of some CRO deliverables, mainly for SDTM and ADaM packages. At first, I was involved in the review cycle of SDTM, and began by reviewing some initial mapping specifications including a draft SDTM Annotated CRF. The CRO in charge was quite experienced and there was nothing major to spot in all the different versions I had to review.
Surprisingly, it was not the case some months later, when I had to provide the same review support for the Biostatistics deliverables, specific to the ADaM package. The ADaM datasets overall were well designed, and there were no major open non-conformance issues. However, it was clear from the very beginning that there was something missing - a missing link between SDTM and ADaM.
Cytel recently conducted a webinar on Bayesian Dose-finding Designs for Modern Drug Development, presented by Dr. Yuan Ji.
Dr. Ji is a Professor of Biostatistics at The University of Chicago and a well-known name in the industry. In his presentation, he introduces representative Bayesian designs for dose-finding trials. The webinar offers insights on topics including classical DLT-based dose-finding designs, designs with delayed toxicity using time-to-event endpoints, and designs for combination dose-finding trial. Watch the on demand webinar to see the illustration of Bayesian modeling and inference for dose-finding designs that utilize the concept of probability intervals and related methods for clinical development and decision making.
Pharmaceutical and biotech companies are under pressure to deliver more and deliver faster with fewer resources. The cost of drug development, failure rate and human cost associated with prolonged participation in a trial turn out to be steep in case of an ineffective trial. As the industry seeks new levels of clinical trial efficiency and probability of success, more companies are looking to use advanced, innovative and computationally intensive designs like Bayesian methods.
Bayesian methods are of growing interest to the drug development industry, as they allow clinical investigators to leverage historical trial data as well as learnings from new data as it accrues throughout a trial. The result is better-informed decision making, greater program flexibility, and the ability to run smaller, more resource-efficient trials.
Cytel’s New Horizons Webinar Series introduces you to the latest innovations in statistical trial design. This webinar from the series is presented by Dr. Yuan Ji, a consultant for Cytel. Yuan is the founder of Laiya Consulting and currently is the Professor of Biostatistics at The University of Chicago. In his presentation, Professor Ji introduces the U-Design version 1.4, which mainly consists of a new module of dose-finding trial designs with joint efficacy and toxicity outcomes.
Click the button to register for the next webinar in this series, presented by Cytel's Ursula Garczarek. Ursula will be presenting a case study on the value of detailed clinical trial simulations for rare diseases.
In this two-part blog series, we interview Bart Heeg, Vice President HEOR and Founder at Ingress Health (A Cytel company). Bart provides us insights on the trends in HEOR and explains why Bayesian methods are also important for Health Economics. Read Part 1 here.
Cytel Introduces Advanced Design Framework: Part 1 - Methods for Thorough Exploration of Design Space
Cytel has recently revealed its Advanced Design Framework, a method developed by Cytel’s thought-leaders after a decade of fine-tuning clinical development processes. The framework consists of three parts: Thoroughly Explore, Decide Together, and Communicate Trade-Offs.
The Framework demonstrates how to unify statistics and strategy in the era of cloud-computing, by making strategic use of well-resourced statisticians. This week, we take a deeper look into the first part of this Framework, revealing how to explore hundreds of thousands of designs available to sponsors, rapidly and in real-time, to improve the chances of identifying the design that optimizes for speed, success, and savings.
In this interview with Thomas Wilke, Principal Scientist at Ingress-Health (a Cytel company), we talk to him about his background and experience in Health Economics, understand the important considerations of real-world evidence studies and the impact of COVID-19 pandemic on the work of the health economics outcomes researchers who work at Ingress and Cytel. We also cover important HEOR topics such as its benefits for market access studies and real-world analytics (RWA) for regulatory submission.
Cytel and Ingress-Health will be contributing to a range of events at Virtual ISPOR EU 2020, on November 16th – November 19th. Our Real-World analytics teams will be collaborating to deliver a number of interactive workshops, issue panels, posters and podiums to showcase their work and share innovative insights in HEOR, evidence generation, knowledge synthesis and decision analysis.
