Knowledge and Experience of Electronic Data Capture (EDC) Especially Inform EDC
Over 7 years of experience in operational and clinical data management encompassing all phases of clinical development in the fields of pain, metabolic disorders, obesity and oncology
Knowledge and experience of Electronic Data Capture (EDC) especially Inform EDC
Experience in database management and Adverse Event/Serious Adverse Event coding with MedDRA
Perform Data entry, review and validation,
Involved in CRF design, creation, and review,
Query generation and resolution (SQL Commands)
I was involved during vendor selection and management
Selecting contract research organization, Site Management Organization (SMO), Central Lab, clinical trial Data Monitoring Committee (DMC)
- Selecting contract research organization (According to 21 CFR 312.52: Transfer of obligations to a contract research organization) - A sponsor may transfer responsibility for any or all of the obligations set forth in this part to a contract research organization
- Quick institutional review board (IRB) submission and documentation
- • Completion of all regulatory, budgets and contracts within 5-7 working days
- • Accurate on-time specimens, data and case report forms collection
- • Fast and complete enrollment of appropriate subjects
- • One of the highest subject retention rates in the industry
- • Complete and conduct 100% verification of case report forms within 2 weeks after the last study event
- • Experience with EDC (electronic data capture)
SMO Companies
Site Management Organization Companies are listed below:
1. SMO- USA
2. Florida (Aventura): International Physicians Research
3. Florida (Miramar): Comprehensive Clinical Development
4. Illinois (Chicago): Excel Life Sciences
5. Illinois (Chicago): Investigator Support Services, Inc.
6. Minnesota (Minneapolis): DaVita Clinical Research (DCR)
7. New Jersey (Metuchen): MaxisIT Inc.
8. North Carolina (Winston-Salem): PMG Research, Inc.
9. Ohio (Cincinnati): Radiant Research
10. Ohio (Columbus): Remington-Davis Clinical Research
11. Wisconsin (Middleton): PharmaSeek
12. Canada (Toronto, Ontario): Trial Management Group Inc.
13. India (Noida - 201 301): Excel Life Sciences
14. Singapore (Singapore): Fortitude Clinical
Role of central labs in clinical trials are as follows.
• It acts as provider for all necessary materials (sample collection kits, sample storage materials, sample shipping materials and all relevant types of instructions).
• act as logistics coordinator for both incoming and outgoing shipments
Few Central Lab Companies
• ACM Global Central Laboratory
• Synevo Central Lab
• BARC
• PPD- Central LEB
• ICON-Central lab
• Quintiles- Q labs
• Covance- Central Lab
clinical trial Data Monitoring Committee (DMC)
The selection of DMC members is extremely important, as DMC responsibilities relate to the safety of trial participants.
imaging core lab (ICL) is now a standard part of the team of the vendors in clinical trials.
Perform Data entry, review and validation,
Involved in CRF design, creation, and review,
Query generation and resolution (SQL Commands)
· Identifying Discrepancies “edit checks”
missing values, simple range check, and inconsistency detection categories
o Manual Review
o Automatic Checks
o External System Checks
· Managing Discrepancies
For a study of medium complexity with several or many sites, we can very roughly estimate one discrepancy per CRF page. Among them, 60% to 70% will be resolved internally by inspection of the CRF and related data.
Once new discrepancies have been thoroughly reviewed, those that have not been resolved internally will require site resolution. These will be sent to the appropriate site; usually on a special form we will call a query form, or "Discrepancy Clarification Form" or "Data Correction Form."
· Data Cleaning as a Process
o Screening Phase
Checking of questionnaires using fixed algorithms.
2. Validated data entry and double data entry.
3. Browsing of data tables after sorting.
4. Printouts of variables not passing range checks and of records not passing consistency checks.
5. Graphical exploration of distributions: box plots, histograms, and scatter plots.
6. Plots of repeated measurements on the same individual, e.g., growth curves.
7. Frequency distributions and cross-tabulations.
8. Summary statistics.
9. Statistical outlier detection.
o Diagnostic Phase
In this phase, the purpose is to clarify the true nature of the worrisome data points, patterns, and statistics. Possible diagnoses for each data point are as follows: erroneous, true extreme, true normal (i.e., the prior expectation was incorrect), or idiopathic (i.e., no explanation found, but still suspect).
o Treatment Phase
After identification of errors, missing values, and true (extreme or normal) values, the researcher must decide what to do with problematic observations. The options are limited to correcting, deleting, or leaving unchanged.
· Edit Checks
• Missing values (e.g., dose is missing)
• Simple range checks (e.g., dose must be between 100 and 500 mg)
• Logical inconsistencies (e.g., "no hospitalizations" is checked but a date of hospitalization is given)
• Checks across modules (e.g., adverse event (AE) action taken says "study termination" but the study termination pages does not list AE as a cause of termination)
• Protocol violations (e.g., time when blood sample is drawn is after study drug taken and should be before, per protocol)
1) Research subject received wrong treatment or dose.
2) Subject did not meet inclusion criteria but was not withdrawn from the study (e.g. age requirements, certain health conditions, test results out of specified range etc.)
3) Research subject received an excluded, concomitant medication.
4) Breaches of confidentiality.
5) Missed oral medications, not relating to treatment of toxicities, or a missed day of treatment with continuous therapy.
6) Failure to obtain informed consent prior to initiation.
7) Failure to report Adverse Event.
o Missing Data Identification
o Consistency Checks
o Protocol Deviation and Violation
o Data Reconciliation
· Data Validation
The planning stage of a project is vital to understanding what the expectations are for the project. Documents generated or reviewed during the planning stages of a project may include:
1) Project-specific planning documents (For example, QA Project Plan or a SAP);
2) Program-wide planning documents (For Example, Quality Management Plan);
3) SOPs including field and laboratory methods for any aspect of the data generation process; or
4) Published, approved sampling or analytical methods (For Example, SW846 methods or American Society for Testing and Materials protocols).
