The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
Since 1953, when the discovery of the structure of DNA was made, we have seen great advancements in genomics. Particularly, in the last few years, the industry has seen a rapid rate of adoption in biomarkers and how they can be used to improve biomedical interventions. Trial investigators have been showing interest in biomarker-guided trials such as basket trials and umbrella trials, developed under the master protocol framework. As a result, we have been seeing a rapid rate of adoption of these innovative trial methods.
In our previous blog, we spoke with Jay Park, Director, Cytel, about the concept of master protocols, their importance and future growth potential. On March 19, Cytel conducted a webinar with Jay on “Key Design Considerations for Basket Trials and Umbrella Trials”. This webinar introduced two master protocol types and explored their extension to design in various contexts from the HIV epidemic in global health to expedited oncology trials. Continue reading for key highlights from the webinar .
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Cytel's Response: EMA Points to consider on implications of Coronavirus disease (COVID-19) on methodological aspects of ongoing clinical trials
Further regulatory guidance has been released concerning the implications of the Coronavirus disease (COVID-19) on clinical trials.
On March 25th the Biostatistics Working Party (BSWP) of the European Medicines Agency (EMA) Committee for Human Medicinal Products (CHMP) published a draft points to consider guidance document on the actions that sponsors of affected clinical trials should take to help ensure the integrity of their studies, and the interpretation of the study results, while safeguarding the safety of trial participants as a first priority.
Cytel's Response: EMA Guidance on the Management of Clinical Trials During the COVID-19 (Coronavirus) Pandemic
On March 20th the European Commission, the European Medicines Agency (EMA) and the Heads of Medicines Agency (HMA) published new recommendations for sponsors on how to manage the conduct of clinical trials in the context of the COVID-19 pandemic. Extraordinary measures may need to be implemented and trials adjusted due to quarantine, limited access to hospitals, and healthcare professional focus on critical tasks. Here is a review of selected elements of the guidance, interpretations and recommendations.
The FDA issued a guidance yesterday on how the COVID-19 Pandemic may affect the conduct of clinical trials. Below are some key messages from the guidance along with some interpretations and recommendations.
In September 2018, the FDA provided a draft guidance on master protocols reflecting an increased interest in these designs by industry. This came after a 2017 editorial published by the Drs. Woodcock and LaVange from the FDA in the New England Journal of Medicine. In this guidance master protocol is defined as a protocol designed with multiple substudies, which may have different objectives and involves coordinated efforts to evaluate one or more investigational drugs in one or more disease subtypes within the overall trial structure. As the adoption of these innovative trial methods is on the rise, we speak with Jay Park, Director, Cytel, about the concept of master protocols, their importance and future growth potential. We take a closer look at their use in oncology trials where the increase in biomarker driven enrichment and stratification designs, as well as the use of companion diagnostics, ensures that master protocols are often adopted by trial investigators.
Generating high-quality clinical data is a vital but challenging task in modern drug development. Unfortunately, in the current era of ‘big data’ and global clinical operations, spanning multiple sites and digital systems, protecting the quality of clinical data has become harder than ever.
Planning your data strategy is, therefore, crucial to ensure a high-quality evidence package and increase the chances of successful clinical development. However, as we discuss in our new eBook, planning a data strategy is a complex process involving various considerations that require significant amounts of time and expertise to fully address.
Read our eBook for expert insights on planning a data strategy that can help overcome key challenges in clinical development and boost your success.
In this blog, we discuss the many data-related challenges commonly faced in clinical development and how to implement a fail-safe data strategy that can overcome these challenges, bringing effective new therapies to patients.
Over the past decade, a new trend began to emerge, changing the way that clinical trials are conducted. Whereas placebo-controlled randomized control
It is widely acknowledged among drug developers that one of their most important assets is the data generated during clinical trials. Hence, it is no surprise that many companies plan and execute a strategy to protect the quality of the clinical data they produce. It is, however, easy to underestimate just how much time and expertise you need to address the numerous and complex considerations involved in the planning process.
Unlock top tactics and tips on how to plan a rock-solid data strategy to minimize risk and boost clinical success in our latest eBook.
If you are keen to find out how to optimize your clinical data strategy, read on to discover five of the top tips outlined in our eBook from specialists working in the Strategic Consulting, Clinical Research Services, and Data Management teams. Their global reach ensures top insights from every corner of the world.
In clinical development, a high-quality evidence package is a prerequisite for a new therapy to gain approval from regulators and other key decision-makers. As such, the quality of your clinical data is one of the key factors determining whether an effective new therapy reaches patients.
Implementing a data strategy can help to protect the quality of your evidence package. However, many companies start planning their strategy quite late in the development process, which makes it difficult to address (sufficiently address) the complex considerations involved. As we explore in our new eBook, a data strategy planned well in advance of starting Phase 1 and following the industry’s best practices can help you reduce risk, expedite clinical development, and successfully achieve your business objectives.
Download the new eBook, “Are you Harnessing the Power of your Clinical Data?” to find out how to optimize your data strategy to advance clinical development.
In our previous blog, we talked about the value of planning a data strategy for the entire duration of your program (i.e., a ‘program-wide’ strategy). However, it is also important to plan for specific phases of clinical development, because they each have unique challenges. Below we discuss the major challenges commonly encountered in Phase 1 and Phase 2 studies, and the tactics you can use to resolve them. An upcoming article will engage with challenges in Phase 3 and post-market.
The Cytel Trial Design Innovations (CTDI) Webinar Series recently hosted a webinar on designing event-based studies. Such studies are essential to designing high-efficiency clinical trials in certain therapeutic areas, but they add a number of challenges to the already complex landscape of adaptive trials.
The webinar was held on January 23rd, featuring Biostatistician and pioneering Bayesian trial-designer Pantelis Vlachos. We had the opportunity to sit down with Dr. Vlachos and speak about innovative trial designs and their benefits, adaptations and interim looks in oncology and cardiovascular, the challenges of designing event-based studies more generally, and how Cytel’s array of software tools, particularly East®, has enabled trial sponsors to fully consider their options in the design of high-efficiency clinical trials.
In the quest for clinical success, we all strive for evidence packages of the highest quality. If the clinical data is strong, then a promising new therapy is more likely to obtain approval from key stakeholders, such as regulators and payers . As a result, you’ll get the chance to develop a therapy that will help many patients (and you will likely gain returns on your investments). As we discuss in our new eBook on data strategy planning, a carefully planned data strategy can help mitigate risks to your programs and enable you to successfully achieve your goals.
Discover how to plan a data strategy that enhances your clinical programs and enables new therapies to reach patients in our new eBook.
In the high-stakes environment of clinical development, it is never too early to start protecting your valuable data assets with a first-rate strategy. So, keep reading to learn which planning approach to use, who should be involved, when it is best to start, and why it is well worth going to all the effort.
