Statistical programmers at all levels can make a significant impact on streamlining delivery, improving efficiency, and importantly ensuring quality. At a recent PhUSE Single Day event , Cytel's Sunil Gupta gave a very well received presentation on how best to achieve high quality deliverables while maintaining efficiency, noting that 3 key components should be observed:
Apr 5, 2017 11:39:42 AM
Mar 29, 2017 8:29:00 AM
With an increasing interest in platform designs and other innovative designs that involve multiple comparisons over multiple stages, the importance of Multi-Arm Multi-Stage ( MAMS) designs is set to rise.
Mar 24, 2017 9:27:00 AM
Robust go/no-go (GNG) decision-making is essential for effectively managing risk across a clinical portfolio. In early phase development, it is particularly important to have the correct tools in place to terminate ineffective compounds quickly, while accelerating promising ones through the process.
Mar 20, 2017 9:54:00 AM
In the randomized clinical trial (RCT), the process of deciding the randomization method and implementing is critically important. Unfortunately, it is not unheard of for problems to arise. In an article (Downs et al 2010 1), it is noted that as well as initial errors of trial design, problems can arise from errors with programming of the randomization or even human error during the course of the trial. Maintaining the rigor of the RCT relies on robust and reliable randomization with no errors. If treatment allocation is inadequately concealed then overestimation of treatment effect can occur, and the ‘randomized’ control trial becomes effectively ‘non-randomized’ – putting the entire study at risk (2).
Mar 15, 2017 8:51:00 AM
A precise and thorough approach to planning is key for success in data management.
The Data Management Plan (DMP) is a critical document in any data management project. It outlines all of the data management work to be done, the timelines and milestones to be achieved, as well as the outputs to be produced. The DMP lets all of the stakeholders know what to expect, how to expect it and when to expect it.
The Society for Clinical Data Management (SCDM)‘s publication, Good Clinical Data Management Practices (GCDMP) (1), provides a complete chapter on Data Management Plans. (The GCDMP is available, even to non-members of the society, at their webpage). It is important to note that while DMPs are not regulated documents, they are in fact so commonly used across the industry they have become auditable, and therefore scrupulously close attention needs to paid to getting them right.
We outline 4 key points to bear in mind when creating or reviewing a Data Management plan.
Use a Standard Template for Consistency
To a great extent, the DMP can, and should be standardized across projects for a consistent approach. When using a centralized biometrics model, where data services( data management, statistics, statistical programming) are conducted by a single provider, the development of such standard documents can represent an efficiency in the study set up, and also reduce the oversight burden for the sponsor. Indeed, for any trial project, a robust Data Management Plan template provides a solid starting point. One of the important challenges facing industry professionals today is the increasing complexity of clinical trials, and as such, great care needs to be taken to ensure the DMP accurately documents what actions will be taken with the trial data. Having a highly experienced data management team working on your project, with a track record of implementing innovative and complex trial designs, therefore, becomes increasingly important in this environment.
Mar 10, 2017 7:19:33 AM
At the recent Biosimilars Summit in Philadelphia, Cytel's Pantelis Vlachos presented on statistical challenges and flexible approaches in biosimilar development. In this blog we summarize some of the challenges and share the slides from talk.
Mar 2, 2017 8:45:00 AM
We continue our case study series with this example of a Phase 3 design that uses Bayesian decision making combined with frequentist final analysis.
Clinical Development Background
Our biopharmaceutical client’s lead drug candidate is a late clinical-stage cancer immunotherapy for treatment of a rare oncology indication. Clinical development of therapies in this indication faces inherent challenges of patient recruitment and scarcity of data.
The sponsor had previously conducted a randomized, double-blind, placebo-controlled Phase 2 study. Moving into a confirmatory clinical trial setting, they came to Cytel for support with a trial design to address their key questions:
Feb 27, 2017 7:39:00 AM
It’s been hard to miss the prevalence of estimand-related discussions in the last year. This is a topic which is very much at the forefront of statistics discussions right now. We are lucky enough to welcome Mouna Akacha to the blog to give us the lowdown on estimands and the problems and opportunities they represent for the global biopharma industry.
Mouna is a Consultant in the Statistical Methodology Group of Novartis Pharma AG, based in Basel, Switzerland. She has a wide range of research interests including topics on missing data, longitudinal data and recurrent event data and is an active participant in the current estimand discussions.
Read on to find out everything you ever wanted to know about estimands but were afraid to ask…..
Feb 21, 2017 9:39:07 AM
In a previous blog, we provided an overview of basic data structures in R. In this follow up piece, we will provide a snapshot of basic syntax in R for programmers who want to get up to speed in this increasingly important programming language.
Feb 15, 2017 9:33:05 AM
Outsourcing solutions should never be a one size fits all process, and smaller and emerging biopharma companies may have different priorities and processes when working with external vendors to larger pharmaceutical organizations.
Feb 9, 2017 7:34:58 AM
In this blog, Adam Hamm, PhD, Director Biostatistics at Cytel shares some of the most important knowledge he uses in his day to day work as a biostatistician working extensively in oncology research. Adam has broad experience with statistical analysis and methodology over all phases (I-IV) of development, in particular working in the oncology arena.
As a Director of Biostatistics at Cytel, I work on design, statistical analysis and reporting projects for a range of biotechnology and pharmaceutical sponsors. During my career, I’ve developed a particular focus on oncology trials, so in this blog I’ll share some insights into the knowledge which I have found particularly vital as a biostatistician working in this area. This knowledge spans specific statistical methodologies and understanding of the clinical issues across the phases of clinical development. The summary is not exhaustive, but provides a glimpse into the broad exposure which is needed for a biostatistician to develop a fully rounded understanding in the area. To learn more, read on...