Click below to download our full list of sessions at ISPOR EU
Upcoming Discussions: The Uniqueness of COVID-19 Real-World Data Challenges & The COVID-19 trial tracker
COVID-19 has created extreme uncertainties -- a dearth of historical information combined with the need for safety, statistical rigor, and speed has prompted the rapid surge in the generation of clinical data. However, this information is scattered across multiple platforms, making it challenging to measure comparative treatment effects across trials. Consequently, we are seeing a high frequency of failures, that diminishes the public’s confidence in research and slows the path from scientific results to action.
For over a decade, advanced trial design techniques have promised efficient trials with accelerated timelines, reflecting the ability to quantify uncertainty and de-risk trials using adaptive tools. Despite the emergence of these complex innovative designs, the success of Phase 3 trials has continued to hover at 33% while the average time to market remains about 6 years.
A credible evidence base is needed to support and document the economic value of new technologies and therapeutic approaches. Companies need careful cost-effectiveness analyses for successful reimbursement submissions. In this two-part blog series, we interview Bart Heeg, Vice President HEOR and Founder at Ingress Health (A Cytel company). Bart talks about his background in HEOR, founding Ingress Health and its recent acquisition by Cytel. He also talks about the benefits of turning to an HEOR specialist and provides a sneak peek into Cytel’s presentations at the upcoming ISPOR EU 2020 event.
The combination of greater access to electronic health records, bigger electronic claims datasets, and the need for more clinical insight in ensuring patient safety, has made observational studies an important new tool in trial design. Observational studies typically take non-randomized data from outside of a trial and use quantitative and modeling techniques to draw conclusions from big datasets. While typically used for HEOR and market access, augmenting regulatory submissions with observational studies is gaining prominence. As with all data analyses, there is an implicit rule of ‘garbage in-garbage out,’ where data that is not up to the standard required for the formation of sound scientific judgment, should not be used. Sponsors should rely on the most sophisticated tools and advanced analytics to make the most rigorous use of available data.
Cytel and Novartis are together hosting a complimentary Bayesian Virtual Symposium and an Interactive 7-part workshop. This series will expose you to cutting edge topics from industry renowned leaders in Bayesian statistics. The introductory webinar “Bayesian Statistics and FDA Regulatory Acceptability” is presented by Greg Campbell, PhD, Former Director of Biostatistics, U.S. Food and Drug Administration.
In the United States Bayesian statistics has been used in regulatory submissions to the Food and Drug Administration (FDA) for confirmatory clinical trials medical devices for more than fifteen years. In this webinar, Dr. Campbell reviews the Bayesian history and accomplishments for medical devices. He talks about the status and opportunities of Bayesian statistics for pharmaceutical drugs and biologicals. We also learn about the challenges and the future of Bayesian statistics in the regulatory environment. You can access the on demand webinar and register for the rest of the series by clicking the button.
Even before the era of COVID-19, significant attention was channeled to the overwhelming potential of adaptive MAMS designs. Short for multi-arm multi-stage designs, these trials enable numerous therapies to be tested on a single platform with a single comparator arm. When patients are too few or there are several therapies in competition with each other to enroll, adaptive MAMS designs expedite the discovery of new drugs.
With the rise in digital technologies, there has been an explosion in the volume and type of data sources. We can obtain information about individual health from social media data and mobile apps, to wearable sensors and electronic health records. Corporations and governments even use insurance claims data as sources of data for analyses.
This data could yield a more robust and complete picture of diseases, the patient journey, and the effectiveness of interventions in the real world. This in turn is often used by life sciences leaders to make better drug development, reimbursement, and clinical decisions. However, apart from accessing and curating this data, we also need to harness advanced analytical techniques to generate evidence, including the sophisticated use of statistical methods. The RWE data sciences team therefore must be chosen carefully to take on the challenges of these novel uses of data.
The delivery of RWE-analyses requires more than simply statistical knowledge. The variety of RWE methodologies reflect the range of opportunities sponsors have, to cast their assets in the best light. In this blog we outline the RWE design and staffing needs of a specific kind of observational study, namely natural history studies, as regulators are increasing demand for these explanatory assessments of the biochemistry of disease progression.