January’s Cytel Trial Design Innovations (CTDI) Webinar Series will feature Biostatistician and pioneering Bayesian trial-designer Pantelis Vlachos. Next week, Dr. Vlachos will speak on high-efficiency trial design for Event-Based Studies, particularly in oncology and cardiovascular trials. In this blog post, we offer a glimpse of Dr. Vlachos’ last CTDI Webinar (February 2019) on high-efficiency trial design using enrichment strategies.
Don't miss next week's webinar "Designing Event-based Studies: Reduce Sample Size and Increase Predictability"! Click on the button below to register.
In clinical development, data is the vital ‘foundation’ that supports your programs. To successfully bring a promising new therapy to patients, the quality of your evidence must be strong enough to gain approval from key decision-makers, including regulators, payers, and health technology assessment (HTA) agencies.
So, how can you strengthen the quality of your clinical evidence package? A key solution is to optimize your data strategy. As we discuss in our new eBook on data strategy planning, making just a few small changes to your planning approach can strengthen your ‘foundation’ and generate various benefits that enhance and expedite clinical development.
Download our free eBook to find out how to optimize your data strategy to boost success in clinical development.
With only two weeks left for this fabulous year to end, we would like to thank all our blog subscribers and new readers for following and appreciating the Cytel blog. This year, we collaborated with several experts from both within and outside the company to bring to you a range of interesting topics including real-world evidence, AI, challenges in rare diseases, patient-reported outcomes, data management, and our popular series “The Good Data Submission Doctor” and “Career Perspectives”. In this blog, we share with you the top 5 Cytel blogs that resonated most with our community in 2019.
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Cytel Inc. and Axio Research joined forces in June 2019, expanding our ability to solve the most complex analytical challenges for the life sciences industry. Cytel offers a full range of clinical data management services delivered by advanced analytics experts with global reach.
In this blog, we talk to Ronald Dumpit, who is based in Bremerton, Washington to find out more about his career path, current role at Axio and his interests outside of work.
PhUSE EU Connect 2019 was held in the beautiful city of Amsterdam between the 10th and 13th of November. This clinical data science conference comprised 19 Streams, including 150 papers, 24 posters and 3 engaging data scientists as keynote speakers. The event was well attended and had several interesting and innovative presentations. Caroline Terrill, Associate Director of Statistical Programming at Cytel UK, conducted a session “No Place Like Home: Managing Remote Programmers Remotely” and stood out as the winner in the Personnel Management category. Based on 5 years' experience of managing remote programmers, Caroline’s paper gives guidance on issues to be considered and traps to be avoided if you are managing people who work remotely.
In this blog, we share the presentations from our Statistical Programmers and summarize some of the sessions that our team members attended.
In association with Statisticians in the Pharmaceutical Industry (PSI) , UCB and Cytel hosted a symposium on September 11, 2019 at UCB’s offices in Slough, Berkshire. The primary agenda was to educate the audience on Artificial Intelligence (AI) approaches and their impact on clinical development.
With recent advances in AI, it is important for quantitative scientists to keep up to date with the most recent methods and be involved in guiding their application to the most pressing analytical challenges. This one-day event covered cutting edge examples of how data science and statistical sciences are intersecting, and its relevance to our attendees.
“Artificial Intelligence and associated methodology is becoming increasingly important to the Pharma Industry and its technical foundation in statistical theory means that PSI is naturally keen to promote good practice through its membership and established Industry links. PSI is proud to have set up a Special Interest Group in this field and is keen to broaden its links and membership.”
- PSI Data Science special interest group
In this blog, we share some of the key takeaways from the symposium. If you are interested in attending similar sessions, you can check Cytel’s list of upcoming events here.
Biotechs and Medtechs, don’t forget your market access strategy (part 4 of 4): How to optimize your market access planning approach
Author: Michael S. Paas, Market Access & Commercialization Expert, Executive at AbbVie and Guest Author at Cytel
In crafting your market access strategy, it can be valuable to follow these five best practices:
- Start planning as early as possible in the drug or device development process, to give yourself enough time to make informed, optimal decisions, and adjust your strategy when needed;
- Plan for global markets and seek early advice from payers and HTA agencies, where possible. There are many different agencies and payers to think about when you launch globally, so it’s vital to ensure you are sufficiently addressing the requirements of the priority markets. Even if you do not plan to commercialize by yourself in countries outside the US, careful, early market access planning with key global markets in mind can maximize the attractiveness of your asset to potential licensors or partners;
Biotechs and Medtechs, don’t forget your market access strategy (part 3 of 4): Harnessing the value of market access planning
Author: Michael S. Paas, Market Access & Commercialization Expert, Executive at AbbVie and Guest Author at Cytel
Addressing the myriad of considerations required for market access planning can be complex and time-consuming, so it is vital to give yourself enough time to make informed decisions. As such, starting to plan your market access strategy at least by early phase II or the proof-of-concept phase of device development can help you inform the design of the clinical program in such a way to ideally generate evidence credible and compelling to payer and HTA stakeholders, as well as regulators, in order to maximize the commercial success of your drug or device.
Planning early also gives you the opportunity to make adjustments along the trajectory of development as you gain new information and insights about the asset itself, as well as about the payer and competitive environment.
At the 2019 Challenges in Rare Diseases Clinical Trials Symposium and East training, Cytel partnered with Alexion to bring together expertise from academia and industry. David Kerr, Director of DMC Services at AXIO, was among the notable speakers and his talk “Data Monitoring Committees – Behind Closed Doors” covered general considerations and options that the DMC has when reviewing the data presentations during their closed sessions. He presented four specific case studies that highlighted the data provided to the DMC from meeting to meeting and discussed how the DMC arrived at their recommendations for each meeting. We had the opportunity to sit down with David and speak about Data Monitoring Committees, understand their proceedings and talk about his presentation at the symposium.
Biotechs and Medtechs, don’t forget your market access strategy (part 2 of 4): The critical role of market access planning in clinical development
Author: Michael S. Paas, Market Access & Commercialization Expert, Executive at AbbVie and Guest Author at Cytel
In my previous post, I established the importance of market access strategy in the clinical development process and why emerging biotechs cannot afford to overlook it.
Click on the button if you missed Part 1 or want to revisit it.
It is imperative to start developing your strategy with market access due diligence and value story creation early in the product development (at least by phase II of drug development or the proof-of-concept phase of a device development). Impactful market access planning involves designing your clinical programs so they sufficiently address the evidence needs of market access stakeholders, patients, and regulators. This means demonstrating the value of your therapy to payers and HTA agencies by generating compelling and robust clinical trial data against appropriate comparators, augmented where possible and helpful with real-world evidence, health economic arguments, economic models and/or relevant patient-reported outcomes.
