Abstract: Among the rising number of New Approach Methodologies (NAMs), Organs-on-Chips (OoCs) are emerging as actionable solutions in the field of pharmaceutical development and diseases modelling. Pushed by the necessity to boost drug development by giving access to relevant model, legislative bodies are expanding their usage in IND submissions. However, as the complexity of OoCs increases to fully achieve their predictive challenges, these technologies still struggle to move from the laboratory into real-life products adopted and used by the pharmaceutical industry. There are still some significant challenges that need to be overcome to fully enable this transition. The lack of trained technicians on microfluidic operations, the high exigence from the industry (high throughput screening and high reproducibility) and the integration with their current technologies and readouts constitute some of these roadblocks. To address these challenges, we show our overall product design framework where scientific relevancy, repeatability and reproducibility of models, and user experience are critical. We present design rules for OoC devices, compatible with ANSI SLAS 4-2004 (R2012) (formerly recognized as ANSI/SBS 4-2004) norms and automated cell culture platforms (Biomek 7, Beckman Coulter), and exemplify their impacts on the culture of human iPSC-derived sensory neurons. We introduce a generic repeatability and reproducibility assessment framework, in which they are quantified by monitoring 1/ the differences between cultures performed by an experienced technician and an automated cell culture robot, and 2/ critical parameters of the cell culture itself (media replacement efficiency, cell density and homogeneity at seeding and after three weeks of culture, axonal growth measurements, supernatant analysis, and fluorescent profiles for cellular markers). This study demonstrates the high level of efficiency, repeatability, and reproducibility achievable when using OoC platforms compatible with automatic cell culture robots. This quest to reduce intralaboratory and interlaboratory variability is essential to reach sufficient performance levels for regulatory submissions for clinical trial of new drugs. Moreover, we believe that designing OoCs with ANSI/SLAS norms in mind, thus being compatible with automated culture and data acquisition platforms, is a crucial step towards fulfilling the needs of industrial companies in terms of scaling and efficiency.
