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Communication and transparency are required for efficient clinical trials, but how can you do this when you’re working with multiple external partners all using different systems with inconsistent reporting conventions?
Analyze Cloud Service provides intelligence, presenting timely status updates across your studies and insights to streamline operational processes. Through visually rich analytics and dashboards, we help transition your team from a process that is reactive to one that is more proactive.
Oracle Health Sciences empowers our visibility into the traditionally cumbersome process of activating investigative sites for clinical trials. We can ‘at-a-glance’ track milestones and associated activities on the critical path and view the end-to-end deliverables, allowing us to navigate sites successfully through the start-up phase to the point where patients can be enrolled. Additionally, capturing robust clinical and operational data allows us to enhance our predictability model for forecasting.
Learn how machine learning technologies can help predict outcomes in clinical trials, leading to faster drug approval times and lower costs.
Learn how to overcome the complexities introduced in outsourced studies (e.g., quality, oversight, collaboration, and governance).
Learn how entrenched silos have stymied data flow efforts due to minimal understanding of what is needed downstream.
Drive competitive performance and operational excellence by focusing on bottlenecks and processes ripe for optimization.
Learn how good clinical practice (GCP) guidelines and systems help improve overall study quality.
Learn how contemporariness can be defined in operational SOPs and implemented in daily operations to ensure audit readiness.
Learn how to tackle the challenge of improving budget and contract cycle times in starting clinical trials.
Discover how to combat poor risk management practices that have fueled the rescue study industry.
Hear how eClinical technologies and industry initiatives are impacting the ability of investigative sites to conduct clinical trials.
Learn how to mitigate the patient and data quality risks associated with decentralized clinical trials.