Reinventing Life Sciences Innovation
Fragmented data assets, limited access to clinical information and long timelines are limiting factors for life science organizations striving to innovate. At MDClone, we understand that gaps and limitations in data impact discoveries, outcomes, and revenue.
MDClone connects life science organizations to rich patient data needed to test hypotheses, build models, validate studies, develop clinical trials, improve care optimization, and create life-saving therapies. Through a secure and controlled platform with embedded synthetic data technology, life science organizations are able to identify sites, analyze robust structured and unstructured real-world data, and explore populations of interest with incredible detail and flexibility.
The Global Network is an international, member-driven collaborative of leading healthcare systems determined to improve patient care. Through the power of community, these organizations are striving to shape the future of health and wellness with rapid, data-driven learning, collaboration, and innovation at the forefront.
With The Global Network’s world-class healthcare systems, life science organizations have access to large data sets, partnerships, information, and expert teams.
Leverage MDClone’s powerful synthetic capabilities to explore robust synthetic data — preserved either longitudinally or in context — to get the information needed without barriers or limitations.
Determine if subject populations are sufficient before committing to traditional data access processes. Query, adjust, and analyze populations of interest to build out projects with confidence.
By accessing real-world data from the source, inside a health system, life science organizations can identify promising patient cohorts for post-marketing analysis.
After exploring synthetic data, validate results against original data to verify conclusions for submission, publication, or patient care.
Quickly identify descriptive variables of interest along longitudinal patient timelines to understand the utilization of care for specific disease groups.
Define cohorts of patients with particular diseases and utilize synthetic data sets to examine the entire patient journey in order to recommend earlier intervention protocols. Build multivariate prediction models and develop risk scores based on findings.
Ensure patients are receiving optimal treatment by understanding and disseminating information about guidelines for new and in-line medications.
Dynamically apply inclusion and exclusion criteria for clinical trials against real-world patient populations to estimate the size of the potential subject pool, time to complete recruitment, and unanticipated confounders in the population.
Develop tools, applications, and services for clinical decision support to identify gaps in care, missed diagnoses, failures in compliance, and suboptimal treatment plans.
Within seconds, view an estimate of the patient cohort size to understand the potential subject population and site criteria. Further define and refine exclusion and inclusion criteria with details only available through synthetic data.
With real-world evidence and robust data at your fingertips, confidently move forward with research and projects of interest. Answer complex healthcare questions quickly, explore data on-demand, and seamlessly interact with all data elements within the confines of a use case.
Join the largest network of global health systems committed to working together to accelerate innovation and improve patient care.
Together, these organizations understand that shared insights, teamwork, and research partnerships are key to shaping the future of health and wellness.
With patient privacy and security at the forefront, the Connect Platform enables dynamic data access and project collaboration between multiple organizations with controls in place to ensure privacy for patients, security for healthcare systems, and protections for insights generated by life science organizations.
Rather than utilizing traditional de-identified data, users access synthetic data, which provide researchers with artificially created, computationally derived data that replicate the statistical characteristics and correlations of real-world data.
Because synthetic data is created as a brand new dataset, the risk of de-identification of individual patients is not possible. Synthetic data enables maximum data utility while maintaining patient privacy.
Connect with our team and discover how MDClone can unlock the power of dynamic data exploration for life sciences.