Biotechs and Medtechs, don’t forget your market access strategy (part 1of 4): Why is market access strategy crucial to succeed?
Market access strategy is an integral part of the clinical development process to ensure success in global healthcare markets and vital access to patients
In clinical development, it’s easy to underestimate the critical role that market access plays in the commercial success of a product. Understandably, organizations instead focus on the regulators, and the steps needed to secure eventual approval. However, ensuring the development plan is aligned with a well-planned market access strategy is essential to help the therapy actually reach the intended patients and realize its true commercial potential following regulatory approval. This is particularly crucial considering that payers and other key stakeholders demand compelling information on a drug’s/device’s value as well as justification of its pricing.
In this four-part blog series, I will address what can be done to optimize your market access planning, and why all that effort is really worth it.
Interview with Kannan Natarajan: Drug Development in Rare Diseases - Need for Innovation in Statistical Thinking
Cytel is delighted to have Kannan Natarajan speaking at the “Complex Innovative Trial Design Symposium and East User Training” on November 6 in Boston, MA. We got a chance to sit down with Kannan and talk about his career in statistics, the changing role of statisticians, his views on evolving statistical thinking, estimands and relevance of technology in the context of rare diseases.
October 3, 2019 was an important day for the ADaM team as it marked the release of the ADaM Implementation Guidance (Ig) 1.2. Download the new guidance from the CDISC website here.
In 2018, several previews of the new Ig were made at CDISC Interchanges all around the world and at PhUSE conferences, it was only a few weeks ago that the final version was released. At first glance, the new Ig does not seem to contain a lot of new concepts and ideas. However, a critical and in-depth review clearly shows the efforts of the entire team to release this new Ig. Creating a new standard or releasing a new version of an existing standard is not an easy job. You need to ensure that you do not introduce anything that contradicts any of the existing CDISC standards. This includes, not only new variables but also any changes in existing sentences or adding entirely new sections that may cause misinterpretations or discrepancies. Moreover, every standard team member comes with their own background, company needs, and specific indication needs. It is not always easy to propose a solution that can satisfy everyone on the team.
A disease is generally considered to be rare if it affects one patient per 200,000 people (1) and most rare diseases affect far fewer than this. However, collectively rare diseases are relatively common, affecting 350 million patients worldwide (2). The path to diagnosis for these patients is often a long, difficult battle and even once the diagnosis is made, it is likely there will be no suitable treatment available. For 90% of rare diseases, there is no approved therapy (2). There is, therefore, a pressing need to develop new, effective therapies that can bring hope to rare disease patients. However, the clinical development environment for life-threatening, rare diseases is fraught with challenges. By their very nature, rare indications have few patients and limited sample size. This scarcity of patients also results in a lack of available information and knowledge about the disease from the best endpoints, to the treatment effect size or the variability of response between subgroups.
"If you went to bed last night as an industrial company, you're going to wake up today as a software and analytics company," CEO of GE, Jeff Immelt
We are living in a new digital world which is evolving every day. Both personally and professionally, we rely on technology for many of our routine activities, and examples of digitization are prevalent across industries. Retail is a big example of how several chains have moved from physical stores to creating an online presence. In some years from now, people perhaps won’t have to learn driving as more self-driven cars will hit the road. Healthcare does not fall far behind in this race towards digitization.
In this blog, we will examine some of the different ways that digitization is set to shift the drug development paradigm.
In place of collecting data from patients recruited for a trial who have been assigned to the control or standard-of-care arm, an external control creates a comparator arm using either real-world data-sets such as electronic health records or previous clinical trials. The external control offers a practical, effective way to leverage real-world evidence and has been applied in regulatory approvals. In this blog, we share an illustrative example of how we can help customers in this emerging area of interest.
This article was originally published as part of a series by pharmaphorum in association with Cytel and is reproduced with their permission.
Ever felt like you ended up somewhere unexpected, not quite knowing what path you took to get there? This is the situation pharma companies can face without the right input from statisticians on clinical trial design – and the results can be very costly. As part of a series of articles in association with Cytel, pharmaphorum spoke with Natasa Rajicic about the vital role statisticians play in improving trial design and preventing expensive mistakes and trial failures.
In this blog, from our career perspectives series, we talk with Jayshree Garade Associate Director, Statistical Programming about her truly global career path at Cytel. Jayshree completed her Masters degree in 2006 and began her professional career with Cytel in Pune India. In the years to follow she supported high profile trials for a number of sponsors, before transferring to our offices in Massachusetts USA. She is currently leading a programming team, working remotely from her North Carolina home. Read on to learn more about life and opportunities at Cytel.
The term biomarker signature describes the behavior of a set of biomarkers that define a signature to maximize the prediction performance. We examine the behavior of specific biomarkers as a set that consistently fluctuate together to maximize the accuracy on predicting the disease-related outcome.
How we apply a biomarker signature depends on the prediction problem. A prognostic biomarker signature is used to predict the disease progression, a risk biomarker signature is used to identify sets of subjects that are likely to develop a disease, and a predictive biomarker signature is used to determine the patients that are likely to respond to a particular treatment. Predictive biomarker signatures are used often in oncology to stratify patients with a specific cancer into sub-populations and develop targeted therapies for the diseased population subtypes defined by the biomarker signature.
In this blog, we share an example project that our data science team has worked on supporting this work. The case study forms part of a new ebook 'Innovative Data Science and Real-World Analytics Approaches in Practice' and we are also delighted to provide the link for download as part of the article.
Health economics and adaptive design methods share common ground in that they both aim to support more efficient and accurate decision making that can enable faster patient access to new health technologies. However, to date, there has been a limited understanding of how, if at all, the two approaches are being used together.
A paper, “A Review of Clinical Trials With an Adaptive Design and Health Economic Analysis,” exploring this important topic was published in the April 2019 issue of Value in Health (1) . In this blog, we catch up with Laura Flight, National Institute for Health Research (NIHR) Doctoral Fellow and the primary author of the paper for a deep dive into the objectives of the publication, key findings and the next steps for promoting better understanding in this area.
Cytel recently hosted a very well-attended and engaging webinar on the topic of “Estimands, not just a statistical issue” presented by Paul Terrill, Associate Principal of Strategic Consulting at Cytel.
The webinar covered a range of issues from what is an estimand to how to structure early discussions on estimands.
In this blog, we are happy to share the replay of the webinar as well a summary of Q&As that arose on this very important topic. For an introduction to the topic, check out our previous blog post 'Estimands 101 with Mouna Akacha'.
By Nicolas Rouillé and Eric Henniger
The right design and the right data ultimately leads to the right decisions, so obtaining fit-for-purpose data, collected based on what your protocol is looking for is vital. However, there are several data pressure points facing oncology drug developers that need specialized expertise and processes to handle. In this blog, we run through some key aspects to consider to smooth your data collection and analysis.
