LIMS Connectivity in the CDMS

AUTO-POPULATING CENTRAL LAB RESULTS WITH A LIMS INTERFACE

FEATURES

LIMS Translation Interface
  • Agnostic LIMS connections
Auto-Populate Lab CRFs
  • Lab panels are delivered via the LIMS interface to the EDC
  • Real-time population of lab data into the study CRFs
  • Dynamic lab-based normal values (configurable)
SDV Not Required
  • Direct data pull from central lab with internal source and data validation
  • PI can sign the lab form in the EDC
Incorporate Lab Panel Accessioning
  • Use barcode/QR code scanner form
  • Add CRF to scanning form

Lateral Flow assay Test Processing1

  • Integrate LFA Capture into the CDMS and laboratory LIMS
1 US Patents : 11281194, 11500359
Q&As
A Laboratory Information Management System (LIMS) is a software system used to manage and track laboratory data, samples, and processes. LIMS systems are commonly used in a variety of industries, including medical and clinical research, pharmaceuticals, biotechnology, and environmental analysis. 
The main goal of a LIMS is to provide a centralized repository for laboratory data, samples, and processes, allowing laboratory staff to access and manage information more efficiently. Some of the key features of a LIMS include sample tracking, data management, process automation, and reporting capabilities.
LIMS systems can help improve the accuracy and efficiency of laboratory operations by automating manual tasks, reducing the potential for errors, and providing real-time access to data and sample information. This can help ensure that laboratory processes are more consistent and that data is more reliable and usable.
The difficulty of connecting to a Laboratory Information Management System (LIMS) can vary depending on several factors, such as:
  1. Technical Expertise: Connecting to a LIMS may require technical expertise in programming, database management, and system integration. The level of difficulty may depend on the complexity of the LIMS system and the resources available for development and maintenance.
  2. Compatibility: The level of difficulty in connecting to a LIMS may also depend on the compatibility between the LIMS and other systems, such as Electronic Data Capture (EDC) systems, that need to be integrated.
  3. Data Format: The difficulty of connecting to a LIMS may also depend on the format of the data that needs to be transferred. Different LIMS systems may have different data formats and requirements, which may impact the ease of connection.
  4. Documentation and Support: The level of documentation and support available for the LIMS system can also play a role in the difficulty of connecting to it. If the system has comprehensive documentation and a robust support network, it may be easier to connect to it than if there is limited documentation and support.
In general, connecting to a LIMS can be challenging and may require technical expertise and resources. However, with proper planning and resources, connecting to a LIMS can bring several benefits, including improved data management, increased efficiency, and enhanced data quality.
A direct connection between a Laboratory Information Management System (LIMS) and an Electronic Data Capture (EDC) system can bring several advantages, such as:
  1. Improved Data Quality: A direct connection between LIMS and EDC eliminates the need for manual data entry, reducing the potential for errors and ensuring accurate data transfer between the two systems.
  2. Enhanced Efficiency: With a direct connection, data can be automatically transferred between the two systems in real-time, reducing the time and effort required to manage the study data.
  3. Better Data Integration: A direct connection between LIMS and EDC allows for seamless integration of data from both systems, providing a comprehensive view of study data.
  4. Increased Productivity: By automating the data transfer process, a direct connection can help increase productivity and reduce the workload of study staff.
In conclusion, a direct connection between LIMS and EDC can improve the efficiency, accuracy, and quality of study data management.