Clinical Data Management Services

Clinical monitoring of therapeutic drugs and medical procedures is an effective way to improve the level of medical care, so accurate clinical feedback must be provided to explain the monitoring results. Creative Biolabs provides customers with a full range of clinical testing services by establishing an interdisciplinary team consisting of medical technology experts, clinical analysis experts, pharmacologists and data analysts. You can use our services for clinical data management, statistical analysis and quality control.

Clinical Data Management (CDM)

CDM is a key step in clinical research and can help healthcare professionals extract high-quality, reliable, and statistically sound data from clinical trials. CDM can greatly reduce the time from drug development to market. With rich expertise, the CDM team of Creative Biolabs offers comprehensive CDM services to help customers maintain the quality standards of the CDM process, from the beginning of the project to all stages of clinical trials. During the trial, we regularly evaluate various procedures in the CDM, including the number of case report form (CRF) designs, database design, data verification, and difference management. In the current situation, there is an increased demand to improve the CDM standards to meet the regulatory requirements and stay ahead of the competition by means of faster commercialization of the product. By implementing data management tools that comply with regulatory requirements, our CDM team can meet these needs.

Clinical information network data management framework.Fig.1 Clinical information network data management framework. (Tuti, 2014)

CDM Services at Creative Biolabs

If you need or have questions about our clinical trial testing services, you can contact us for more details.

Reference

  1. Tuti, T.; et al. Innovating to enhance clinical data management using non-commercial and open-source solutions across a multi-center network supporting inpatient pediatric care and research in Kenya. Journal of the American Medical Informatics Association. 2016, 23(1): 184-192.
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