Folia Pharmacologica Japonica最新文献

Human induced pluripotent stem cells derived cardiomyocytes (hiPSC-CMs) can recapitulate the properties of human cardiomyocyte and exhibit disease phenotypes in vitro, attributable to their healthy- or patient-specific genetic backgrounds. Therefore, hiPSC-CMs are a crucial tool for developing therapeutic agents for cardiovascular diseases, and regenerative medicine using hiPSC-CMs is expected to be an alternative therapy to heart transplantation. Moreover, the development of organoid models has been advanced to replicate the complex structure of heart tissue in vitro, thereby effectively facilitating drug discovery. On the other hand, current methods for advancing drug discovery using hiPSC-CMs face limitations, including the difficulty of quantifying characteristics such as cell structure and predicting the risk and efficacy of candidate drug in clinical practice. In the field of regenerative medicine, challenges include quality control and the verification of safety of transplanted cells in human. In silico model, including artificial intelligence (AI) and simulation, have been developed in the field of drug discovery using hiPSC-CMs. These advancements encompass phenotype scoring via AI and risk prediction through simulations. This review outlines the current status and challenges of drug discovery using hiPSC-CMs and in silico model, based on the published reports.

In vitro compound evaluation using human-derived neural cells is beginning to incorporate microphysiological systems (MPS). Neural MPS includes not only microfluidic devices but has also recently recognized neural organoids as viable MPS platforms. The history of neural MPS utilizing microfluidic devices is extensive, with the development of models that control the positioning of cell bodies and neurite outgrowth, as well as models that mimic neuronal projections through the connection of heterogeneous cell types. This paper presents examples of predicting peripheral neuropathy through machine learning applied to images of cell bodies and neurites in microfluidic devices, as well as the construction of a motor neuron-skeletal muscle model. Additionally, it discusses the responses to contraindicated drugs in Dravet syndrome using brain organoids that reflect biological brain structures. In drug discovery applications of neural MPS, it is essential to develop and utilize appropriate MPS tailored to specific objectives, ensuring biological relevance and reliability for future advancements.

Age-related macular degeneration (AMD) is one of the most common neuroinflammatory diseases that is the leading cause of blindness worldwide. AMD is caused by not only mutations in immune-related genes such as Cfh (complement factor H) but also the accumulation of environmental factors such as obesity and other inflammatory triggers with age. Our study found that the past histories of obesity can lead to immunological reprogramming in the innate immune system and affect the development of AMD in later life. This reveals a new link in the role of innate immune memory in neuroinflammatory diseases such as AMD, and intervention in innate immune memory may be a new therapeutic strategy.

The delay and loss of drugs are serious problems in Japan. To overcome this issue, it is important to strengthen drug development capabilities. For drug development, the establishment and advancement of non-clinical testing methods are necessary for safe and effective clinical trials. Recently, the movement toward alternatives to animal testing has accelerated internationally. New Approach Methodologies (NAMs), such as human inducible pluripotent stem cell (hiPSC) technology and in silico modeling & simulation, are considered valuable for drug development. It has been demonstrated that hiPSC-derived cardiomyocytes (hiPSC-CMs) are useful tools to assess drug-induced cardiotoxicity, including arrhythmia and cardiac contractile dysfunction, leading to the use of hiPSC-CMs in the drug review process. Advancing hiPSC technologies have enabled the generation of mature hiPSC-CMs and engineered heart tissues, which are expected to provide novel information in drug safety and efficacy evaluation. Furthermore, it would be possible to establish the non-clinical evaluation that takes into account individual differences by developing hiPSCs bearing characteristics specific to certain populations, such as pediatrics or rare disease patients. Here, we present the recent findings and future perspectives on non-clinical evaluation using hiPSC technology.

In recent years, the rapid development of generative AI has given rise to a variety of services such as machine translation, sentence summarization, and programming code generation. In drug discovery, generative AI and chemoinformatics have been used for seed/lead compound generation and optimization, and several successful cases were reported. The use of AI technology in drug discovery is expected to solve previously difficult problems and dramatically improve success rate in drug discovery. ITM, Inc. is a venture company established in 2004 to support drug discovery in silico using original chemoinformatics technology. Currently, ITM is developing a drug discovery support system that combines state-of-the-art AI technology and chemoinformatics technology. This paper introduces ITM's technology with a focus on the use of generative AI.

Belumosudil mesylate (REZUROCK_® Tablets hereafter belumosudil) is a novel selective rho-associated, coiled-coil containing protein kinase 2 (ROCK2) inhibitor. ROCK2 is a kinase involved in immune cell differentiation and tissue fibrosis. Belumosudil exerts its effect by decreasing the inflammation and fibrosis in various organs which are the two key features of cGVHD. In the phase III clinical study in Japan, the primary endpoint was met, best overall response rate (best ORR), defined as the percentage of patients who achieved complete response (CR) or partial response (PR), was 85.7%. Belumosudil received manufacturing and marketing approval for the treatment of chronic graft-versus-host disease (cGVHD) in patients who have insufficient response to steroid therapy in March 2024 and launched in May 2024. The Japanese MHLW has also granted orphan drug designation in May 2023 for the treatment of cGVHD.