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TrackREX: Track and reconcile non-CRF data including biosamples, labs or ECG with EDC-derived datasets. Reconciliation is automated with an intuitive and streamlined approach. 

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TrackREX is a re-engineered solution that is based on a previously released PK (pharmacokinetic) reconciliation tool. It comes with numerous enhancements and has evolved into a module-based solution allowing clients to only deploy those functions that are required at study level. Whilst the entry modules are based on tracking and reconciling of data, additional modules can be added throughout the life-cycle of a study.

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TrackREX takes a typical approach to reconciling data from different sources (see below), whilst the functionality within the tool allows for a much more refined experience for end-users:

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1) Data inputs from any data source and with no restriction by EDC platform or data type (accepts RAW/SDTM).

2) The 'matching process' (reconciliation) is performed automatically with any mismatches identified.

3) The final output shows the end-user discrepancies and any potential errors with suggestions for resolution. An added bonus is that TrackREX will retain all user actions and any associated comments for inclusion in future report outputs.

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TrackREX versus  Laboratory Information System (LIM)

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Whilst LIMs have long been regarded as ultimate solution for tracking and reconciling lab data, they often fall short of being able to do this effectively. Typical issues associated with a LIM:

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• Difficult to implement and maintain

• Costly to purchase and service (overly complex, steep learning curve)

• System is slow (often due to associated amounts of data from various inter-connected systems)

• Resistance by adopters (Different parties along chain of custody use multiple incompatible systems)

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Overall result: ‘Back to square one’:

• Manual tracking of Samples are tracked at multiple points along the chain of custody with numerous tracking sheets being referenced

• Clerical (human) error prone recording (e.g. no scanning of barcode labels)

• No automated tracking!

• Samples are lost, inaccurate labelling = lost data!

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LIMs, with their associated issues and lack of full adoption means that there is often a shortfall when it comes to dealing with both the tracking of samples and reconciliation of the associated data. TrackREX will never replace a LIM,  but will function independently of all systems and plug any of the real-world shortfalls which are typically tracking and reconciliation of sample data.

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TrackREX functionality

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Setup requires no programming

Typically PK reconciliation is performed by using SAS to import EDC and PK datasets and programmatically compare data fields that are captured in both datasets. This requires a SAS programmer and DM to collaborate with agreed specifications. To arrive at an effective solution can prove expensive and time consuming. At the end of the exercise, the result is still a flat file that needs manual review (and most likely further programming tweaks down the line). 

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Flexible data sources

The TrackREX solution will work with any EDC platform and can feed in both raw EDC and SDTM datasets. Similarly lab files can be of any format. It is possible to add further systems into the equation such as IWRS/IVRS and CTMS platforms which will enable further functionality (see below).

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Feed in ancillary data such as vendor and other sponsor spreadsheets

Often studies will have ancillary data that can be useful to be incorporated into the reconciliation review. This could be sponsor feedback (pertaining to certain samples or patients) or perhaps input from a lab vendor (e.g. updates on samples that may not yet have been received or processed). This type of ancillary data can all be incorporated into TrackREX if they are associated with key variables that can be mapped to a sample. By having reconciliation and ancillary data under one tool, this makes the process a far more efficient solution. 

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Adjustable review mode allowing users to add/remove columns as per personal preference

Reconciliation sheets typically are large, cumbersome to navigate and review comprehensively. Different users often do not require to view each data point (column) and therefore our tool enables role selections to only show those data points associated with that role. Views can also be further customised and saved for future reviews. 

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Easy to understand discrepant data issues

Thousands of hours are typically wasted during any clinical trial by individuals manually comparing data points. Whilst this can simply be done programmatically, our solution takes it a few steps further. Data anomalies or discrepancies are not only highlighted, but suggested resolutions are also displayed (e.g. "sample exists but dosing not performed as per CRF yet visit exists in IWRS. Likely that data has not yet been entered in EDC - please re-run program in 1 week"​. It can also suggest where the action needs to be made such as at site or lab vendor.

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Apply data cuts by date or visit

Most clinical trials will have numerous analyses or data review points during the study. Trying to determine which samples need to be reconciled around cut off dates can be complex. Our solution allows the user to enter a cut off date or visit which will exclude samples that fall outside of that snapshot. This is ideal for studies with multiple deliverables! 

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Reporting options

The reporting module allows a number of reports to be created from listings that show data summaries at patient or site level that show patients with missing samples, data issues,  etc.

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No need to re-review data

Actions are stored for future review cycles (i.e. the user will not have to re-review data that has not changed). The tool will automatically resolve prior data issues but any user actions or comments for persistent data issues will be retained for future reviews. This is one of the biggest benefits of our solution in that users do not have to start each review from scratch or indeed have to review comments made during a previous review cycle.

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Permanent issues

Each study will have data issues that will never be resolved. These are typically identified during reconciliation and will include incorrect sampling times, samples not taken or lost samples which may be need to be recorded as protocol violations. The tool therefore allows for these permanent issues to be recorded and be exported for review by the PK scientist or statistician during the conduct of the study.

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Status metrics / site performance KPIs

Comprehensive metrics are available that provide ​study specific insights or measurable KPIs against portfolio criteria.

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No more manual review with multiple open spreadsheets

During the lifetime of  a typical study, TrackREX can save hundreds of hours per study team!

Data reviews will typically consult numerous spreadsheets as part of their data reconciliation efforts: 

• EDC extracts (Drug administration, Sample ID/reference point (if included in CRF), visit information

• Lab vendor

• Sample Data Requisition listings from site/lab

• Other ancillary data from vendor or sponsor

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These data extracts are typically 'programmed' in a haphazard fashion with rudimentary Excel functions including VLOOKUP and manual filtering and at worst are reviewed entirely manually. Part of this review process may not only be repeated by the same review multiple times during the study, but will likely also be  undertaken by other functions. This overlap and duplication of effort has a tremendous impact not only on resourcing but may also have ramifications on the study results themselves. As the usual review of sample data is via manual method, the very activity is often performed seldom or too late in the study when issues are caught too late. At this stage, endemic issues are too late to rectify and missing samples are identified too late to be actioned.

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The TrackREX 'Mapper' utility allows numerous disparate extracts to be incorporated into the tool (see below)