The primary aims of Phase 1 Clinical Trials are to determine the safety, tolerability and pharmacokinetics (PK) of a compound. Trials have historically been conducted in the logical sequence of single ascending dose, multiple ascending dose, examination of preliminary effect of food on exposure, and potential drug-drug interaction, with assessments to determine the effect of gender, age, bioavailability and bioequivalence performed as necessary.
This blog explores the statistical methods used in Risk Based Monitoring (RBM) and how the result of such statistical methods enables improved data integrity across a clinical trial.
Within the last few decades the number and complexity of clinical trials has increased considerably, not only across the industry but within individual companies. With this increase comes the enhanced pressure of effectively monitoring these trials.
![[Published Journal] Using Observational Studies to Investigate the Relationship Between Fatigue and Work Disability - Featured Image](https://www.quanticate.com/hubfs/observational%20studies%20fatigue%20work%20disability.jpg?t=1540296858454)
Our Statistical Consultancy Team recently collaborated on a study to investigate the long-term relationship between fatigue and work disability in patients initiating treatment with etanercept for rheumatoid arthritis (RA) or ankylosing spondylitis (AS); and this work has now been published. (https://arthritis-research.biomedcentral.com/articles/10.1186/s13075-018-1598-8)
At the July 25th PhUSE Webinar Wednesday, Ethan Chen (Director, Division of Data Management Services and Solutions Office of Business Informatics, FDA CDER) gave us a glimpse of the FDA’s view on Technical Rejection Criteria for Study Data. Those that were at the US Connect Conference earlier in the year may have seen this already.
Food ingredient and nutraceutical manufacturers are increasingly looking to market their products by substantiating their unique health benefits.
There are many generic, widely used claims - in the EU, Article 13.1 of the European Food Safety Authority’s (EFSA) EC Regulation permits manufacturers to use some 4,6371 that pertain to vitamin and mineral content.
This proliferation is driving manufacturers to develop unique claims to use in marketing efforts, which in turn has led to a significant growth in demand for nutraceutical trials.
The BAYES 2018 Bayesian Biostatistics workshop took place from the 20th to the 22nd of June, and was an extraordinary chance to discuss how Bayesian methodology can be used within the pharma industry.
![[Video] Bayesian Methodology - How to Analyse Multiple Endpoints - Featured Image](https://www.quanticate.com/hubfs/Artwork%20Statistical%20Knowledge%20Share%20January.jpg?t=1540296858454)
In this Statistical Knowledge Share Video our Principal Statisticians, Sonia, presents an example of Bayesian Methodology using simulated data and examines how to analyze Multiple End Points in Clinical Trials.
The laboratory dataset is one of the core safety datasets and, at first glance, it could appear intimidating, with multiple tests and visits per patient. This article will illustrate checks that are worth applying at the very beginning of programming work – these could be in addition to the standardized process of domain validation.
Clinical Trial Management Systems (CTMS) are an important part of every clinical trial. Selecting the right CTMS helps address inefficiencies on the operational side of research, such as clinical trial planning, preparation, performance and reporting. As more and more pharma and biopharma sponsors start to recognize the potential opportunities that exist with EDC-CTMS integration, there is a growing need to address the complex process of electronic data capture (EDC) implementation.
