ABOUT

Remarque Systems provides a single, easy-to-use, and effective platform to manage all of your clinical trial data. Remarque Systems brings all your data from different sources together in real time; delivers end-to-end visibility and oversight with data-driven analysis, monitoring, and risk assessment; and drives better-informed decisions with clear and conclusive analytics, reports, and visualizations. By consolidating your data on one powerful platform, Remarque Systems brings process optimization, increased visibility, rapid communications, and improved quality to your clinical trials. 

CONTACT INFORMATION

Remarque Systems

3800 Paramount Parkway, Suite 3, Room 3-01

Morrisville, NC 27560

UNITED STATES

Phone: 919-261-5830

Contact: Debbie Aoyagi

FEATURED ARTICLES

  • Discover why a unified CTMS platform is the answer for managing both the clinical trial itself and the data it produces when it comes to poorly integrated clinical trial management systems (CTMS).

  • Explore the solution for adequately verifying and analyzing data from wearables, remote devices, and other novel data collection modalities. 

  • The new processes and technologies that DCTs require may offer advantages to nimble small and midsized biotechs that are free to select the best solutions.

  • As decentralized clinical trials (DCTs) gain ground, small to midsized sponsors face new challenges—many of which can be solved by technology.

  • Gain insight into how a combination of consulting and technology enabled a CRO to reduce the time and cost of a clinical study so that the team could take quick action to reduce risk and improve patient safety.

  • In this case study, discover the complexity that decentralized clinical trials (DCTs) may add to patient enrollment and retention due to the lack of interaction between patient and trial personnel.

  • Clinical trial monitoring has remained grounded in on-site source data verification: a costly, time-consuming process that does not address risk or site performance data. It’s time for that to change. Find out why data literacy is the change agent.

  • As the inter-relationship of race, socioeconomic status and healthcare outcomes has begun making international headlines, achieving clinical trial diversity has surfaced as a priority in successful trial conduct.

  • Over the past decade, there has been a gradual uptick in the popularity of decentralized clinical trials (DCTs).  As you consider clinical operations platforms, explore the key features to help simplify DCT management and ensure success.

  • Anyone who has run a clinical trial knows that having data and having actionable data are not the same. Only by arming teams with the ability to analyze data on the fly can you wrest all the value it has to offer.

  • As an industry, we are drowning in data, but is the abundance of data being effectively used? Uncover the importance of building a data-driven organization and the steps to embedding data into an organization’s identity.

     
  • An established biotechnology company needed a technology partner to support them in implementing risk-based quality management and providing greater visibility into their data. In this case study, learn a risk-based approach with data visualization and communication that dramatically increased output and time savings.

  • A leading pharmaceutical company was poised to begin phase 3 trials for a potential therapy for COVID-19, testing in patients with symptomatic COVID-19 infection. Every moment mattered. Yet traditional methods—involving consistent in-person interaction—were clearly not viable.

  • With an eye on speed, safety, and efficiency, CROs and sponsors are employing software that offer enhanced capabilities for identifying risks in clinical trials. The broad category of such systems is often referred to as riskbased monitoring (RBM) technology. But even though such systems introduce new monitoring capabilities, too many fall short of delivering the full benefits of RBM.

  • In this white paper, we discuss how to build a foundation prior to technology implementation. We also explore key factors to consider during implementation and strategies for operational execution after implementation.

  • In an environment where the volume, velocity, and variety of study data generated are increasing exponentially, machine learning algorithms are poised to become indispensable tools for safer, more efficient clinical trial management. And yet, adoption of machine learning-driven RBM technologies has been slow.

  • RBQM is a more substantial undertaking, requiring quality, reliability, and interpretability. Regulators want to see clinical trials implementing this approach. Yet, sponsors and contract research organizations (CROs) are finding it challenging. It doesn’t have to be.

  • With governments everywhere asking people to practice social distancing or shelter in place, monitors are not able to get to sites—and clinical trial subjects aren’t able to get to investigators—creating a challenge for both data collection and monitoring. This threatens to derail trials at all stages, as well as potentially putting trial subjects in harm’s way. It doesn’t have to be this way.

  • In this white paper, learn how a lack of timely data can create catastrophic setbacks, how new technology solutions can speed insights, enhance safety, and produce cost-savings, and how real-time data synthesis and analysis can revolutionize clinical trials.

  • Three decades ago, an international committee came together to create a revolutionary document designed to improve the efficiency of new drug development. Explore how its revised version, ICH E6 (R3), maximizes efficiencies and facilitates innovations in clinical trials.