Enhancing population pharmacokinetic modeling efficiency and quality using an integrated workflow
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Population pharmacokinetic (popPK) analyses are at the core of Pharmacometrics and need to be performed regularly. Although these analyses are relatively standard, a large variability can be observed in both the time (efficiency) and the way they are performed (quality). Main reasons for this variability include the level of experience of a modeler, personal preferences and tools. This paper aims to examine how the process of popPK model building can be supported in order to increase its efficiency and quality. The presented approach to the conduct of popPK analyses is centered around three key components: (1) identification of most common and important popPK model features, (2) required information content and formatting of the data for modeling, and (3) methodology, workflow and workflow supporting tools. This approach has been used in several popPK modeling projects and a documented example is provided in the supplementary material. Efficiency of model building is improved by avoiding repetitive coding and other labor-intensive tasks and by putting the emphasis on a fit-for-purpose model. Quality is improved by ensuring that the workflow and tools are in alignment with a popPK modeling guidance which is established within an organization. The main conclusion of this paper is that workflow based approaches to popPK modeling are feasible and have significant potential to ameliorate its various aspects. However, the implementation of such an approach in a pharmacometric organization requires openness towards innovation and change—the key ingredient for evolution of integrative and quantitative drug development in the pharmaceutical industry.
KeywordsPopulation pharmacokinetics Modeling Workflow Efficiency Quality Dataset specification
The authors acknowledge Novartis colleagues from the Advanced Quantitative Sciences (AQS) group, who provided valuable input, discussion, and feedback. Special thanks go to Anne-Gaëlle Dosne and Ivan Demin who reviewed the paper in detail and helped to make it much better.
Conflict of interest
Henning Schmidt and Andrijana Radivojevic are employees of Novartis Pharma AG and receive salaries and benefits commensurate with employment.
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