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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 trusted collaboration is key to keeping sponsor-CRO partnerships aligned on shared goals.
Learn how the focus on efficiency in ICH E6 (R3) will fundamentally change clinical trials.
Learn how machine learning can help identify and rectify systemic inefficiencies, allowing life science organizations to learn and adapt.
Learn how the collaboration between Cognizant and Oracle eliminates redundancy for sites and deliver better outcomes from sponsors/CROs.
Will the industry embrace this change or revert back to its old ways post-COVID-19?
Learn how vendor oversight can be implemented end-to-end, ensuring compliance with ICH regulation guidelines.
Learn how to gain critical operational insights by using AI/machine learning to transition from subjective decision making.
Learn how digital transformation roadmaps were accelerated to embrace innovative approaches to overcome adversary.
Learn how fundamental to new ICH guidelines is the modernization of processes and technology with a focus on QbD and risk-based management approaches.
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.