Staying abreast of the rapid pace of clinical development means adopting innovative or computationally intensive designs like Bayesian methods. These methods allow for the incorporation of prior knowledge, in terms of either expert opinion from clinicians or historical data, in statistical inference. Thus, they have the additional advantage of being able to work with real-world data (generally, real-world data has a lot of missing data) without the need to impute missing values. These kinds of models are also flexible enough to work with temporal data. This helps ease the reliance on large sample approximations that are often required for frequentist methods and generally results in greater efficiency in study design.
In this edition of The Informative Bayesian by Pantelis Vlachos, we learn about information borrowing to form a prior distribution. In a Bayesian framework, borrowing from historical data is equivalent to considering informative priors. These priors can be derived as meta-analytic predictive (MAP) priors or using patient-level data.
Methods involving Group Sequential Designs is one of the earliest deviations from a traditional two-arm clinical trial with no interim looks at the data. They add incredible value to trials through their abilities to safeguard patients, reach positive conclusions early and keep trial designs simple and streamlined.
Sequential trials also help reduce costs and the number of patients involved, but finding a positive conclusion earlier is quite important too. In the drug development process, where patent lifetime is limited, reaching a decision six months or a year earlier is a big advantage. Sample Size Re-estimation is another key tool in the modern trial designer’s toolkit that proves to be useful. Continue reading this blog to learn how to use these methods and understand how they can improve trial design.
Today, there is a need for advanced quantitative techniques to combine all available information for better decision making in health care. Bayesian statistics allow us to make probabilistic inferences on the parameter of interest, which is missing in a traditional frequentist approach. Apart from the philosophical issues, Bayesian analysis provides a practical and intuitive tool for interpretation of study results and risk evaluation of clinical hypotheses.
Cytel and Novartis are together hosting a complimentary Bayesian Virtual Symposium and an Interactive 7-part workshop. This series will expose you to cutting edge topics from industry renowned leaders in Bayesian statistics. Click the button to learn more and register.
Innovation in trial designs are offering new routes forward for organizations of any size. They are now also aligned with the overarching goals of improved clinical development, better pre-planning, greater patient safety, less medical waste, and/or increased knowledge.
Cytel is hosting "New Horizons Webinar Series" that will introduce biostatisticians to the latest innovations in statistical trial design. The first webinar in the series on Adaptive Multi-arm Multi-stage Clinical Trials is going to be presented by Cytel's President & Co-Founder, Cyrus Mehta. Click on the button to register.
TOGETHER trials, and the advantages of adaptive platform designs for investigating COVID-19 therapies
Cytel has recently designed and implemented the TOGETHER Trials, funded by the Bill & Melinda Gates Foundation to generate knowledge to help fight COVID-19, particularly in low and middle-income countries. The trials, with sites in Brazil and South Africa, test three existing interventions as possible treatments for COVID-19 in high-risk adults who do not require hospitalization, compared to a placebo.
The TOGETHER trials use an adaptive platform design. This type of design is particularly useful for contexts such as COVID-19 response, where there are many unknowns and a need for accelerated and resource-efficient answers, for 5 reasons.
Regulators in both the United States and Europe have responded positively to the use of synthetic control arms (SCA)s in clinical development. The desire to speed up and lower the cost of drug development, coupled with increased availability of rich real-world data, contributed to the increased willingness towards using SCAs as supplementary evidence to accompany regulatory submissions using single arm trial data only.
As with any sophisticated statistical method, deciding on the optimal SCA approach is a necessary condition to ensure robustness of findings. Cytel’s new audiobook "Demystifying synthetic control arms", explains the concept of synthetic controls and offers insights on some common quantitative strategies for trial design and regulatory submission. Continue reading this blog to learn more and get access to the audiobook.
Research Scientists, Thomas Wilke and Sabrina Mueller recently published a manuscript on “Diabetes-Related Effectiveness and Cost of Liraglutide or Insulin in German Patients with Type 2 Diabetes: A 5-Year Retrospective Claims Analysis”.
As insulin and liraglutide are both treatment options for type 2 diabetes mellitus (T2DM), it was important to understand their long-term real-world outcomes. A retrospective study was conducted using administrative claims from a German health fund (AOK PLUS) and clinical data; the clinical data was collected in a disease management program. This claims data analysis, in adult patients with T2DM, investigated diabetes-related effectiveness and costs with long-term (up to five years) treatment with liraglutide or any insulin, in a real-world setting.
