Neurons on a chip - toward high throughput network and pharmacology investigations

‘Body-on-a-Chip’ Technology and Supporting Microfluidics

In order to effectively streamline current drug development protocols, there is a need to generate high information content preclinical screens capable of generating data with a predictive power in relation to the activity of novel therapeutics in humans. Given the poor predictive power of animal models, and the lack of complexity and interconnectivity of standard in vitro culture methodologies, many investigators are now moving toward the development of physiologically and functionally accurate culture platforms composed of human cells to investigate cellular responses to drug compounds in high-throughput preclinical studies. The generation of complex, multi-organ in vitro platforms, built to recapitulate physiological dimensions, flow rates and shear stresses, is being investigated as the logical extension of this drive. Production and application of a biologically accurate multi-organ platform, or ‘body-on-a-chip’, would facilitate the correct modelling of the dynamic and interconnected state of living systems for high-throughput drug studies as well as basic and applied biomolecular research. This chapter will discuss current technologies aimed at producing ‘body-on-a-chip’ models, as well as highlighting recent advances and important challenges still to be met in the development of biomimetic single-organ systems for drug development purposes.

Understanding the molecular mechanism of interventions in treating rheumatoid arthritis patients with corresponding traditional chinese medicine patterns based on bioinformatics approach

Better effectiveness would be achieved when interventions are used in treating patients with a specific traditional Chinese medicine (TCM) pattern. In this paper, the effectiveness in treating rheumatoid arthritis (RA) patients in a randomized clinical trial as reanalyzed after the patients were classified into different TCM patterns and the underlying mechanism of how the TCM pattern influences the clinical effectiveness of interventions (TCM and biomedicine therapy) was explored. The pharmacological networks of interventions were builtup with protein and protein interaction analyses based on all the related targeted proteins obtained from PubChem. The underlying mechanism was explored by merging the pharmacological networks with the molecular networks of TCM cold and hot patterns in RA. The results show that the TCM therapy is better in treating the RA patients with TCM hot pattern, and the biomedical therapy is better in the RA patients with cold pattern. The pharmacological network of TCM intervention is merged well with the molecular network of TCM hot pattern, and the pharmacological network of biomedical therapy is merged well with the network of cold pattern. The finding indicates that molecular network analysis could give insight into the full understanding of the underlying mechanism of how TCM pattern impacts the efficacy.