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.
Scientists hypothesize, but cannot definitively prove, that tangles of tau protein and build-ups of beta-amyloid plaque contribute to the hallmark cognitive decline of Alzheimer’s disease. Without a definitive cause or diagnosis – and no cure in sight – many aging adults see no reason to assess their risk, or determine their cognitive status, if little can be done to stave off the disease. Perceptions such as these present a growing challenge to Alzheimer’s research. Understanding these clinical research barriers is critical to developing strategies to overcome them.
Typically Clinical Research Organisations (CRO’s) involvement in the Clinical Trial process has centered on site management in terms of identifying potential sites and managing patient recruitment.
Standard Operating Procedures (SOPs) have long been fundamental to many industries, and the clinical trials sector is no exception. With the advent of the Good Clinical Practice Guideline in 1996 from the International Conference on Harmonisation (ICH-GCP), stakeholders have been motivated to develop SOPs, not only for regulatory compliance, but also as a routine business practice. Yet, too often, after companies devote significant time and resources into creating SOPs, they may not be followed.
Quality management and competitive edge are vital to the clinical trials sector and are fueling widespread use of purpose-built technology. Cloud-based solutions, such as clinical trial management systems (CTMS) and the electronic trial master file (eTMF), are broadly accepted, but these tools fail to address study startup (SSU), a complex set of processes that contribute heavily to lengthy timelines, often lasting seven years. With greater globalization of clinical trials and factors ranging from site selection to regulatory document submission to enrolling the first patient, assessing SSU status is critical. It pinpoints bottlenecks and areas of risk that could impact data quality and derail study budgets and timelines.
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