Continue reading this blog to learn about the unique insights that were gained during this project and get access to the publication.
The TOGETHER Trial: Cytel Designs and Implements Novel Adaptive Platform Trial for COVID-19 Therapies
Cytel has designed and implemented a novel adaptive platform trial for early stage COVID-19. The severity of the coronavirus emerges in five stages, with the majority of clinical trials focusing on therapies for the final stage of the disease. According to the Cytel Clinical Trial Tracker, only 6 of 2000 trials are focused on early stages; staggering given that only 5% of coronavirus cases are considered severe.
Keeping up with the rapid pace of clinical development means that we need to adopt the innovative or computationally intensive designs like Bayesian methods. Yet, cutting edge technology can sometimes be difficult to assess or can introduce risk. Cytel’s new web-native extension of East, East AlloyTM, makes it practical and sustainable to adopt innovative and computationally intensive designs. Continue reading this blog to learn more.
Synthetic control arms (SCA) are virtual trial arms that use historical claims data and observational data to simulate the control arm of a study. When enrollment targets are low and large amounts of data already exist about the performance of a control, then in many cases using quantitative techniques to simulate a control arm of a trial will expedite timelines and serve as a more optimal use of resources.
Cytel’s new audiobook "Demystifying synthetic control arms", provides insights on synthetic controls, suitable conditions for their use, and some common quantitative strategies for trial design and regulatory submission. Click the button download the audiobook.
In clinical trials with small or sparse data, statistical methods meant for large sample sizes may not be helpful to get an accurate interpretation of data. This is where computationally challenging exact methods often come into play. Chris Corcoran, David B. Haight Professor of Analytics in the Huntsman School of Business, is presenting at a Cytel webinar where he will introduce some basic exact statistical procedures provided in Cytel’s StatXact®. The software offers more than 160 tests and procedures for exact inference and power analysis.
Join Chris Corcoran in this example-based discussion where he will illustrate why exact analysis can be crucial in providing accurate results in some very common settings, particularly those involving small or sparse samples. Click on the button to register for the webinar.
“A good start is half the battle” (the Before) when submitting data to the FDA and there are a couple of cherries to put on top (the After) when your regulatory group has finally submitted the eCTD to the FDA . A good start is to have early discussions with the agency by regularly meeting them and sharing the status of your clinical data standards. While, the cherry on the top is the continuous support you need to guarantee to your submission project to promptly react when the reviewers come back with questions and additional requests during the review process.
Single arm trials are emerging as an accepted way of assessing a new treatment intervention. They establish clinical benefit by demonstrating the positive effects of a new therapy or treatment, without the need to use placebo or standard of care as a control. Instead, alternative approaches of establishing the comparison are used; these have become known as external controls or synthetic control arms (SCA) and include approaches leveraging real world data from various sources or evaluations of historical clinical trial data.
Is your Trial a Candidate for a Synthetic Control Arm? Continue reading this blog to learn more.
Cytel’s co-founder, Nitin Patel, conducted a webinar on designing clinical trials from a program-level perspective. His presentation helps us understand the value of designing clinical trials considering downstream consequences. Watch the on demand webinar to get insights on the role of simulation in optimizing clinical trials' performance from a program perspective and understanding the hybrid Bayesian-frequentist approach to clinical trial design.
We also had the opportunity to interview Nitin about his journey since he co-founded Cytel and got his views on implementing a program-wide strategy for pharma and biotech companies. Read the blog here.
Continue reading this blog for key highlights from the webinar.
Cytel Co-Founder Cyrus Mehta Presents at the Heart Failure Collaboratory, a Public-Private Partnership with FDA
On Friday September 11, Cyrus Mehta, co-founder of Cytel, will be delivering a talk to the Heart Failure Collaboratory, on how adaptive designs can be utilized to salvage trials disrupted by COVID-19. The Heart Failure Collaboratory is a public-private consortium with FDA, and will be hosting a day long symposium online, on the application of innovative methods for drug and device studies in the age of COVID-19.