The Cytel team made its annual trip to the PSI (Statisticians in the Pharmaceutical Industry) conference 2nd to 5th June. Taking place in London, UK, the theme of this year's meeting was Data-driven decision-making in medical research. As ever, the discussions both within the official conference agenda and during the networking breaks were engaging and productive.
In this blog, we share some of the particular highlights from the sessions that our team attended. We look forward to participating again in 2020 when the conference will return to Europe.
This article was originally published as part of a series by pharmaphorum in association with Cytel and is reproduced with their permission. Scott Harris, a four-time biotech Chief Medical Officer, and principal at Middleburg Consultants, a pharmaceutical consulting organization, told pharmaphorum’s Richard Staines that using novel adaptive or seamless clinical trial models can help to cut development costs. In doing so they can reduce the risks of trial failure that can spell the end for those biotech companies without the deep pockets of big pharma behind them.
In case you haven’t noticed, the traditional three-phase clinical development process is changing. While big late-stage trials are still pretty common, it’s also no longer a surprise to see sponsors refer to phase 1/2 trials, or phase 2/3, indicating that a smaller trial can be progressed to the next phase if an interim data readout supports further evaluation.
This is known as a “seamless” trial as the boundaries between each development stage have become less defined, and there are other options too.
Middleburg Consultants’ Scott Harris is a proponent of this new way of working and has personal experience of the approach after using it to steer a gastroenterology drug through the approval process.
Nowadays, it’s difficult to pick up a mainstream newspaper or read an industry publication without seeing reference to Artificial Intelligence or AI and progress towards innovations like autonomous vehicles, or customer behavior prediction. For the biopharma industries specifically, AI represents an opportunity to avert the R&D productivity crisis with paradigm-shifting applications such as in-silico drug design, prediction of trial risks and big data analytics.
However, with every opportunity, there are risks and challenges, and in this blog, I will discuss how pharma needs to address the opacity of AI to ensure trust and credibility with all stakeholders.
In this blog, Alla Muchnik, Senior Clinical Data Manager at Cytel, discusses how specialist CROs can add value and streamline processes by providing oversight of data management services delivered by another CRO. This model helps to fulfill essential regulatory obligations for biopharma companies who may lack their own internal oversight resources.
In this blog, Jonathan Pritchard, Director Business Development at Cytel, draws on his experience in commercial, clinical and technology roles within the biopharmaceutical industry and shares his insights on the primary considerations for sponsors when implementing an ePRO solution.
At the Partnerships in Clinical Trials Conference in Barcelona in November 2018, Strategic Consultant Ursula Garczarek participated in a thought leadership stream tackling various developments in Real World Evidence, Pediatrics, Trial Design & Big Data. As well as participating in a panel discussion on innovations in clinical trial design, she was impressed by the contributions and innovations offered from other stakeholders across the healthcare landscape. One of these exceptional contributions came from from Galina Velikova, Professor of Psycho-social and Medical Oncology at the University of Leeds, and in this blog, we are thrilled to share an interview with Professor Velikova, in which she expands her discussion of the role of Patient Reported Outcomes (PROs) and Quality of Life Measures in trials and clinical practice.
No one plans to have a trial whose data collection needs rescuing. However, lagging enrollment rates, operational struggles, and diminished budgets can leave some trials in need of intervention. A great deal has been written about how to prevent the need for rescues (e.g., more investment in study planning and improved communication between stakeholders). Far less has been said about how to assemble a rescue team – the roles that need to be filled and the process of analysis that ensures the completion of a failing trial.
Quantitative pharmacology encompasses the many strategic advantages of using complex mathematical models to understand biochemical relationships that ultimately improve clinical decision-making. This includes pharmacometric modeling, familiar to those who have used pharmacokinetic/pharmacodynamic (PK/PD) modeling to improve dosage decisions, and the extension of such models to the performance of meta-analyses, the construction of decision rules, and other uses involving a broad array of cases. In this blog we summarize some key areas of opportunity.
In honor of Rare Disease Day 2019 we share a new Cytel podcast featuring Cytel Strategic Consultant Ursula Garczarek discussing how innovative statistical approaches can overcome challenges in rare disease development. Below, you can access the podcast and a summary of some of Ursula's key insights from working in rare diseases and interacting with regulatory agencies for complex and innovative designs.
In 2018, Cytel ran a qualitative survey among biostatisticians and programmers on trends in data science and perceptions about the goals, barriers and future of the field in the biopharma and life science industry. Our analysis and report revealed a range of insights from the respondents including :
Lack of shared understanding of what data science represents with less than 1 in 7 of all respondents suggesting a definition of data science.
Clear trend of investment in data science across organizational types with three-quarters of all respondents saying their organizations had a dedicated data science department.
An opportunity for improved clinical trial design by using data science techniques was recognized by the majority of respondents. In addition, respondents across all functions perceive the key opportunity for data science to be in maximizing the value of real-world data.
In a recently published discussion on The Effective Statistician podcast ( a weekly podcast produced in association with PSI) Ursula Garczarek, Associate Director Strategic Consulting at Cytel sat down with hosts Alexander Schacht and Benjamin Piske to discuss where the biopharma and life science industries are headed with the application of data science.
A 2018 publication in the Biometrical Journal by Cytel’s Cyrus Mehta, Lingyun Liu and Sam Hsiao, ‘Optimal Promising Zone Designs’ (1) marks a new milestone for adaptive sample size re-estimation. Inspired by insights from the team's work with a number of Cytel's strategic consulting clients, it presents an easy to implement and new iteration of the popular promising zone design. The basic principle? That any investment of sample size at an interim analysis should be contingent on a minimal acceptable return on the investment. This return is expressed in terms of guaranteed conditional power, By identifying a minimum rate of return upfront, the new design offers greater efficiency to clinical trial planners. Importantly, the design concept is both easy to communicate, and easily understood among statistical and clinical stakeholders alike.
In this blog, Cytel Co-Founder and Fellow of the American Statistical Association, Cyrus Mehta shares his insights with us on the goals and key takeaways of the publication, and how it adds to the growing toolkit of intuitive adaptive designs available to drug developers today. We also share full access to the publication itself.
Career Perspectives: Interview with Tina Checchio, Associate Director, Quantitative Pharmacology & Pharmacometrics
QPP remains at the heart of model based drug development. Short for Quantitative Pharmacology & Pharmacometrics, it refers to several types of quantitative modeling including meta-analysis, PK/PD, statistical modeling and the modeling of go-no-go decision rules. Cytel’s expert Quantitative Pharmacology and Pharmacometrics group delivers high quality solutions to help our customers get those decisions right.
In this blog we talk to Tina who lives in Stonington, Connecticut, to find out more about her career path, current role at Cytel, and her interests outside of work.
