Vincent Buchheit, Michael Hackl, Katja Kuldszun, Christian Flandorfer
Roche Pharma Research and Early Development - Scinteco gmbh
Objective: We combine design and analysis of clinical trials with quantitative pharmacology expertise to guide a selection of the best dose regimen. We investigate the relationships between dose, exposure and response to understand how and why these differ between patients; develop simple ways to explain large amounts of response variability and develop simple and practical ways to implement treatment optimization. In order to achieve those objectives, the team processes large amounts of data, using different tools and methodologies. Given the importance and impacts of the quantitative clinical pharmacology contribution to the team, those analyses are often shared with Health Authority agencies. As a result, it has become crucial [TS1] for the team, to move from an open shared drive to a more robust and validated platform.
The objective of this abstract is to highlight the user’s perspectives on using a validated environment to support modeling and simulation activities and how it further improves efficiency and quality of the quantitative clinical pharmacology analyses.
Methods: Together with our IT colleagues, we defined user requirements and explored several solutions. Quickly we noticed that improve had the potential to fulfill our needs. improve was designed to support PKPD analysis and provides a valuable and convenient interface with modeling software like NONMEM®, Monolix, Pumas and other tools.
Results: improve is a repository allowing scientists to perform their daily work, in a secured validated and versioning control environment. improve combines a global, secure file repository with a robust and versatile modeling management interface for 3rd party tools like NONMEM®, Monolix®, Pumas, SAS®, R, PsN, Rstudio…. The main concept behind it is to offer control and traceability over your complete modeling and simulation workflow while retaining the simplicity and ease of use of a standard file explorer. No matter which analysis you choose, improve will keep track of the “who, what, when, where and why” of your data. At the same time, you are completely free to make decisions for the analysis you want to perform and which actions you want to take within your third-party tool of choice. In short: Whatever you perform with your data, improve will help you to keep track of your files AND your decisions.
improve automatically extracts key information from the users NONMEM® run, such as objective function value, thetas, omegas, and sigmas. improve provides also a graphical representation of your analysis flow using steps. A color code on a step level helps end-users to identify erroneous or out of sync steps. You can flag steps to easily identify your base, full or final models.
improve provides additional key features. It is a versioning control system. At any time, you can go back to a previous version of your script, input data or output files. You can also compare versions of files, or versions of outputs. This also works for entire runs, so you can compare inputs, outputs and estimates of specific versions of a run or other runs. Users can restrict access for interim analysis for individual users or define groups that are allowed to work on those resources.
Current Limitations: Besides the client, there is the improve.office Module that enables easy access to the client repository without having to use the client itself. This is particularly useful for code development in SAS® for example. We are also using this module to save Phoenix Project Files via improve.office into the client. Although this extra entry point into the repository is a great addition to the platform it comes with certain limitations that potentially prohibit the extension to other processes and workflows. As improve client and improve.office are only loosely integrated users currently have to synchronize the folders of interest to the hard drive. This set up potentially takes up a lot of disc space and is error prone. It demands that users always check if files of interest have changes in the repository and demands for users to always manually synchronize back into the repository.
Conclusions: improve is currently used to support modeling and simulation activities, as well as Non-Compartmental Analysis (NCA). During the course of the year, we are planning to use improve to store all Clinical Pharmacology documents, making this new platform the single source of data and analysis for all Quantitative Clinical Pharmacology activities.
References:
[1] www.scinteco.om
Reference: PAGE () Abstr 9334 [www.page-meeting.org/?abstract=9334]
Poster: Software Demonstration