In this blog, Cytel's SVP Corey Dunham’s talks about our Functional Services teams and the qualities we seek in new hires. As our FSP division continues to grow, we are looking to hire programmers and biostatisticians. Cytel's recruitment and FSP teams are hosting a one hour long Virtual Careers Open Day on Thursday, September 10th at 11:00AM EDT. Join us to learn more about our expanding FSP team, open career opportunities and what it means to be part of Cytel. Click on the button to register for the virtual event.
Pantelis Vlachos, Principal, Strategic Consultant at Cytel, conducted a webinar to introduce the capabilities of East AlloyTM. East Alloy is a new East environment that enables rapid access to innovation with the trust and support you have come to expect from Cytel. The cloud-native software makes it practical to apply computationally intensive Bayesian methods. Download the brochure to learn more.
This blog is a part of the new blog series on technology and Bayesian decision-making by Pantelis. Continue reading to learn about the methods and capabilities, such as, Bayesian meta-analytic priors, Bayesian MAMS, adaptive dose-finding and others, available to all East Alloy users.
As Chief Scientific Officer, Dr. Yannis Jemiai plays a pivotal role in maintaining Cytel’s well-established reputation for statistical excellence and our track-record of bringing innovative analytic approaches to the development of medicines for human health. With oversight for the corporate-level Scientific Agenda, Yannis ensures Cytel continues to be known for thought leadership in adaptive designs while expanding its reputation in Bayesian statistics, Complex innovative designs, and the use of Real-World analytics for regulatory and post-approval purposes. Yannis’ research interests include adaptive trial design, causal inference, decision theory, and regulatory affairs.
In this blog we talk to Yannis about his long-standing association with Cytel, his views on adaptive designs and their future; and we get some tips from him for young statisticians, programmers and those interested in pursuing a career in this field.
It is important to take a strategic approach to clinical development in order to minimize the potential for Phase 3 attrition. In our next webinar from the ‘Introduction to Complex Innovative Trial Design’ webinar series, Nitin Patel, co-founder of Cytel, will provide an overview of the concepts of program optimization. As a case study, we will describe a Phase 2 trial design based on program-level optimization. We utilize a hybrid Bayesian-frequentist framework to evaluate the impact of Phase 2 design choices on the probability of Phase 3 success, clinical utility, time to market, trial costs and expected net present value (ENPV) of the product. These factors include Phase 2 sample size, dose selection and go-no go decision rules for Phase 3, and Phase 3 sample size.
Click the button to register for the webinar on August 26, 2020.
In this blog, we talk to Nitin about his journey since co-founding Cytel; and gain insights on program optimization, the challenges for both big and small pharmaceutical/biotech companies, and how to go about the planning process.
As uses of real world data become more familiar for trial design and regulatory submission, sponsors might become more interested in techniques related to Bayesian borrowing. Sophisticated uses of this technique have been applied to COVID-19 vaccines development and complex oncology trials. Simpler versions can be used to optimize across existing datasets, design trials with lower enrollment targets, accelerate the time to regulatory submission, and strengthen the power of a trial. Here we provide an overview of the potential benefits.
Bjoern Bornkamp, Statistical Methodologist at Novartis and Jose Pinheiro, Senior Director, Johnson & Johnson provided their insights on adaptive designs for dose finding in Cytel’s latest webinar. The webinar demonstrates how adaptive and Bayesian techniques can be implemented for optimal dose-finding.
This two-part blog series provides a summary of the webinar. Read the first part to get key highlights from the presentation by Jose Pinheiro on the need to conduct dose finding Phase 2 studies, dose selection comparisons and the use of MCP-Mod for dose finding.
Continue reading this second part to learn about the methods of adaptive dose-finding, presented by Bjoern. Click the button to access the webinar recording and download the presentation slides
Career Perspectives: Interview with Mrudula Joshi, Associate Director, Statistical Programming Services
Mrudula Joshi joined Cytel in July 2005 as a young SAS programmer. Last month, she celebrated her 15th year work anniversary at the company. In this blog we talk to Mrudula about her journey so far, her current role, and achievements; and we get some tips from her for young statisticians, programmers and those interested in pursuing a career in this field.