Nand Kishore Rawat is a Director and Head, Early Phase Biostatistics based in the King of Prussia, PA Cytel office. We recently spoke with Nand for the Cytel podcast to gain his thoughts on the unique aspects of Phase 1 development and where innovative approaches supported by thorough planning can meet these challenges head-on. Read on for key insights or listen to the podcast.
Happy New Year! As we look ahead to future successes and the new advancements in drug development that 2019 will bring, we are taking a moment to reflect on the topics that resonated most with our community on the Cytel blog in 2018. While these 6 most popular blogs encompass a variety of topics from across the data science, statistics, and statistical programming space, they all have in common a focus on innovative practices and application of statistical, data management, and data science excellence to achieve better outcomes in drug development.
PhUSE EU Connect 2018 took place in Germany’s financial capital Frankfurt, 4th - 7th November and brought together a range of experts to tackle the most pressing issues facing statistical programmers today. The agenda was superb with 143 presentations in 16 different streams and nearly 30 posters. This year’s event theme ‘Future Forward’ did not disappoint and there were some very thought-provoking talks on the drug development industry's challenges and what we can do in the future to meet these challenges. Additional hot topics were: Analytical Risk Based Monitoring, Machine Learning, and Data Standards and Governance. We found this year's event informative and well attended.
In this blog, we share the contributed posters and presentations from our Statistical Programmers and summarize some of the particular highlights from the sessions and posters that our team members attended.
In this blog, Paul Terrill, Director of Strategic Consulting at Cytel outlines his blueprint for ensuring smooth communication between statistical and clinical stakeholders. Paul draws upon his 20 years of experience working as a statistician and his training background to share his guidelines for success. Whether you are a statistician looking to hone your project communication skills, or a clinician keen to maximize the benefit of statistical input to your trial, this article will provide helpful pointers.
This is the third in our blog series ' The Good Data Submission Doctor' in which Angelo Tinazzi, Director of Standards, Systems and CDISC Consulting at Cytel tackles key issues in preparing data for CDISC submission. In the previous “Good Data Submission Doctor” blog Angelo discussed his top 5 SDTM FAQ; in this article he turns his attention to the top FAQs for ADaM. Read on for Angelo's insights.
In this blog, we talk with Robert Greene, Founder and President of the HungerNDThirst Foundation, about his upcoming presentation at Cytel’s East User Group Meeting on 14th and 15th November at Merck in Darmstadt, Germany. Robert will bring a fresh perspective to the discussion of the role statisticians can play in enhancing the position of patients in clinical trials. Patient-centricity is a key topic in modern drug development, and this session aims to encourage statisticians to question the importance of a more patient-centric approach within their field.
We are excited to announce an upcoming webinar in our Trial Innovations Series. “Basket Trials: Design and Implementation Considerations” on 4th December 2018 at 11am EST. Noted basket trial expert, Robert (Bob) Beckman will share his most recent experiences with Cytel Strategic Consulting Statistician Sam Hsiao on expanding the application of this innovative breed of trials. Bob acts as a trial design consultant to biopharma companies in addition to his role as Professor of Oncology and Biostatistics, Bioinformatics, and Biomathematics at Lombardi Comprehensive Cancer Center and the Innovation Center for Biomedical Informatics, Georgetown University Medical Center.
Data is the most crucial asset in any clinical trial and is used to ultimately drive the decision-making process related to the development candidate. Therefore, for any sponsor, paying close attention to the data management aspects of clinical operations should be paramount. The principles of data management are simple and well-founded. However, the application of these principles needs careful consideration, depending on various scenarios and the size of the organization. When implementing data management for your trial, it is critical to plan ahead and fully understand all the steps and activities involved. Fortunately, both strategic and tactical opportunities are available to help sponsors successfully
implement a data management strategy, and ensure quality and simplicity in data collection to enable subsequent analysis. In this ebook, our experienced global data management team outlines some considerations to help sponsors navigate key decisions that need to be made throughout trial implementation.
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.
In this second post of the “Good Data Submission Doctor” ( read my first post The Master Recipe: Quality and Attention to Detail Matter here) I would like to go through some of my favorite SDTM Frequently Asked Questions. These are questions I regularly receive in my capacity as a CDISC Subject Matter Expert, either from my colleagues or from the sponsor. Let’s start by taking a look at five of the most recent.
Cytel data scientists apply advanced statistical techniques including predictive modeling of biological processes and drug interactions to unlock the potential of big data.
In this blog we talk to Munshi Imran, who is based in Pune, India to find out more about his career path, current role at Cytel and his interests outside of work.
In this blog, we talk with Simon Kirby, former Senior Director at Pfizer, about his upcoming presentation at Cytel’s East User Group Meeting on 14th and 15th November at Merck Darmstadt, in Germany. Simon will address the topic of Selection Bias for Treatments with Positive Phase 2 Results and in this blog he explains why this is a key topic of particular relevance for pharmaceutical companies in today’s climate of accelerated development. He also talks with us about his career in statistics, current research, and his book Quantitative Decisions in Drug Development.
The Society for Clinical Data Management (SCDM) conference brought clinical data managers from around the world to Seattle-Bellevue, WA on September 23-26. The conference offered an unmatched opportunity to discover innovative solutions in the clinical data management industry. In this blog, we will share our data management colleagues' experiences, observed trends and contributions to the program.
We are delighted that Stephen Senn will be joining us at the EUGM on November 14th and 15th in Darmstadt, Germany. In this blog, we sit down for a discussion with Stephen about his career in statistics, his advice for early career statisticians, his upcoming research, and the topic of his presentation at the East User Group Meeting “70 Years Old and Still Here: the Randomized Clinical Trial and its Critics”.
The "Master Recipe": Quality and Attention to Details Matter When Submitting CDISC Packages to Authorities
One of my wife’s favorite TV shows is ‘Quattro Ristoranti’ (Four Restaurants). In each episode of the show, 4 restaurants of the same style are assessed and the one getting the best evaluation wins the prize. One of the first things the TV presenter Alessandro Borghese, a famous Italian chef, does while visiting the restaurant is to assess (of course!) the kitchen and how much the kitchen and its tools are cleaned. This assessment could have a big impact on the final outcome regardless of the quality of the food served in the restaurant .... the state of the kitchen and its cleanliness influences Borghese’s faith in the chef’s work.
This is exactly what could happen in a data submission to health authorities such as the FDA: the efficacy and safety of your drug are of course what matter, but lack of traceability, or poor or insufficient documentation might trigger questions and concerns from the reviewer. While this might not impact the overall final outcome of your submission, approval could be delayed if the reviewer starts questioning what you have done by requesting changes, or new deliverables to clarify the aspects that were not sufficiently clear in your original submission.
