During my time in the life science industry I have learnt a lot of SAS techniques through attending training sessions, however some of the best SAS tips I have picked up were from other programmers: for instance when asking for advice on a coding problem or running programs written by colleagues. I found there are many simple SAS® tips you can use in your day to day SAS programming. This blog will provide explanations and examples of four of these.
The second blog post in our “How Total Value Ownership (TVO) can help shape an outsourcing strategy" blog series.
Project costs in clinical development partnerships can be influenced significantly by the location of staff since salary levels differ widely depending on where the staff members are located. The percentage and mix of staff in different locations can provide a cost-effective solution, but it can also provide a solution that compromises quality if the mix is not right. Whilst the initial costs may decrease and help to build a business case, the Total Value Ownership (TVO) may not look so attractive when taking into account the oversight and other costs associated with the deliverables. Any projects that move off their critical paths can also have significant impacts to the overall TVO, particularly if this results in delays of submissions and ultimately launch.
We've all heard the hype - Big Data will solve all your storage, processing and analytic problems effortlessly! Some moving beyond the buzzwords find things really do work well, but others rapidly run into issues. The difference usually isn't the technologies or the vendors per-se, but their appropriateness to the requirements, which aren't always clear up-front.
Big Data, and the related area of NoSQL, are actually a broad range of technologies, solutions and approaches, with varying levels of overlap. Sadly it's not just enough to pick "a" Big Data solution, it needs to be the right one for your requirements. In this talk, we'll first do a whistle-stop tour of the different broad areas and approaches of the Big Data space. Then, we'll look at how Quanticate selected and built our Big Data platform for clinical data, driven by the needs and requirements. We won't tell you what Big Data platform you yourself need, but instead try to help you with the questions you need to answer to derive your own requirements and approach, from which your successful Big Data in clinical trials solution can emerge!
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.
The first blog post in our “How Total Value Ownership (TVO) can help shape an outsourcing strategy" blog series.
Total Value Ownership (TVO) is not a new concept but it is an area that has attracted much interest in recent years. It can help in determining the best approaches to take and suppliers to use, by demonstrating the real value of selecting a certain partner in clinical development.
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.
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?
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.