Correction: Integrated biosensors for monitoring microphysiological systems.

Correction for 'Integrated biosensors for monitoring microphysiological systems' by Lei Mou et al., Lab Chip, 2022, 22, 3801-3816, https://doi.org/10.1039/D2LC00262K.

Integrated biosensors for monitoring microphysiological systems.

Microphysiological systems (MPSs), also known as organ-on-a-chip models, aim to recapitulate the functional components of human tissues or organs in vitro. Over the last decade, with the advances in biomaterials, 3D bioprinting, and microfluidics, numerous MPSs have emerged with applications to study diseased and healthy tissue models. Various organs have been modeled using MPS technology, such as the heart, liver, lung, and blood-brain barrier. An important aspect of in vitro modeling is the accurate phenotypical and functional characterization of the modeled organ. However, most conventional characterization methods are invasive and destructive and do not allow continuous monitoring of the cells in culture. On the other hand, microfluidic biosensors enable in-line, real-time sensing of target molecules with an excellent limit of detection and in a non-invasive manner, thereby effectively overcoming the limitation of the traditional techniques. Consequently, microfluidic biosensors have been increasingly integrated into MPSs and used for in-line target detection. This review discusses the state-of-the-art microfluidic biosensors by providing specific examples, detailing their main advantages in monitoring MPSs, and highlighting current developments in this field. Finally, we describe the remaining challenges and potential future developments to advance the current state-of-the-art in integrated microfluidic biosensors.

Organ-On-A-Chip Models of the Blood-Brain Barrier: Recent Advances and Future Prospects.

The human brain and central nervous system (CNS) present unique challenges in drug development for neurological diseases. One major obstacle is the blood-brain barrier (BBB), which hampers the effective delivery of therapeutic molecules into the brain while protecting it from blood-born neurotoxic substances and maintaining CNS homeostasis. For BBB research, traditional in vitro models rely upon Petri dishes or Transwell systems. However, these static models lack essential microenvironmental factors such as shear stress and proper cell-cell interactions. To this end, organ-on-a-chip (OoC) technology has emerged as a new in vitro modeling approach to better recapitulate the highly dynamic in vivo human brain microenvironment so-called the neural vascular unit (NVU). Such BBB-on-a-chip models have made substantial progress over the last decade, and concurrently there has been increasing interest in modeling various neurological diseases such as Alzheimer's disease and Parkinson's disease using OoC technology. In addition, with recent advances in other scientific technologies, several new opportunities to improve the BBB-on-a-chip platform via multidisciplinary approaches are available. In this review, an overview of the NVU and OoC technology is provided, recent progress and applications of BBB-on-a-chip for personalized medicine and drug discovery are discussed, and current challenges and future directions are delineated.

State of the art in integrated biosensors for organ-on-a-chip applications.

Organ-on-a-chip (OoC) models are bioengineered tissue constructs integrated with microfluidics that recapitulate the key features of the physiology of human organs and tissues with applications related to drug development and personalized medicine. The characterization of OoCs relies on conventional labor-intensive approaches despite the many years of research in the field. The physical environment of the tissue constructs, functionality, and metabolic activity of the cells must be monitored to ensure the behavior of the cells, and the cellular environments represent in vivo physiology. Current efforts focus on monitoring these parameters, particularly with in-line biosensors integrated with OoCs. In this review, we describe the recent advances in different biosensing modalities applied to monitor the environment and functionality of OoC models and offer suggestions for future directions in OoC applications.