Feb 6, 2017 9:10:00 AM
CDISC is a global, nonprofit charitable organization whose mission is ‘to inform patient care and safety through higher quality medical research’. The organization delivers this mission through the development of data standards designed to streamline clinical research- these standard formats are increasingly expected for use in data submissions by regulatory authorities. Importantly, data standardization also brings significant benefits to the industry- in the CDISC 2014 Business Case (1), it is noted that:
“For those developing regulatory eSubmissions, using updated baseline numbers for the time and cost of getting a drug to market, it can be found that ~ $180M can be saved per submission (18% of the total cost). An average of two years can be saved off of an average 12-year clinical development program lifecycle – just by standardizing data”.
It’s therefore critical that the biopharma and CRO industries develop the next generation of data managers, statisticians and programmers with strong knowledge of the CDISC standards.
Angelo Tinazzi has more than 20 years’ experience in data-management and statistical programming and is Director of Clinical Data Standards and Data Submission at Cytel. He has been a member of the European CDISC Committee since 2015 and is a member of the CDISC ADaM team. Taking the next step in his journey as a data standards expert, Angelo is now a "candidate trainer" with CDISC –working towards becoming an “Authorized CDISC Instructor”. In this blog we find out more from Angelo about his experiences and the role of the CDISC trainer.
Jan 30, 2017 9:50:24 AM
Single ascending dose (SAD) and multiple ascending dose (MAD) studies are typically the first in human studies. They seek to gain information on safety and tolerability, general pharmacokinetic (PK) and pharmacodynamic ( PD) characteristics, and of course identify the maximum tolerated dose (MTD).
Conventionally, SAD and MAD studies were conducted separately, but increasingly are combined into an ‘umbrella’ protocol which addresses both SAD and MAD objectives.
Jan 23, 2017 10:35:00 AM
As a group, Cytel had over 40 successful regulatory interactions last year, many of which supported approvals for innovative trial design approaches. In this blog we look at some of the key success factors for regulatory interactions regarding adaptive designs.
Jan 19, 2017 7:05:00 AM
R is on the rise in biopharma, and as we have previously discussed on the blog, it is now time for SAS programmers to get up to speedwith this popular and powerful programming language. Indeed, one of the advantages of R is its ability to integrate with other languages like C, C++, Python and SAS. Its strong graphical capabilities allow output in PDF, JPG, PNG, and SVG formats and table outputs for LaTeX and HTML. Importantly, as an open source resource, there is a strong community around R and extensive support for users in the form of forums like R-bloggers, StackOverflow and GitHub Repository
In this blog, we’ll provide an overview of R basic structures for programmers.
Jan 16, 2017 8:41:00 AM
The Global Cardiovascular Clinical Trialists Forum is a key event bringing together leading experts from across the spectrum of opinion leaders, clinical trialists, investigators, regulators, statisticians and practitioners to address the most pressing questions in cardiovascular clinical development today. At the December conference, eminent biostatisticians Cyrus Mehta and Stuart Pocock led a packed workshop tackling the advantages and limitations of adaptive designs within this space.
Jan 5, 2017 8:45:00 AM
Nonlinear Mixed Effects Modeling (NONMEM) is a type of population pharmacokinetics/pharmacodynamics (popPK/PD) analysis used in Clinical Pharmacology research. The population PK approach combined with pharmacodynamics modeling, allows integrated analysis, interpretation, and prediction of the drug’s safety, efficacy, dose-concentration relationship, and dosing strategy.
Dec 23, 2016 8:21:00 AM
As we prepare to say 'so long, farewell' to 2016, we'd like to take the opportunity to thank all our blog readers and subscribers. Read on for a round up of our most read topics from the year....
Dec 21, 2016 9:45:00 AM
December 18th 2016 was a significant date for the pharmaceutical industry and regulatory submissions. For trials which commence after this date, the FDA will no longer accept non-CDISC data submissions for new drug applications ( NDAs) , certain investigational new drug applications, abbreviated new drug applications (ANDAs) and certain biologics license applications (BLAs).
The FDA guidance Providing Regulatory Submissions In Electronic Format — Standardized Study Data (1) also notes that the requirement will include ‘all subsequent submissions, including amendments, supplements, and reports’ to the submission types.
With regard to other regulatory agencies position on CDISC, the Japanese Pharmaceuticals and Medical Devices agency ( PMDA) will now request CDISC compliant submissions after October 2016 with a certain transitional period. This will be fully mandatory by 2018. While the European Medicines Agency (EMA) is adopting a top-down approach and therefore more focused on topics such as data transparency, issues of data integration and interoperability will also form part of the EMA’s future plans.
With this in mind, any sponsor planning an NDA, BLA or other regulatory submission needs to make sure they are observing best practice with regards to CDISC. In this blog, we outline some of the key issues to bear in mind as you prepare for your data submission.
Dec 20, 2016 9:21:00 AM
Data Standards play a crucial role in structuring and promoting long term value of clinical data.
Clinical Data Acquisitions Standards Harmonization or CDASH was developed with participation from all three ICH regions (US, Europe and Japan) with recommended data collection fields for 16 domains-> DEMOG, AE etc. It also includes implementation guidelines, best practice recommendations, and regulatory references. There is sometimes a misconception that CDASH defines the layout of the CRF and eCRF. This is not the case. The function of CDASH is to define the naming conventions for the clinical database, and outline how variables are mapped to SDTM. It defines how questions should be formulated for data collection within the CRF and eCRF making use of standard CDISC controlled terminology. In this blog, we will provide an example of CDASH implementation.