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Technologies that accelerate and improve Clinical Trials

Digital Health Ecosystem

New technologies are enhancing the efficiency and scope of clinical trials through:

  • Big data and predictive analytics which enable quick identification of promising study subjects and sites
  • Artificial intelligence (AI) processing large amounts of data to help guide patient management and protocol design
  • Electronic health records increasing data collection reach and efficiency, and help better integrate trials into clinical practice
  • Patient-focused technologies, such as mobile sensors and smartphone apps

How patients and developers benefit in a digital health ecosystem

Disruptive Innovation – The Impact

Disruptive Innovation – The Impact

Disruptive innovation is evolving and presenting real solutions but in order to adapt to the emergence of this innovation, companies will need to be more agile and open to learning and dealing with the impact. The barriers of disruptive innovation are forcing pharmaceutical companies and their partners to reshape how they look at everything they do across the entire spectrum of drug development.

New Report: Read the views of three Senior Pharma Executives on how their organisations are approaching innovation.

Artificial Intelligence (AI)

Artificial Intelligence (AI)

In our industry survey and whitepaper, 'Improving Pharma R&D Efficiency' when asked what technologies would have the most impact improving clinical trial efficiency, the top answer from survey respondents was leveraging big data and AI at 36 percent.

Indeed Big Data and AI technologies are complimentary as AI can help to synthesize and analyse ever-expanding data. AI-enabled measures include data integration, data management and interpretation.

They make possible innovations that are fundamental for transforming clinical trials, such as seamlessly combining phase I and II of clinical trials, developing novel patient-centered endpoints, and collecting and analysing real-world data.

Blog: The power of AI to transform clinical trials

Blog: Leveraging Voice-Assistant Technology in Clinical Trials

Digital Health Ecosystem

Real World Data

Late phase research is undergoing rapid transformation due to the impact of healthcare digitalisation and access to ​Real World Data

With the right technology infrastructure and support, sponsors can more completely leverage RWE across the enterprise for maximum value. 

Read our white paper, “On a Technology-Enabled Collision Course: Clinical Research Meets Clinical Practice through Real World Evidence” and learn how to:

Meeting Evidentiary Needs with EHRs

RWD-powered, post-marketing studies require fewer resources and EHRs are an efficient data source to support observational studies. Real World Data from Electronic Health Records can enhance your late phase research studies while decreasing study costs.

Read our whitepaper: Meeting Evidentiary Needs with Electronic Health Records white paper

RWD and Alzheimer's

RWD such as sleep quality and quantity have clinical relevance in Alzheimer's disease. Review the use of wearables in Alzheimer’s disease to provide objective measures of sleep and activity patterns that are not subject to patient recall bias.

Cybersecurity in Medical Devices

Cybersecurity in Medical Devices

Cybersecurity vulnerabilities can emerge in any medical device that is or can be connected to another electronic device and/or network, resulting in potential harm to patients or financial loss for providers, posing major challenges for medical device manufacturers.

Checklist: View the cybersecurity checklist to see how well you're prepared.

Blog: Five Cybersecurity Threats for Medical Device Manufacturers

mHealth & Wearables in clinical trials

mHealth & Wearables

Wearable devices and sensors offer great potential in the collection of richer data and insights to enhance our understanding of the effects of treatment. However, implementing wearables and sensors brings new challenges to clinical trial conduct, data management and interpretation.

BYOD promises greater patient-centricity by enabling patients to conduct assessments using the convenience and familiarity of their own hardware devices. 

Harnessing Blockchain Technology and Digital Disruption

Blockchain technology allows for complete transparency of data, which has immense potential within clinical trials. Blockchain ledgers allow for user confidentiality, so patient privacy can be protected during exchange of data between parties - patient data is the most notable item of transactional nature between networks such as healthcare institutions, patients, and regulators.

Disruptive Innovation – The Impact

ICON Explores Quantum Computing

Improving Trial Designs for Heterogeneous Populations

Accurately projecting outcomes for diverse patient populations – from the wealth of genomic, phenotypic and outcomes data available through genome sequencing and electronic health records – holds the potential to transform the effectiveness and efficiency of drug and medical device development.

Quantum computing may enable statisticians to quickly explore, understand and interpret these enormous multivariate and often poorly structured data.

ICON is actively exploring this new field of quantum computing, and in spring 2017 co-sponsored a quantum computing workshop.

What’s happening in ICON