Cytel’s Biostatistics and Statistical Programming team for Functional Services provides integrated solutions, by blending the expertise of programming and the experience of statistics. As our FSP division continues to grow, we are looking to hire programmers and biostatisticians. Cytel's recruitment and FSP teams are hosting a one hour long Virtual Careers Open Day on Thursday, September 10th at 11:00 AM EDT. Join us to learn more about our expanding FSP team, open career opportunities and what it means to be part of Cytel. Click on the button to register for the virtual event.
Bjoern Bornkamp, Statistical Methodologist at Novartis and Jose Pinheiro, Senior Director, Johnson & Johnson provided their insights on adaptive designs for dose finding in Cytel’s latest webinar. Finding the right dose in Phase 2 gives a potential new therapy its best chance to demonstrate efficacy during Phase 3. A well-executed dose-ranging trial therefore has the potential to alter the course of the entire clinical development program. This webinar demonstrates how adaptive and Bayesian techniques can be implemented for optimal dose-finding.
This two-part blog series will provide a summary of the webinar. In this first part, get key highlights from the presentation by Jose Pinheiro on the need to conduct dose finding Phase 2 studies, dose selection comparisons and the use of MCP-Mod for dose finding. Click the button to access the webinar recording and download the presentation slides
Cytel’s Biostatistics and Statistical Programming team provides integrated solutions, by blending the expertise of programming and experience of statistics. Being a notable Functional Services Provider (FSP) in the industry, we take pride in supporting our clients as they navigate the intricacies of 21st century drug development. As our FSP division continues to grow, we are looking to hire programmers and biostatisticians. Cytel's recruitment and FSP teams are hosting a one hour long Virtual Careers Open Day on Thursday, September 10th at 11:00AM EDT. Join us to learn more about our expanding FSP team, open career opportunities and what it means to be part of Cytel. Click on the button to register for the virtual event.
Making the Most of Your Data II: Optimizing Clinical Information in Trial Design and Implementation Using Bayesian Methods
While there is increasing optimism about the discovery of a COVID-19 vaccine, one of the less talked about aspects of such vaccines development are the lessons that can be used in other therapeutic areas. After all, COVID-19 vaccines development has uncovered numerous ways to design and execute trials within shorter time-frames and with less data.
One theme that has emerged consistently is the need to optimize the use of clinical information available, an endeavor well-supported by Bayesian methods.
Making the Most of Your Observational Data: Creating a Synthetic Control from Your Natural History Study
Recently a biotech approached Cytel for support with a Phase 2 Study in oncology. Regulators had requested a natural history of disease study, which tracks disease progression in the absence of any form intervention. These studies are used to build disease-models that can then inform a range of development opportunities within a drug development program.
A March 2019 FDA Guidance highlighted the importance of such studies for rare diseases, with former FDA Director Scott Gottlieb acknowledging that a lack of knowledge about the natural history of certain diseases is a significant obstacle in rare disease drug development.
Head to Head Comparisons Using Real World Data – Design and Data Considerations from Cardiovascular Pilot Investigation
Cytel is conducting two pilot projects on head-to-head comparisons using real world data. These projects in oncology and cardiovascular will occur in real time and will take place across our latest webinar series on the topic. The aim of this series is to introduce our audience to head to head to comparison using Real World Data (RWD) while focusing on practical application and results from the pilot projects.
The second webinar from this series was held on July 28, 2020 and outlines the design of the cardiovascular pilot investigation. None of the existing randomized trials of recently developed second-line antihyperglycemic agents can provide adequate information on their comparative effectiveness and safety regarding cardiovascular outcomes. Conducting Target Trials to get information of interest would be costly, difficult to perform, and would take many years to complete. As a result, we need to use observational databases to emulate it. This blog provides a brief on the design of the cardiovascular pilot project. Our team of experts also discussed the data requirements and the data source to be used in the pilot investigation, with the primary challenge focusing on how to assess if data are sufficient for the purposes of trial emulation. Continue reading the blog for a summary of the webinar.
Get access to the webinar recording and download the slides by clicking the button.
