A hybrid innovation method based on quality by design and agile scrum paradigms for the development of medicinal products.

This study proposes an agile paradigm of the pharmaceutical Quality by Design (QbD) approach initiated and recommended by regulatory agencies to better understand and control their innovative products and processes throughout the development phase. The primary objective of this hybrid innovation method is to improve the structural organization of the QbD approach to simplify its use and expand its application to the early stages of preclinical development. This agile QbD paradigm relies on the incrementation and/or iteration of short studies called sprints indexed according to the Technological Readiness Level (TRL) scale. Each QbD sprint addresses a priority question of development and relies on a hypothetico-deductive scientific method to address it. They are composed of five steps: developing and updating the Target Product Profile, identifying critical input and output variables, designing experiments, conducting experiments, and analyzing the collected data to generalize conclusions through statistical inference. At the end of a sprint, four outcomes are possible: incrementing knowledge on the developed drug, i.e. moving to the next development sprint, iterating the current or previous sprint to reduce decision-making risk, pivoting to propose a new product profile, or stopping the development project. This decision-making process is based on the results of a statistical analysis estimating the probability of meeting the efficacy/safety/quality specifications of the medicinal product to be developed. To illustrate and to assess the practical relevance of this incremental and iterative approach, we applied it to the development of a new radiopharmaceutical for Positron Emission Tomography (PET) imaging. The Agile QbD approach was applied over six consecutive sprints to progress from an initial product concept (TRL 2) to a prototype manufactured using a production automation system (TRL 4). The method and results presented in this study provide a new perspective on applying QbD as an efficient tool for managing knowledge during innovation projects.