Case Studies
Case Study 1
One of our clients asked GEM if we could take over the reporting of a phase II oncology study. Another company had made a start on the programming of the SDTM and ADaM datasets but were unable to continue to complete the reporting.
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Case Study 2
Having been recommended by a statistician colleague, a Biotech organisation approached GEM with an interesting request to harmonise safety data from several legacy phase I studies.
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Case Study 3
One of our senior GEM consultants is providing expert programming advice to a European based biopharmaceutical organisation that is preparing its lead candidate drug for US and EU submissions in 2021.
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Case Study 4
One of our clients asked GEM if we could convert a legacy phase II study (that had reported ~ 10 years previously) into CDISC SDTM and ADaM compliant standards so that the supportive data from this study could be included in a New Drug Application.
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Case Study 5
A UK based Biotech company was looking to urgently bolster their internal biometrics resources on a short-term basis with several contract programmers. The resources were needed to report a phase I oncology study and deliver other ad-hoc reports as required.
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Case Study 6
Having worked at AstraZeneca for many years, both Mark and Paul have built up an extensive network of ex-colleagues with expertise in all aspects of Clinical Development, but specifically in the fields of Programming, Statistics, Medical Writing and Data Management.
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Case Study 1 – Rescue Study
We received the data, SDTM and ADaM specifications, TFL shells, and the previous programs for some of the SDTM and ADaM datasets. We were able to use these as a starting point and reduce the time spent to complete the programming.
We checked the SDTM programs and made any required updates to make sure that the raw data was mapped into CDISC SDTM standards correctly using the latest SDTM Implementation Guide.
Then we checked the ADaM programs and made any required updates, including creating programs for ADaM datasets that we not previously created, to make sure that validated, ADaM compliant reporting datasets were created.
We also created the CRT package including the define XML and reviewer’s guide for SDTM and ADaM as well as the aCRF.
Then using the ADaM datasets, we created the analysis results for the CSR, according to the TFL shells received.
Case Study 2
They wanted a Microsoft® Access database containing standardised Demography, Exposure, Adverse Event, Medical History and Con Meds data, so that they could quickly interrogate the pooled data.
The legacy data was saved as SAS datasets for which the client had no way of accessing internally. The pooled Microsoft Access database enables the client to quickly generate summary information rather than having to manually check PDF listings.
GEM created a mapping document for each pooled dataset containing the source and target parameters and a detailed specification for the derivation. Once the specification was agreed, a dynamic process was developed which semi-automated the harmonisation process. A data warehouse was created containing each of the legacy phase I studies.
The last step was to export the final pooled SAS dataset into both CSV and MS Access formats which were then uploaded to the file share repository.
Case Study 3 – Expert Consultant
A full service CRO is delivering the pivotal phase III study and pooled safety data and without an internal biometrics team, the client needed someone with broad expertise and technical skills to provide guidance and advice relating to all the programming components included in the US submission package.
For this client, GEM has provided input both at a strategic level – e.g. discussions relating to the content of the FDA briefing document, discussions relating to the content of the pooled safety database, discussions around the unblinding process for the pivotal phase III study, as well as more operational input such as reviewing technical documents delivered by their full service CRO and confirming key endpoint results.
Our relationship with our client means that GEM will routinely flex our working hours each week or month to suit the needs of the client.
Contact us to hear more about our Expert Consultant services and how we can support your submission delivery team.
Case Study 4 – Legacy CDISC Conversion
As a CDISC Gold member, we are strong proponents of industry standards at GEM and we were happy to provide a competitive quote and ultimately won the business.
Upon receipt of the legacy data, programs and outputs, we mapped the raw data into CDISC SDTM standards using the latest SDTM Implementation Guide and converted the raw data into SDTM datasets. We then mapped the validated SDTM data to ADaM specifications and created the validated, ADaM compliant reporting datasets.
Using the ADaM datasets, we replicated the analysis results from the original CSR, and therefore demonstrated that the underlying integrity of the original datasets remained intact after the CDISC conversion.
Finally, we ran Pinnacle 21 reports on the datasets to ensure compliance with CDISC and produced a CRT package for inclusion in the NDA.
Case Study 5 – GEM Insourcing
Having worked with this client previously, GEM were able to provide the CVs of individuals who best met the requirements of their needs – namely Primary Programmer and QC Programmer to work together as a team. The GEM SOP framework complements the clients SOPs in terms of dual Programming approach to all high risk deliverables.
The GEM Programmers are now working for the client 3 days per week using their in-house reporting system and SOPs. They are using the client’s laptops which were shipped out to their home address and are successfully connecting to the remote desktop using a VPN connection.
Again, flexibility is a key factor for the client in choosing GEM.
Case Study 6 – Unblinding for Interim Analysis
GEM regularly collaborates with ex-colleagues, one example being when an expert Statistician asked us to support a company who needed programming resources to perform the unblinding process for a Data Monitoring Committee who were reviewing data for an Interim Analysis.
To support the Interim Analysis, GEM were provided the necessary programs, blinded raw data and random scheme and downloaded these to an internal restricted area. Within a controlled, secure environment, GEM merged the random scheme onto the data and produced a validated set of unblinded outputs. After successfully following the agreed QC process, the TFLs were released to the members of the DSMB to interpret the data and write a formal report for the sponsor.
With GEM performing the unblinding this ensured that the sponsor remained completely independent to the unblinding process.