Last year, Paul Terrill, Associate Principal of Strategic Consulting at Cytel, presented an engaging webinar on the topic of Estimands. The webinar covered a range of issues from what is an estimand to how to structure early discussions on estimands. On popular demand, Paul will re-run this webinar on August 13, 2020, and add recent developments on this topic. He will share the bottom-line on estimands and discuss their implications for a trial's objectives, design, data collection, statistical analyses and conclusions. Paul will also share his guidance on managing the communication about estimands between multiple internal stakeholders, gaining internal buy-in, and ensuring that a trial’s objectives, design, conduct, analysis and interpretation are in line with the addendum. Register today by clicking on the button.
A new peer-reviewed article co-authored by several Cytel scientists re-examines the way in which adaptive trials are designed and implemented within the oncology space. The wide ranging paper spans numerous topics including data considerations, statistical considerations, the commercial and scientific value of flexibility in adaptive designs, and also a “Holistic Approach” to program development, wherein development plans are not created study by study, but across phases.
CDISC standards have been around for a while with the first SDTM Standard version released in 2004. However, it was only in the last decade that it became “The Standard”, particularly when Health Authorities (HA), such as the US FDA and Japanese PMDA, made it a requirement for data submissions to support most of the regulatory requests for market approval. Additionally, most of the Pharma companies made the CDISC standards a part of their operational data model and consequently, the number of studies using the CDISC standards increased across phases of development.
The benefit of receiving data in standard formats was soon recognized by HA reviewers as they now require lesser time to understand the structure of the data they receive. Integration of data provided by different sponsors, for example on the same indication, for better understanding of safety signals, has become possible with data submitted in standard CDISC format.
However, the HAs such as the US FDA, soon realized that this was not enough, for two main reasons:
- sponsors sometimes make bad or different interpretations of the standard
- lack of standards or use cases in specific disease areas or indication
Cytel is conducting a webinar series on complex innovative trial designs. Dr. Thomas Burnett, Senior Research Associate in Medical and Pharmaceutical Statistics at Lancaster University, joined us as the presenter in the latest webinar from this series. In this webinar, “Adaptive Enrichment Designs in Clinical Development”, Dr. Burnett provides us a brief introduction to population enrichment and explains where it fits in clinical trials. He offers his insights on the topics of hypothesis testing and decision making, which is a key component of adaptive designs. You can also learn about a real-world case study (TAPPAS Trial) where this approach was used. Continue reading this blog for highlights from the webinar.
Watch the webinar recording and download the slides by clicking the button.
Read an interview with Dr. Thomas Burnett on adaptive enrichment.
Just as there are numerous adaptations that fall within the umbrella of adaptive designs, there are several different statistical methods that can lead to the construction of a synthetic control arm. Cytel’s ebook, “Demystifying synthetic control arms”, is an effort to explain common strategies for their construction. Download the ebook by clicking on the button.
Cytel brings to you a new blog series on technology and Bayesian decision-making by Pantelis Vlachos, Principal/Strategic Consultant for Cytel. In his inaugural post Pantelis walks us through the features and benefits of our new offering, East Alloy™. East Alloy™ is a web-based extension of East for clinical trial design that blends the pace of SaaS delivery, the ease of use and robustness of Cytel software, and the velocity of cloud-based computing. Gain some behind-the-scenes insights into the development of this new module and understand how your company can leverage East Alloy to conduct computationally intensive designs with ease, confidence, and speed.
Cytel is conducting a webinar series that focuses on target trial emulation and causal inference approaches using real world data. In collaboration with Dr. Miguel Hernán, Professor at Harvard University, Cytel is pioneering two “Head-to-Head Comparisons using Real World Data” studies, one in oncology one and in cardiovascular disease. These projects will occur in real time across this webinar series. Our presenters for the first webinar in this series were Dr. Miguel Hernán and Devon Boyne, Director of Epidemiology at Cytel. Continue reading this blog for a summary of the webinar, “Head to Head Comparisons Using Real World Data - The Time for Causal Inference is Now” conducted on July 7, 2020. Click on the button to access the webinar replay.
We also had the opportunity to interview Dr. Hernan on head-to-head comparisons. Read the interview here.
Unlike many therapeutic areas, oncology benefits from having standardized endpoints like overall survival and progression-free survival, as well as standardized methods of measuring such endpoints. Given that the purpose of an Estimands Framework is ostensibly to streamline scientific questions with specific targets of estimation, what is the benefit of an Estimands Framework for oncology?
