RTSM software developed with an agile methodology and built on a modern technology stack dramatically accelerates the study start-up process and mid-stream adjustments. Customers are able to see and interact with the system before approving specifications and changes can be made quickly, without impacting study progress. The use of agile software in clinical trials enables customers to streamline internal processes and spend time on other high-value activities critical to the success of their studies.
There is a dazzling array of quality initiatives within the clinical trials sector all looking to move the needle from paper-based methods or single point solutions to a more integrated, non-siloed approach to study conduct. These efforts, may be rooted, at least somewhat, in work started nearly 20 years when the Institute of Medicine published To Err is Human, a call-to-action to improve safety in our healthcare system by linking it to greater quality. That seminal work was followed by various reports recognizing the urgent need to transform the clinical trials enterprise by focusing more intently on quality, which leads us to today’s sharp focus on this subject.
The sharpening focus on quality management is fueling greater use of standardized metrics to optimize clinical trial performance. Stakeholders are embracing this trend through growing adoption of cloud-based technologies, such as clinical trial management systems (CTMS), source data, and the electronic trial master file (eTMF). The information they generate is flowing into data analytic tools, and with this capability, standardized metrics are gaining mainstream status.
The trend toward increasing the diversity of clinical trial participants is encouraging, but a continued effort is needed to keep moving in the right direction.
From leisure activities, to our own health and wellness, to the industries in which we work — Big Data has transformed our world. Subscription-based content providers, like Netflix and Amazon Prime, are changing television programming by using detailed customer segmentation and viewing habits to rethink how new programming is funded, produced, and released to the market. Everyday items like Nest are transforming home heating and cooling by collecting and aggregating sensor data to automate thermostat changes.
The life sciences industry is repeatedly cited as the most at-risk for a major security breach. Many assume that the greatest threat comes from outside: malicious parties that are actively working to compromise company information. While this certainly reflects the new normal in cybersecurity - for example, see Pfizer's recent U.S. Securities and Exchange Commission (SEC) filing acknowledging that their IT systems are subject to frequent attacks – the unfortunate reality is that most information security breaches start with insecure data sharing.
Immunotherapies are being touted—both in scientific literature and the general media—as the most promising advances in cancer treatment in decades.
This paper isolates three specific areas that warrant close attention for app developers, clinical trials sponsors and CROs designing trials powered with mHealth app tools: technology considerations, data considerations and regulatory considerations. These areas are vital to developing a compliant trial that generates meaningful data for clinical development using mHealth sources.
Understanding patient reported outcomes (PROs) in oncology clinical trials enables researchers to develop more effective treatments for patients battling this illness. But if it isn't easy for patients to report their health data, they won't - so it must be accessible for them.
Clinical protocols are increasingly relying on clinical outcome assessments to prove efficacy and safety. COAs are collected electronically for many reasons, and in today’s clinical environment, electronic collection is becoming more common. This document provides scientific evidence and operational proof that patients prefer electronic data collection in clinical trials, while providing a fundamental eCOA education. An objective review of reliable eCOA collection modalities is presented. Several case studies are summarized, providing scientific evidence of patients preferring electronic data collection in clinical trials. A Guide to eCOA and Integrated Medical Devices Selection is also included in this document.
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