In this blog, we talk with Heiko Götte, Senior Expert Biostatistician at Merck about his upcoming presentation at Cytel’s East User Group Meeting on 14th and 15th November at Merck Darmstadt, in Germany. The topic Heiko will address is Decision Making in Development Programs with Targeted Therapies and he explains to us why this is a key topic for pharmaceutical companies today as they strive to improve their decision-making, and what delegates can expect to take away from the presentation.
At Cytel we believe that expert statistical input has the power to shape the future of clinical development: de-risking portfolios, accelerating timelines, and increasing the probability of success.
In this blog we talk to Adam who lives in North Carolina United States to find out more about his career path, achievements, current role at Cytel and his interests outside of work.
Immunotherapy has brought us many promises, most notably, of a future where humans are able to harness their body’s own ability to protect them from illness. Immuno-oncology (IO) may be the ultimate frontier of that future reality, with a promise of being able to help our bodies deflect or cure us of any malignancies. Today, these therapies include cell therapies, cancer vaccine, and T-cell–stimulating antibodies, with the field continuously expanding.
While medical science behind immune-oncology (IO) treatments is fascinating and expanding at a rapid pace, so too are the statistical challenges posed by the development of these agents.
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 artificial intelligence (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. A recent Deloitte survey (1) found that 90 percent of biopharma companies are making significant investments in
real-world evidence capabilities to drive drug development and meet regulatory requirements.
Real-world evidence (RWE) has historically been used for post-marketing endorsement and in pricing and reimbursement negotiations. But could data science offer an opportunity to fundamentally shift this
paradigm, leading to better and more affordable medications being approved on the basis of RWE?
In June 2018, Cytel created and ran a survey asking respondents from our audience about the potential of data science approaches in the sector. We are now excited to share the insights from the survey* ( designed as a qualitative pulse check) which reveal a powerful potential shift in the current drug development and approval paradigm.
On August 29th 2018, the FDA announced (1) that it would be establishing a Complex Innovative Trial Design (CID) Pilot Meeting Program. This follows the release earlier in August of a draft guidance (2) to help advance effective and innovative clinical trial designs early in drug development that can expedite new cancer therapies.
EnForeSys is Cytel’s tool for patient recruitment planning. We have discussed on the blog recently with Tufts University's Center for the Study of Drug Development, Ken Getz, the problem the industry continues to face with patient recruitment, and the fact that most trials significantly exceed their original planned duration. In the face of this problem there's a pressing need to create more realistic plans and scenarios. To achieve this, EnForeSys models the enrollment process and then assigns probabilities for various scenarios.
JSM 2018, ASA’s annual gathering of over 6500 attendees attracted statisticians and data scientists to the beautiful city of Vancouver on July 28 – August 2. The conference offers a one of a kind opportunity for statisticians to exchange ideas and explore opportunities for collaboration. In this blog, we will provide access to our team's slide decks from the event, as well as some of their key takeaways from sessions that they attended.
Cytel has grown significantly over the last 30 years, with operations across North America, Europe, and India. All of our processes, talent, and expertise are applied to maximizing the value of clinical data. At Cytel, quality comes first, and our QA team are committed to ensuring processes are in place to support our services.
In this blog we talk to Meredith who lives in Somerville, Massachusetts, to find out more about her career path, current role at Cytel, and her interests outside of work.
After having spent 15 years in the pharmaceutical industry, in May of 2018, I decided to explore new horizons and took the lead of the newly created Basel statistical programming team at Cytel. Building a new team in an exciting environment and being part of a successful story was the challenge I was looking for. In this blog, I will share my perspectives on what a sponsor programmer might expect when moving into a CRO role, and some of the differences and similarities of working within the two environments.
2018 East User Group Meeting Addresses Multiplicity Themes, with keynotes including Stephen Senn and Meinhard Keiser.
Cytel’s 7th East User Group Meeting (EUGM) will take place on November 14 & 15, 2018 at Merck in Darmstadt, Germany, bringing together industry experts, thought leaders and applied statisticians to discuss the future of clinical trials.
The agenda has been developed collaboratively by the EUGM Scientific Committee, and keynote speakers will include Stephen Senn, Meinhard Kieser, Thomas Burnett, Robert Greene and Simon Kirby.
In this blog, we took the opportunity to talk to one of the speakers, Thomas Burnett, Senior Research Associate in Medical and Pharmaceutical Statistics at Lancaster University, about his presentation topic “Bayesian Optimization of Enrichment Designs” and his perspectives on what EUGM delegates will be able to take away from his talk.
We have written on the blog in the past about the value that a statistical consultant can bring to your team, and to the overall clinical development process. Statistical consultants can be instrumental to the success of your development program, providing a variety of input from creating innovative trial designs that improve information quality and efficiency, to supporting regulatory interactions.
By Gordhan Bagri and Munshi Imran Hossain with H A S Shri Kishore
Shiny (from RStudio) is one of the most popular R packages. The package allows programmers to create applications with interactive user interfaces. These applications can then be deployed for non-programmers to perform analysis. Non-programmers can, therefore, make use of the statistical capabilities of R by means of point and click. This is one of the reasons why its use has been on the rise in the last few years.
In this blog, we share a new infographic based on this popular blog post illustrating some of the critical interactions that need to take place between data management and statistics groups to help ensure efficiency and data quality.
At Cytel our strategic consulting team works on a wide range of projects including: Identifying the best clinical trial design, implementing adaptive designs, developing a regulatory strategy and interacting with regulators.
In this blog we talk to Sam who lives in the Boston area, to find out more about his career path, current role at Cytel, industry experience and his interests outside of work.
A recent article published by Cytel authors Samadhan Ghubade, Sharayu Paranjpe, Kushagra Gupta, Anil Gore and colleague Krishna Asvalayan in the journal Current Science, tackles the topic of adverse drug reactions (ADRs) – a matter of great concern in drug research. The authors focused their research on drugs which had been either banned or withdrawn due to a serious problem of ADRs and applied quantitative modeling techniques to see if a systematic pattern of safety signals could be detected within the ADR count data. In this blog, the publication’s authors share their thoughts on the goals, takeaways and next steps for the research and we also link to the full article.
In this blog we share a case study of how we established and ramped up a functional service outsourcing partnership for biostatistics, programming and data management.
It’s shaping up to be a busy year for Cytel’s software development team with a number of upgrades and planned launches across our range of tools. (Watch this space for announcements soon on new quantitative decision-making software OK GO and an upgrade to EnForeSys). East, our industry leading platform for clinical trial design, simulation, and monitoring will be unveiling version 6.5 in the Fall, and delegates at the PSI conference in early June had the chance to grab a sneak peek of the new functionality in one to one demos.
