Nowadays, more and more studies are being designed to collect information on treatment response at several time points during the treatment period of the study. Although the primary endpoint is often the comparison at the end of the study of the absolute response or of the change to baseline between study treatments, analyses involving intermediate time points in the assessment of treatment effects, e.g., repeated measures modeling, are now widely used.Read More
Quanticate CRO Blog
Functional Service Provider (FSP) relationships are becoming more commonplace within the Pharmaceutical Industry. The aim of such a relationship is a jointly beneficial commercial and financial model which will continually drive improvements in quality and maximise efficiencies and value for the customer. Collaboration is often defined by company and business goals which can be changeable, and has flexibility to evolve as the business develops which strengthens relationships further.Read More
When running a clinical trial the industry standard is a double-blind placebo‑controlled parallel group trial. This is because it is the best way to ensure that the characteristics of subjects in each treatment group are the same, whilst ensuring the investigators cannot anticipate the treatment of a subject.
There are a number of unique challenges that a medical writer might encounter while writing / managing patient / safety narrative projects. This blog describes the scope of narrative projects and outlines the associated challenges and provides some ideas to help you successfully manage narrative projects.
Tags: Case Report Form (CRF), Adverse Events (AEs), Medical Writing, Regulatory Writing, Clinical Trial Documentation, Clinical Documents, Clinical Study Report, Serious Adverse Events (SAEs), Patient Narratives, Safety Narratives, Data Clarification Form (DCF), Quality Control
The third blog post in our “How Total Value Ownership (TVO) can help shape an outsourcing strategy" blog series.
The location of staff within a functional partnership in clinical development was discussed in a previous blog, but this is closely linked to the experience of staff and where the different levels of experience reside. Having a solution primarily focused around graduates in a low cost area vs. a solution based around experienced team members in a higher cost location can have significant impacts on the cost of clinical development projects. It is likely that any proposed solution will incorporate both sides and understanding the exact make-up of the team will provide some insight into what the Total Value Ownership (TVO) is likely to end up being.
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.Read More
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.
Nick Burch, CTO at Quanticate discussed Big Data in Clinical Trials at the 4th Annual Clinical Data Integration and Management conference this year in Princeton, NJ. His presentation is titled: 'The Myth of the Big Data Silver Bullet - Why Requirements Still Matter'
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!
Big Data in Clinical Trials Video
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.
In this recorded presentation a member of the Quanticate's Clinical Programming Team explores the creation of two ADaM datasets; ADPC and ADPP for Pharmacokinetic (PK) Analysis.