„Humanizing. Drug. Development. How much Predictivity is in your Chip?“
Organ-on-Chips (OoCs) represent a groundbreaking advancement in the realm of drug development, offering a more precise in vitro emulation of human physiology compared to traditional animal models. These innovative systems hold immense promise in humanizing the drug development process, primarily by enhancing drug efficacy and hazard identification in both drug discovery and non-clinical studies. Despite their potential, OoCs have not been widely adopted in drug development due to uncertainties surrounding their predictive and translational capabilities compared to existing in vitro models and animal testing.
To address this challenge, a novel integrated workflow has been proposed, combining OoC data with advanced computational modeling, thereby creating digital twins of these chip systems. This approach not only offers a profound mechanistic insight into biological principles but also elevates the predictive accuracy of human clinical outcomes, such as safety and efficacy, for novel drugs. Such digital twins represent a significant leap in modeling human physiology, bypassing the need for animal testing while providing more reliable and sustainable drug development processes.
A prime example of this synergy is seen in the development of DigiLoCs, a digital liver-on-chip simulator, which focuses on simulating hepatic metabolism. This platform surpasses traditional methods in accurately predicting human pharmacokinetics, underlining the effectiveness of integrating biological data into digital twins. Beyond liver metabolism, this approach has profound implications for other areas like media optimization and kidney toxicity studies, highlighting its versatility and scope.
The integration of OoCs and computational models into digital twins not only improves our understanding of drug mechanisms but also streamlines the drug discovery process. This innovative workflow is poised to revolutionize the field, making drug development more efficient, cost-effective, and most importantly, more aligned with human in vivo situations. The lecture will delve into this integrated approach, underscoring the need for such advancements in the context of drug development and presenting a comprehensive overview of literature-based examples and future prospects in this exciting field.