Enhance your clinical trial design with our strategic consulting services, featuring adaptive trial models and comprehensive regulatory guidance to ensure innovative, compliant, and successful trial outcomes.
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Experience the future of flexible strategic partnerships with Analytics on Demand, providing adaptive and innovative solutions that transcend traditional models to achieve unparalleled operational excellence.
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Maximize efficiency and outcomes with our project-based services, delivering specialized expertise, end-to-end biometrics, and focused solutions for unique projects, ensuring timely completion and exceptional results.
Project-Based Analytical Solutions
Cytel's software platform enables precise trial design and simulation, utilizing adaptive and Bayesian tools to optimize protocols and accelerate drug development with confidence and efficiency.
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Our unique software package streamlines trial implementation with intuitive solutions for protocol development, randomization, and patient management, optimizing operational efficiency and ensuring study success.
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Our innovative preclinical solutions empower your drug development journey with cutting-edge analytics and insights from inception to preclinical stages.
We help you navigate complex trial phases efficiently with data-driven methods & strategies tailored to Phase I-III trials for accelerated drug development.
Maximize your market potential and optimize your commercial strategies with our advanced analytical methods, data science, and tailored commercialization solutions for data-driven commercial success.
Harness the power of real-world data and real-world evidence to gather insights and shape future drug development cycles for enhanced efficacy and regulatory compliance.
Craft optimal trial designs with our advanced analytical methods to enhance efficiency and increase the probability of success throughout your drug’s lifecycle.
Empower your trial delivery by transforming trial designs into actionable strategies with our data-driven approach to ensure seamless delivery and successful outcomes.
Unlock the power of data with our methods for actionable insights to drive informed decisions and optimize clinical trial outcomes.
We offer tailored analytics solutions for your specialized or niche projects enabling you to optimize both efficiency and precision in drug development.
Enhance your clinical trial design with our strategic consulting services, featuring adaptive trial models and comprehensive regulatory guidance to ensure innovative, compliant, and successful trial outcomes.
Experience the future of flexible strategic partnerships with Analytics on Demand, providing adaptive and innovative solutions that transcend traditional models to achieve unparalleled operational excellence.
Maximize efficiency and outcomes with our project-based services, delivering specialized expertise, end-to-end biometrics, and focused solutions for unique projects, ensuring timely completion and exceptional results.
Cytel's software platform enables precise trial design and simulation, utilizing adaptive and Bayesian tools to optimize protocols and accelerate drug development with confidence and efficiency.
Our unique software package streamlines trial implementation with intuitive solutions for protocol development, randomization, and patient management, optimizing operational efficiency and ensuring study success.
By Grammati Sarri, Evie Merinopoulou, Vinusha Kalatharan, and Jason Simeone
The Canadian Agency for Drugs and Technologies in Health’s (CADTH) long-expected guidance on real-world evidence (RWE) is now in the public domain; however, it solely provides standardized (core) reporting practices for manufacturers submitting RWE studies to support their drugs applications, and important aspects of the incorporation of RWE in decision-making are missing.
Read more »
Written by Marie Diamond and Maria Rizzo
Systematic literature reviews (SLR) are essential to informing healthcare decision-making and are pivotal for reimbursement submissions to health technology assessment (HTA) bodies. One limitation of SLRs, however, is that they quickly become outdated due to the continuous publication of new literature. The living systematic review (LSR) model can overcome this challenge by incorporating relevant new evidence as it is published. Read more »
Moving beyond static evidence development to ensure local market access success; responding to recent changes in governmental drug regulations and the role of automation
The worldwide drug regulation landscape is rapidly changing. The introduction of the EU Health Technology Assessment (HTA) Regulation (EU) 2021/2282 and US Inflation Reduction Act (IRA) created a need for pharmaceutical companies to develop strategies to generate data through diverse patient data sources and use complex methodologies while keeping pace with evolving evidentiary requirements for their products across healthcare decision-making bodies. Read more »
Launching a treatment for inflammatory diseases can be a make-or-break endeavor. A robust evidence base and a compelling value story are crucial to success, but current challenges and unexpected bumps in the road will require creative solutions.
Here we describe three case study examples of common issues faced in the inflammatory disease space and how these challenges were overcome using novel solutions, ultimately leading sponsors to submission success.
Pharmaceutical research in oncology is increasingly focused on the development of therapies targeted at newly identified driver mutations. However, the rarity of many of these mutations presents new challenges for trial design and patient recruitment. In particular, it may be difficult in practice to recruit enough patients with the same mutation and tumor histology. One solution has been to evaluate these histology independent therapies (HITs) in basket trials, which recruit patients across multiple histologies that all share a common targetable driver mutation.
Many thanks to Grammati Sarri and Michael Groff for their comments in developing this blog.
An indirect treatment comparison compares two trials A and B, by first comparing the results of Trial A to Trial C, and then comparing the results of Trial C to Trial B. Unlike head-to-head comparisons where these trials (A and B) would be directly compared with each other, indirect treatment comparisons, or ITCs, utilize at least one other trial to create a network for comparison.
Often, there are fundamental differences between the trials, such as population, or the interaction of the treatment with features of the population (e.g., age, sex, etc.). These are either caused by prognostic variables or by effect modifiers. The methods with which we handle the complexities raised by each differ slightly. Population-Adjusted Indirect Treatment Comparisons (PAICs) use individual patient data from one or more trials to adjust for characteristics of patients and ensure populations across all trials are reasonably comparable.
