The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
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.
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.
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.
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.
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.
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.
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
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