Integrated Planning of Drug Development Programs

点击翻译按钮获取中文摘要

In clinical research, the planning of pilot and subsequent confirmatory study are strongly linked. This leads to the idea of simultaneous planning with the aim of ensuring a predetermined probability of success. Specifically, the question arises as to an optimal strategy for choosing the sample size for the pilot study and the decision rule as to whether or not to proceed with conducting the confirmatory study (“go/no-go decision”) with the most economical use of the total resources. This can be done by maximizing the expected value of a pre‐specified utility function – which includes costs of the program (fixed and variable per-patient costs for pilot/confirmatory study), future benefit and some kind of development risk (expected value of a successful program) – over the sample size of the pilot study and the threshold value for the go/no-go decision rule. In the ongoing DFG research project “Integrierte Planung von Pilotstudien und konfirmatorischen Studien in der klinischen Forschung” methods were derived so that several situations in clinical research could adequately be mapped. For example, studies with time-to-event, binary or normally distributed endpoint, multiple arms, multiple co-primary endpoints or bias adjusted treatment effect estimates can be planned. In order to facilitate the practical implementation, the corresponding biostatistical methods were implemented in the programming language R. Up to now, prototype versions of user friendly R Shiny applications (“Apps”) and an R package (drugdevelopR) are provided for optimal planning. The Apps as well as the package are accessible via https://web.imbi.uni-heidelberg.de/drugdevelopR/.It is desirable to provide an adequately validated and professionally quality assured version of the drugdevelopR software for use in clinical research. Therefore, the aim of the project to be applied for is to prolong the successful work of the DFG research project in order to increase the functionality, usability, and – most importantly – the quality assurance (“Fit for Purpose”) of the research software drugdevelopR to guarantee sustainable use and transfer to new research contexts beyond the research project (“Fit for Re-Use”). Quality assurance (i.e. e.g. validation, verification, testing and audit) of drugdevelopR and enhancement of its user friendliness is to be achieved by following a “quality assurance concept”. This includes measures for archiving, versioning, bug reporting/tracking and source code documentation. The concept for the description of the software stipulates the transformation of the prototype software to a professional CRAN version (including e.g. detailed user manuals and/ or tutorials) and provision of at least one publication in a peer-reviewed journal. The open-source publication on GitHub.com and an appropriate licensing model (MIT License) of the durgdevelopR software are intended to ensure that the academic use and development is free of charge.