We’ll also be opening the hood on the new design capabilities you can expect in East 6.5 at a complimentary webinar on Wednesday July 18, 11:00AM - 12:00 US EDT (16:00 UK, 17:00 EU).
Our presenters Pantelis Vlachos and Charles Liu, will introduce the 3 new available modules and share their insights on the supporting methodologies and their practical applications. New developments in the East software are typically derived from two sources: our team’s interaction with our customers, particularly during East training; and from our consulting practice when we help clients design their trials.
The new modules in East 6.5 include:
MCPMod (design with Multiple Comparisons Procedures)
MCPMod allows you to measure the likelihood that particular dose-response curves are the right mathematical model for a given set of data. East MCPMod will allow designing a trial using optimal allocation and then analyze the trial data using various dose/model selection criteria resulting
into a solid base (target dose) for the next phase confirmatory trial.
Population Enrichment (Adaptive designs)
An adaptive enrichment design allows the full population is segmented during interim analyses. Recently, we worked with TRACON Pharmaceuticals to design their TAPPAS trial that incorporated a population enrichment component to help overcome the potential heterogeneity of treatment effect between subpopulations for an angiosarcoma design.
It is important to take a strategic approach to clinical development to minimize the potential for Phase 3 attrition. This new module will help users apply simulations to optimize their clinical trial programs.
Click the button below to secure your place at the webinar.
A number of the Cytel team were in Amsterdam, 3rd- 6th June 2018 for the PSI Conference. This year’s conference was held at the magnificent Beurs Van Berlage, a venue full of history and interesting architectural features. We took the opportunity to give delegates a first look at OK GO, our new clinical trial Go/No-Go decision-making software in this magnificent setting.
In this blog, we'll summarize some of the particular highlights from the sessions that our team members attended.
Measuring lots of little details: Non-Compartmental Analysis and the Early Phase Regulatory Environment.
By Esha Senchaudhuri
With thanks also to Jitendarreddy Seelam and Ramanatha Saralaya for their input.
The fact of the matter is that I now want to recall everything, every trifle, every little detail. I still want to collect my thoughts and - I can't, and now there are these little details, these little details...”
― Fyodor Dostoyevsky, The Meek One
Old Fyodor was hardly talking about clinical trials, but early phase trial sponsors can probably relate to a regulatory environment which requires systematic attention to details, the little details and all these little details. When conducting early phase studies, global regulators require submission of Non -Compartmental Analyses (NCAs) that measure factors such as extent and rate of exposure to a drug, without the complexity of strenuous assumptions or complex models. Through the use of rudimentary methods such as linear trapezoidal rules, NCAs make it relatively easy to measure the concentration of a drug in a body over time. They can capture length of exposure, and time of peak exposure, without the challenges of models that require independent validation . While those other models are also becoming more common in quantitative pharmacometrics, ideally NCAs can complement these other methods.
It may be tempting to assume that due to the ease of measurement, it is unnecessary to invest in statistical expertise and reliable software for NCAs. While the calculations may not be as complex as other forms of pharmacometric modeling, taking shortcuts at this stage can prove problematic later on.
Widely recognized for being ‘assumption-free’  NCAs are a common subject of regulatory inquiries. Exposure and absorption data is obviously important for early phase trials, so NCAs are required for submission throughout the process. A strong data management system with reliable software can ensure that findings collected at this stage are streamlined across several early phase trials, making such information easy to access and ensuring a rapid response for regulators. Further, NCAs are often required to be submitted with early protocols making it useful to have statistical designers familiar with the NCA findings. As NCAs are an integral part of establishing an early phase audit trail, it is important to use NCA software that streamlines a detailed and complex workflow such as Phoenix WinNonlin.
Accurate NCAs can combine with other forms of quantitative pharmacometric models like PK/PD analysis to build strong dose-response models for Phase 2. It is common knowledge that unreliable dose-response models in Phase 2 can create headaches for Phase 3 tests. Only 13.2% of Phase 3 trials that are accepted after initial rejection, are rejected on grounds of efficacy. More common reasons are dose selection, choice of endpoints, and other challenges that better Phase 2 modeling can prevent . Working with statistical experts as early as Phase 1 can ensure that knowledge gleaned from NCAs can be employed to build stronger Phase 2 models, thus avoiding Phase 3 pitfalls.
Cytel has a dedicated team that has developed efficiencies and experience in early phase trials, including Non-Compartmental analyses. To learn more about our capabilities in this area, please click on the button below.
 Gabrielsson, J. and Weiner, D., 2012. Non-compartmental analysis. In Computational toxicology (pp. 377-389). Humana Press, Totowa, NJ.
 Sacks, L.V., Shamsuddin, H.H., Yasinskaya, Y.I., Bouri, K., Lanthier, M.L. and Sherman, R.E., 2014. Scientific and regulatory reasons for delay and denial of FDA approval of initial applications for new drugs, 2000-2012. Jama, 311(4), pp.378-384.
At the recent PCMG conference in Malta, Adrian Otte ( Independent Consultant, formerly VP Global Development Operations at Amgen) presented to delegates the strategic choices open to sponsors when choosing an outsourcing model and the three fundamental issues in play: standardization, flexibility and cost. In Dr. Otte's view, standardization of systems and processes is key, but is often overlooked as a factor by companies of all sizes when deciding how to outsource clinical trial activities. In this blog, Dr Otte joins us to share his insights on this topic, as well as this views on how outsourcing has evolved in recent years, and the future trends that will have most impact.
Cytel data scientists apply advanced statistical techniques including predictive modelling of biological processes and drug interactions to unlock the potential of big data.
In this blog from our Career Perspectives series, we talk to Andrea Hita, at Data Scientist at Cytel, to find out more about her career path, her current role at Cytel and her interests outside of work.
By Esha Senchaudhuri
An important trend in clinical development involves integrating strategic pharmacometric analysis with program level decision-making, to make the most use of available data. This can occur in various forms, from leveraging preclinical data for go-no-go decision making , to the need for improved comparative effectiveness frameworks .
Here we have five reasons why you should consider utilizing model-based meta-analyses ( MBMAs) for your program or portfolio development.
Our Industry Voices series showcases our clients’ innovative work and breakthrough therapeutics in oncologic indications and other critical areas of medical unmet need.
In this article, we sit down with Charles Theuer, M.D., CEO of TRACON Pharmaceuticals to discuss
his work, his views on the key advancements in oncology development, the unmet needs yet to be overcome, and the importance of efficient trial design in rare cancers. Click here to download a .pdf of the article, or read on.
At the recent CDISC EU Interchange in Berlin, Angelo Tinazzi, Director of Clinical Data Standards and Submissions at Cytel, showcased a popular poster presentation analyzing the differences between the Pinnacle 21 enterprise (P21e) and community versions. Those working in the field of data standards, will know that Pinnacle 21 is led by the team that created OpenCDISC, and is now the leader in software and services for managing CDISC compliance and clinical data quality. The organization continues to offer a community based software tool, in line with the OpenCDISC model, but now offers an enterprise version to sponsors and CROs, that is also used by the FDA itself.
