Dr Ben Goldacre, author of 'Bad Pharma' presented a keynote speech at the Clinical Data Live! symposium on clinical data transparency.Read More
Quanticate CRO Blog
Tags: Regulatory Requirements, Good Clinical Practice (GCP), FDA, Electronic Medical Record (EMR), Adverse Events (AEs), Historical Data, European Medicines Agency, Clinical Trial Documentation, Clinical Documents, Ethics, Accessible Data, Data Transparency
This blog provides an overview of efficacy endpoints in oncology studies. We will focus on RECIST (Response Evaluation Criteria In Solid Tumours).This is a method of assessing how solid tumours change over the course of a study. We will cover the measurements taken for RECIST assessments (Target lesions, Non target lesions, New lesions) and the possible outcomes, (complete response, partial response, stable disease, progressive disease) and what they mean – for example; patient recovered, stayed the same or got worse. We will also cover how visit windows and censoring can be handled. How and why measurement methods are important. We will cover other endpoints relevant to oncology such as Overall survival, Objective Response Rate, Best overall response, Disease control at X weeks and quality of life.Read More
On 22 October 2013 the European Parliament agreed to new proposals for regulation on Medical Devices and in vitro diagnostic medical devices. Outdated legislation and high profile scandals have made changes a necessity. This is despite disagreements between legislators and industry over the content of the new legislation. But how will this impact vigilance practices and will it stop medical device scandals from ever happening again?Read More
Bayesian statistics in clinical trials are becoming more widely used in the pharmaceutical industry. By gathering data from historical studies, it is possible to reduce the sample size of the current trial by using an informative prior in the Bayesian analysis. This blog explores five cases in different indications that have historical data on placebo subjects from the literature, and calculates the effective sample size using an informative prior. In some cases, the effective sample size is substantial, but in others there are no sample size savings despite abundant data in the literature.Read More
Today, Big Data is one of the hot topics within almost every Industry, especially in clinical trials. May saw the biggest ever European technologists conference on this, Berlin Buzzwords, while the likes of O'Reilly's Strata conference pull in huge numbers of attendees keen to learn how to adapt to this new world.
European Pharmaceutical Contractor held an interview with Quanticate CEO; David Underwood, asking how he started in the pharmaceutical industry, the reasons behind Quanticate's recent success and future trends as well as regulations in the industry.
Q&A on Data Transparency in clinical trials with Dr Ben Goldacre, Katherine Hutchinson & Kevin Carroll at Clinical Data Live!
Tags: Regulatory Requirements, Good Clinical Practice (GCP), FDA, Adverse Events (AEs), Historical Data, European Medicines Agency, Ethics, Phase 3 Studies, Accessible Data, Phase 4 Studies, Data Transparency
In a case study examined to look at Multiple Imputation (MI) in clinical trials, comparing Active to Placebo treatment (at Weeks 2, 4, 6 and 12 of the trial) in adolescents with acne, drop outs were common. The primary endpoint was the number of lesions at Week 12. The factors believed to affect the propensity to be missing included age, side effects and lack of efficacy, and thus missing data patterns differ between groups.
Tags: Bayesian Statistics, CDISC, FDA, Standardization, Remote Monitoring, Remote Data Capture, Source Data Verification (SDV), Randomization, SAS Programming, On-Site Monitoring, Serious Adverse Events (SAEs), Quality Control, Visualization, Additional Monitoring, Efficient Data Review, Fraud Detection, Patient Safety
Today, the Pharmaceutical industry, like many, has its feet in both camps when it comes to Big Data. Some parts of the industry, such as genomics and drug discovery, were early adopters and today couldn't imagine life without Big Data technologies and approaches. Others are pushing their current approaches to near their limits, and are beginning to consider "what's next?"