Scenario Experience
Question | Sanofi/Covance | CRL | MPI Research, w/ Lilly et al. |
|---|---|---|---|
Does your experience match the scenario flow-chart? | Scenario 1: The SEND datasets generated were prepared after report was finalized/approved as a data exchange exercise so the workflow differed greatly. Data sets created by CRO, Sponsor reviewed datasets and interacted with CRO to address questions to finalize the datasets. |
| For the most part. |
Do you have any experiences with re-work initiated by a request from the FDA. How long did the process take, and what can you share about the experience? | This was not done as the datasets were not part of a current submission. |
| Use of the OpenCDISC Validator with resolution of any issues it uncovered removed the need for a feedback loop with the FDA. |
What were the challenges and solutions for the scenarios? | How do we address study numbering and animal numbering conventions as well as conventions for arms and sets that have been defined by Sponsor |
| The biggest challenge is mapping trial design and exposure for non-boiler-plate cases. This is something that previously did not have to be done, and has to be learned and then defined by the preparer using an interface. |
>What would you want to do differently in the future? |
|
| Work through “template” cases for some of the more common designs. |
>What would you need to work out in advance to ensure a smooth process? | Expectations that were defined ahead of time would reduce rework and questions about datasets. |
| With expectations set ahead of time (decoupled from the study timeline), everything goes smoothly. |
>Where there any areas that you were unable to resolve? | No |
| No. |
Timing | It took Covance approx. 1 week to prepare dataset this would also depend on the complexity and number of endpoints |
| Packaging of a submission takes between a few days to a couple weeks, depending on the complexity of the contents and the number of endpoints. |
>What were the activities that determined the length of the project (critical path)? | Complexity of study design and if PK data part of datasets could increase the timeline PK data |
| Complexity of study design |
>Do you have any guides on estimating the effort to do the work? | No, not at this time |
| Starting with a barebones tox study (inlife, path, clinpath), estimate the total work for that. Then think through any add-on sets of endpoints or circumstances which equate to a chunk of work, such as adding pk, or adding a crazy study design, etc. This can give you a rule of thumb for estimating the effort behind individual studies. |
>How many times have you done this? Is this the first experience? | 1 with 1 CRO |
| 20-25 studies for about 10 Sponsors |
>If you have done this several times, can you describe the learning curve? | N/A |
| It takes a few studies to hit a stride. Special cases that pop up (such as a special study design that hasn’t been done in SEND yet) can represent an additional bump as they come along. |
>How long (calendar time, person hours) did each phase take? (determining what needs to be done, doing the work, confirming/closing the project) | Few hours to several days |
| Estimation: 0-1 hour. |
What tools (software) did you use? | CRO tool |
| Custom-developed add-on to reporting solution. |
Were any domains not provided? Why? | Yes, some domains are not collected while others currently cannot be provided by CRO |
| No, but there could be cases where they are not, to cut down on costs for non-GLP studies where the Sponsor just wants key data to subsume into their own system for discovery/mining purposes. |