Cytel SVP Corey Dunham’s inaugural post on leading the industry’s largest Biometrics CRO considers the FSP Engagement Landscape, and how the responsibilities of Sponsors and FSP providers are shaped by the needs of different projects.
Cytel is hosting a complimentary webinar series that introduces biostatisticians and other members of the development team to some of the more commonly used complex innovative trial designs, the benefits of each, and the practical considerations for adoption. You can access the replay of the completed webinars and register for the upcoming ones by clicking on the button.
In this blog, we interview Dr. Thomas Burnett who is a Senior Research Associate in Medical and Pharmaceutical Statistics at Lancaster University. His main research interests are Adaptive clinical trials and personalized medicine. In the upcoming Cytel webinar on July 15, Thomas will be presenting on the foundational elements of enrichment strategies and adaptive designs.
There has been an increased use of synthetic control arms for regulatory submissions in recent years, with three rare disease submissions and 22 medical device submissions approved using these techniques.
Synthetic control arms are virtual trial arms that use historical claims data and observational data to simulate the control arm of a study. When enrollment targets are low and large amounts of data already exist about the performance of a control, then in many cases using quantitative techniques to simulate a control arm of a trial will expedite timelines and serve as a more optimal use of resources.
Overcoming Clinical Development Challenges in Oncology with Innovative, Adaptive Designs: Complimentary Paper
Having its roots in the seminar rooms of the Dana Farber Cancer Institute, Cytel has a long record of establishing new methods in small samples, adaptive designs, Bayesian designs and multi-arm trials, to align statistical rigor to the goal of accelerating clinical development for oncology trials.
There are currently 1570 registered clinical trials for COVID-19 therapies and vaccines. Approximately 20% are registered in the United States and 25% in the European Union. How well do you know the state of COVID-19 clinical development? Take our quiz to find out:
From the time the COVID-19 outbreak was declared a pandemic, the number of studies conducted around the world to either diagnose, prevent or treat the virus literally exploded (1570 as on today, according to the Cytel Global Coronavirus COVID-19 Clinical Trial Tracker1).
Moreover, the pandemic impacted the regular schedule of ongoing clinical trials. Health authorities such as the FDA, promptly provided recommendations in the form of questions and answers on how to handle “disruptions” due to the pandemic2. These disruptions include a range of challenges including skipped assessments or study withdrawal.
“CDISC launched a task force in an effort to support CDISC members and the research community as they work tirelessly to discover critical breakthroughs to treat COVID-19 …. The task force was launched with the goal of developing Interim User Guide and Related material” said David Bobbitt, CDISC CEO, in an interview with Outsourcing-Pharma.com3. On April 21, 2020, the task force released two guidances. In this blog, I provide you with a quick summary of what these guidances address.
The two guidances are:
- Guidance for Ongoing Studies Disrupted by COVID-19
- CDISC Interim User Guide for COVID-19
Continue reading to learn more.
Expert statisticians at Cytel have spent the past three and a half months designing and deploying dozens of trials for COVID-19 trials. A new whitepaper describes the critical uses of Bayesian methodologies employed by Cytel statisticians, in their search for effective therapies, prophylactics and vaccines.
Last week, Cytel conducted its third webinar in the new introductory webinar series on Complex Innovative Trial Designs. Our speaker, Dr. Satrajit Roychoudhury is a Senior Director, Statistical Research and Data Science Center at Pfizer. In this webinar, Dr. Roychoudhury gets into the basics of phase I designs in oncology trials, explains the caveats of frequently used traditional designs and provides insights on how implementing a model-based approach can enable a better statistical inference and decision-making. You can watch the replay of the webinar and access the slides by clicking on the button.
We also had the privilege to interview Dr. Satrajit Roychoudhury. Read our blog where he talks about his interest in statistics, explains the concept of Bayesian model-based approaches and their importance in oncology trials.
Supposing two treatments, A and B, need to be compared that have not been compared through a clinical trial. In the absence of such information, those treatments have been compared with each other via a third treatment, C (i.e., A to C and B to C) using indirect treatment comparison approaches. Recent developments are challenging this status quo. The increased availability of regulatory-grade RWD helps. We can also now avoid some of the biases that used to plague the use of observational data.