Our Industry Voices series showcases our clients’ innovative work and breakthrough therapeutics in oncologic indications and other critical areas of medical unmet need.
In this article, we are delighted to share an interview with Kurt Gunter, M.D., Chief Medical Officer of Cell Medica in which he discusses his work, his views on the key advancements in oncology development, the unmet needs yet to be overcome, and the importance of strategic biostatistics input to his organization. Read on, or click here to download a copy of the article to read offline.
PSI is a global member organization dedicated to leading and promoting best practice and industry initiatives for statisticians in the biopharmaceutical industry. The PSI annual conference is going from strength to strength, attracting increasing numbers of delegates from Europe and beyond. With the 2018 conference taking place in Amsterdam in only a month’s time, we took the opportunity to sit down with Lucy Rowell, Senior Principal Statistical Scientist at Roche and the Conference Chair, to learn more about this year’s venue, themes, and new hot topics, along with insights on Lucy’s vision for the future of the PSI organization. We look forward to seeing you in The Netherlands!
Cytel has industry-leading experts in Statistical Programming, our programmers have years of SAS® Programming expertise, combined with in-depth knowledge of the specific clinical subject matter, which allows for competent and on-time completion of tasks.
In this blog, we talk to Omar, who is based in Geneva to find out more about his career path, current role at Cytel and his interests outside of work.
Data management is an essential building block for successful Immuno-Oncology (I-O) trials. At the Immuno-Oncology Clinical Trials operations meeting in New York in earlier this year, Patti Arsenault, VP Quality Assurance at Cytel discussed with Christopher Lamplugh, AVP, Clinical Data Management, Global Data Operations at Merck, the key challenges for data management in the space, and what’s needed to overcome them.
Our recent Clinical Biometrics Survey explored the views of respondents from across the statistical programming, biostatistics, and data management functions to learn their top challenges, and most important perceived industry trends and skills development. In this blog, our Ajay Sathe gives his perspectives on the key areas of personal and knowledge development that he believes statistical programmers need to focus on to keep abreast of the evolving drug development landscape.
We return to our discussion with Ken Getz of the Tufts CSDD for part 2 of our blog post on key challenges in clinical trial operations. You can find Part 1 of the interview here, or read on to gain his insights on the fundamental problem at the heart of clinical trial operations challenges, and his views on the initiatives and programs that he believes show the most promise for the future.
Photo by J. Kelly Brito on Unsplash
Research on clinical trial enrollment makes for sobering reading, characterized by the oft-cited statistic that 11% of active sites fail to enroll a single patient. In this first part of a two part interview, we sit down for a discussion with Ken Getz of the Tufts CSDD. Here, Mr. Getz expands on some of the Center’s more recent research on challenges in clinical trial operations. In the second part, to be published next week, Mr. Getz will reveal his insights on the key opportunities for the future.
By Esha Senchaudhuri
In response to its R&D productivity from 2005 – 2010, AstraZeneca took the initiative in 2011 to implement what it has called the 5R Framework to strengthen its capabilities. In a Perspectives article from Nature Reviews Drug Discovery , Paul Morgan and his team provided complex details about the success of this framework from the perspective of every stage of drug development. Between 2005 and 2010, AstraZeneca was behind industry averages in every phase of clinical development except Phase 1. After the implementation of 5R, AstraZeneca success rates improved substantially. Indeed, it was announced by IDEA Pharma in March 2018 that AstraZeneca had topped its 2018 innovation index. Here we examine to what Morgan et al, attribute AstraZeneca’s success.
To mark the occasion of our 30th anniversary, in late 2017 we conducted a brief survey to gain a snapshot of what professionals in data management, statistical programming, and biostatistics feel are the key challenges facing their functions, the top areas for skills development, and the clinical data areas they believe are likely to have the greatest impact on drug development.
We are now able to share our findings- read on for some highlights, and to download your complimentary copy of the report.
East is the industry standard platform for clinical trial design, simulation, and monitoring, improving scientific productivity during the critical planning stages of clinical development. In this blog, our Hrishikesh Kulkarni takes us on a tour of his life as a Cytel software trainer and answers some frequently asked questions about how East training sessions work in practice.
CliPLab (Clinical Professional Laboratory) is Cytel’s premier training initiative for bridging the skills gap in biometrics and analytics within clinical development. Leveraging Cytel’s experience and reputation in biostatistics and clinical biometrics, the organization provides practical learning modules in clinical SAS programming, biostatistics, data management, pharmacovigilance, scientific medical writing, key therapeutic areas and crucial soft skills. With learning programs led by experienced trainers, CliPLab engages both with individual students, and companies (e.g. biopharma, CROs) needing to support and augment their internal training programs.
In this blog we share a case study of how CliPLab supported a pharmaceutical customer with a tailored SAS training program for a cohort of new graduate recruits.
At Cytel we believe that expert statistical input has the power to shape the future of clinical development: de-risking portfolios, accelerating timelines, and increasing the probability of success.
In this blog we talk to Benjamin who lives in France, to find out more about his career path, achievements, current role at Cytel and his interests outside of work.
by Natalie Fforde, Senior Director of FSP Services at Cytel
With effective use of outsourcing, sponsors are able 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. At Cytel we work with our clients to tailor the outsourcing model that works best for an organization's particular circumstances.
In this blog, I will take a look the Functional Service Provider ( FSP) outsourcing model and some of the key factors that can help make a partnership ‘tick’ successfully.
By Ivan Navarro, Data Scientist at Cytel
R is an open-source implementation of ‘S’, the statistical programming language. With its open character and ability to extend its functionality using external packages, R allows users to create their own packages that are easily loadable into the core instance.
In essence, R-packages are extensions that contain source-code, documentation, data and examples of personal contributions and can be extremely useful for data scientists, statisticians and programmers alike who need to create custom analysis and visualizations. However, creating your first R-package can be a complex task for non-experienced users.
In this blog, I explain how to create a basic R-package which can be used as template for anyone interested in making a contribution. A previous knowledge on R programming is required, but you will not need to deal with technical aspects of the creation process because the R-Package structure is shared at the end.
Photo by Dose Media on Unsplash
By Charles Liu, Senior Product Manager, Cytel
Several years ago, I was one of few Luddites in my social circle still using a “dumb” phone. Other than calls, and (text only!) messaging, it had no other functionality. Once I made the switch, a whole new magical world unveiled itself. With the tap of a button, I could read my email, listen to a podcast, find a nearby restaurant, order a cab, snap a photo, and so on. What was once considered science fiction seems an indispensable part of life today.