Learn how unparalleled data, domain expertise, and technologies enable AI-powered solutions that are purpose-built for healthcare.
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn moreDeveloping IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn moreDeveloping IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn moreDeveloping IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn more"We strive to help improve outcomes and create a healthier, more sustainable world for people everywhere.
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SEE LATEST REPORTSBy making intelligent connections between your needs, our capabilities, and the healthcare ecosystem, we can help you be more agile, accelerate results, and improve patient outcomes.
LEARN MOREBuilding on a rich history of developing AI for healthcare, IQVIA AI connects the right data, technology, and expertise to address the unique needs of healthcare. It's what we call Healthcare-grade AI.
LEARN MOREYour new expert analyst is here. Be at the forefront of data-driven decision-making with a new generative AI tool that enables you to interact with our products and solutions like never before. Get results you can trust, faster.
LEARN MOREThe IQVIA Human Data Science Cloud is our unique capability designed to enable healthcare-grade analytics, tools, and data management solutions to deliver fit-for-purpose global data at scale.
LEARN MOREThe IQVIA Innovation Hub connects start-ups with the extensive IQVIA network of assets, resources, clients, and partners. Together, we can help lead the future of healthcare with the extensive IQVIA network of assets, resources, clients, and partners.
LEARN MOREIQVIA Decentralized Trials deliver purpose-built clinical services and technologies that engage the right patients wherever they are. Our hybrid and fully virtual solutions have been used more than any others.
LEARN MOREEmpowering patients to personalize their healthcare and connecting them to caregivers has the potential to change the care delivery paradigm.
LEARN MORE"At IQVIA your potential has no limits. We thrive on bold ideas and fearless innovation. Join us in reimagining what’s possible.
VIEW ROLESAlzheimer’s disease is both a devastating degenerative brain disorder and the most common type of dementia. About 5.7 million Americans live with Alzheimer’s today and a new person is diagnosed with the disease every 65 seconds (1, 2). Elderly Americans are more afraid of developing Alzheimer’s or dementia (35%) than cancer (34%) and for good reason. The prognosis is not good, but the future is hopeful when human science meets data science. When scientific expertise and advances in data analytics and innovative technologies—like predictive analytics and machine learning—come together, we can ask better questions and extract more meaningful insights about Alzheimer’s disease, while proactively creating a more accurate and predictable picture of the patient pipeline, identifying patients earlier in the diagnosis, optimizing study planning and speeding time to market.
In this white paper, you will:
More than 100 Alzheimer’s agents have failed clinical trials since 1998, and early Alzheimer’s trials have a high screen failure rate of about 75%. Only five agents have ever been approved: tacrine (later withdrawn for safety), donepezil, rivastigmine, galantamine, and memantine. Unfortunately, they are only able to provide a moderate symptomatic relief with no impact of disease progression.
Dozens of unsuccessful trials have provided some lessons, which are important to understand since at least 112 potential agents to treat Alzheimer’s and its symptoms are currently in clinical trials.
First, for drug development efforts, it is critical to target Alzheimer’s pathology as early as possible before the onset of dementia to lessen the disease’s effects. Amyloid deposits and other brain changes associated with Alzheimer’s appear more than 20 years before the onset of clinical symptoms. As per Alzheimer’s Association, earlier diagnosis (even with no disease-modification treatment yet available) may also save $7.9 trillion in healthcare costs in the US alone (1, 2).
Second, it is critical to enroll a well-defined patient population using biomarker confirmation of diagnosis.
In addition, because most agents currently under trial are monoclonal antibodies (mAbs), the blood–brain barrier poses a substantial challenge. These challenges translate into four concerns:
Learn how unparalleled data, domain expertise, and technologies enable AI-powered solutions that are purpose-built for healthcare.
Change the model of clinical research by integrating data, expertise, analytics and technology from study design through execution to power better decisions.