We recently conducted a global survey of clinical research sites around the world.
The goal was to better understand the challenges sites face when it comes to tracking, organizing, and managing their study drugs, lab kits, devices, specimen shippers, and everything else their clinical trials require (and the list goes on and on).
Not surprisingly, we discovered that most sites don't actively manage their clinical trial supplies and inventory. The ones that do rely on sticky notes and spreadsheets as their main tools. It's clear to most Study Coordinators why sticky notes are not an ideal long term solution for inventory management, but what about spreadsheets?
Devices and equipment are absolutely essential to the success of a clinical trial. However, their accuracy and precision does tend to shift over time and with repeated use.
This is where calibration comes into play. The goal of calibration is to ensure that any uncertainty in device and equipment measurements are minimized. To do this, measurements made by a device are compared against a reference instrument or standard to check precision, accuracy, and limits.
Clinical research is a team sport. From drug developers to study coordinators to patients (and every role in between) it takes a huge amount of effort and teamwork to help a drug or device achieve commercialization.
In addition to people, clinical trials also require lots of different drugs, devices, lab kits, diagnostic equipment, specimen shippers, and bulk supplies.
Mickella Knapp is a Research Coordinator focused on trial innovations that improve efficiency and patient outcomes. Today she shares her perspective on lab kit supply and how it impact a site’s enrollment and recruitment efforts.
Subject recruitment and retention is unquestionably one of the most important aspects of conducting a clinical research trial.
We are living in the age of information, witnessing the development of the Internet of things, the slow march forward of artificial intelligence, and a renaissance of global communication. All of this is powered by automation. How will this change the world of clinical research?