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Our Services

Clinical Trials-Real Time Data Review


•        Daily data review

•        Communicate with the site regarding outliers as per MMP

•        Track clinically significant values

•        Assists CRA to resolve queries faster

•        Analyze trends

•        Reminds site for dose reduction or discontinuation of subjects based on clinical findings.

•        Generate, resolve and track queries to address problematic data identified during data review activities and apply proper modification/correction to the database.

•        Work with central laboratories like QNET, Covance, and PPD to facilitate appropriate monitoring and reporting of subject laboratory results.

Prepare safety slides as per sponsor specifications.

Importance of Real-Time Data Review

•        Patient safety is the priority and requires immediate review of adverse events and immediate response.

•        Cost-effective and saves time.

•        Assists in Monitoring and provides available options in making the process more efficient, economical, and easier for both the sponsor and site. Monitoring is estimated to be a third of the clinical trial budget.

•        Real-time review of clinical data assists clinical monitors.

•        Identify missing data and deviations that require immediate action.

•        Reduces PDs

•        Identify trends early

•        Assist in randomization

•        Close eye on Hy’s law and DILI criteria

•        Endpoints analysis

Medical Data Abstraction

  • Clinical data abstraction is the process of converting de-identified unstructured data into structured data by navigating medical records (Electronic or paper) as per client's requirement. This data can be used for secondary purposes.

  • It is entered into pre-defined fields (Defined by clients) so that everyone who needs the data has access to it.

  • Uses

  • Data can be used to identify disease trends, safety of care and quality improvement, cost of care and other uses.


•        Review EMR/EHR records, paper medical records, administrative databases

•        key data points are abstracted.

•        Data fed into electronic files/ Excel

•        QC data sets

•        Final files shared with clients








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