Applications of microphysiological systems to disease models in the biopharmaceutical industry: Opportunities and challenges

疾病 生物制药 制药工业 药物开发 药物发现 计算生物学 药学 医学 风险分析(工程) 计算机科学 药品 生物信息学 生物 药理学 生物技术 病理
作者
Onyi Irrechukwu,Ronnie L. Yeager,Rachel David,Jason E. Ekert,Anitha Saravanakumar,Colin Choi
出处
期刊:Alternatives to animal experimentation [ALTEX Edition]
被引量:2
标识
DOI:10.14573/altex.2204071
摘要

Disease models enable researchers to investigate, test, and identify therapeutic targets that would alter the patients’ disease condition and improve quality of life. Advances in genetic alteration and analytical techniques have enabled rapid devel­opment of disease models using preclinical animals and cell cultures. However, success rates of drug development remain low due to limited recapitulation of clinical pathophysiology by these models. To resolve this challenge, the pharmaceutical industry has explored microphysiological system (MPS) disease models, which are complex in vitro systems that include but are not limited to organ-on-a-chip, organoids, spheroids, and 3D bioengineered tissues (e.g., 3D printing, hydrogels). Capable of integrating key in vivo properties, such as disease-relevant human cells, multi-cellularity/dimensionality of organs, and/or well-controlled physical and molecular cues, MPS disease models are being developed for a variety of indications. With on-going qualifications or validations for wide adoption within the pharmaceutical industry, MPS disease models hold exciting potential to enable in-depth investigation of in vivo pathophysiology and enhance drug discovery and development processes. To introduce the present status of MPS disease models, this paper describes notable examples in six disease areas: cancer, liver/kidney diseases, respiratory diseases/COVID-19, neurodegenerative diseases, gastrointestinal diseases, and select rare diseases. Additionally, we describe current technical limitations and provide recommendations for future development that would expand application opportunities within the pharmaceutical industry.

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