Although cases of research misconduct in sponsored clinical trials have been sporadically reported, no systematic reviews or national surveys on this topic have been conducted in Japan. Thus, this study aimed to: 1) systemically review publicly available information on scientific misconduct reported through sponsored clinical trials, and 2) carry out a national survey to examine incidents of scientific misconduct using the following three approaches. First, a systematic review of publicly available information on scientific misconduct using Google search, Japan Medical Abstracts Society database, and PubMed.gov; second, a survey of sponsors using an anonymous web questionnaire; and third, a national survey of clinical research coordinators (CRCs) using an anonymous web survey by snowballing sampling. The systematic review identified five cases of misconduct; however, all five cases were already well-recognized in the public domain. In the survey of sponsors, five of the 12 sponsors responded that they had reported other cases to PMDA. In the national survey of CRCs, 22 of 164 (13.4%) responders reported being aware of at least one instance of “fabrication or falsification” in the past three years. These data suggest that not all instances of misconduct in sponsored clinical trials in Japan had been reported to PMDA and that not all instances reported to PMDA had been disclosed to the public. The publicized cases represent only the “tip of the iceberg.” A centralized process for reporting instances of scientific misconduct to Japanese regulatory authorities with pertinent public disclosure may improve the quality of clinical trials.

Although intake of ω-3 fatty acids such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are well known to be beneficial for some cardiovascular and inflammatory diseases, their action mechanism remains elusive. Recently, we revealed that a EPA-metabolite 5,6-dihydroxy-8Z,11Z,14Z,17Z-eicosatetraenoic acid (5,6-DiHETE) represents strong anti-inflammatory reaction in animal body. We originally found that 5,6-DiHETE is produced rich in mouse inflamed colon tissue in the healing phase of colitis. Administration of 5,6-DiHETE could suppress histamine-induced vascular hyperpermeability by inhibiting intracellular Ca²⁺ increase in vascular endothelial cells. Following studies revealed that these bioactivities of 5,6-DiHETE is derived from antagonistic reaction against transient receptor potential vanilloid 4 (TRPV4) channels. In vivo, intraperitoneal or oral administration of 5,6-DiHETE promoted healing of mouse colitis. Interestingly, this novel anti-inflammatory lipid metabolite is contained rich in blue-back fish intestines. In summary, 5,6-DiHETE is an EPA-derived anti-inflammatory lipid mediator which promote healing of inflammation. It could be a new therapeutic tool as a fish-derived supplement.

The development of pharmaceutical drugs, medical devices, and bio-centric products has recently progressed by utilizing start-up-style mechanisms and venture investments. As this requires the involvement of various specialists, it is important to have human resource visionaries that can monitor such development and connect everyone involved. Regulatory science knowledge and expertise offer novel development perspectives and are valuable for clinicians who wish to convert translational research into real clinical work. We believe that such knowledge and expertise in regulatory science is indispensable for advancing core translational research, which is the development of pharmaceutical drugs and medical devices. In this way, translation refers to research data and the thinking and planning processes. Working in an academic research organization is undoubtedly far from a physician’s duties. This is challenging but rewarding work, and having different perspectives and knowledge of domains other than clinical expertise can be beneficial.

Approaches applied for protein structure prediction are roughly divided into two categories: deductive and inductive. The effectiveness of inductive approaches, including AlphaFold, has stood out to date because the patterns of protein structures, the so-called fold or topology, are expected to be limited. In this review, we introduce and outline AlphaFold, which has recently emerged from the recent increase in datasets of protein sequences and structures. In addition, we discuss their effects on drug discovery and development.

Proteins control all biological processes. Therefore, understanding protein functions is indispensable for elucidating each life phenomenon, including the pathogenic mechanisms of diseases. In structural biology, three-dimensional structures of proteins are used to uncover their functions. Thus far, more than 180,000 structures, determined using X-ray/neutron crystallography, nuclear magnetic resonance, or cryo-electron microscopy, have been deposited in the Protein Data Bank. These structures have significantly contributed to our understanding of life. During the summer of 2021, two artificial intelligence (AI) programs that can predict protein structures were released (AlphaFold and RoseTTAFold). These AI programs can predict highly accurate three-dimensional structures of proteins from their amino acid sequences. AlphaFold can predict protein structures with high accuracy; therefore, structural biologists and other scientists can now easily predict the protein structure of interest without requiring any specialized skill or equipment. Furthermore, AlphaFold accelerates the experimental protein structure determination because the program-generated structures can be excellent starting models for experimental structure determination. In contrast, these AI programs use only information based on amino acid sequences. They cannot predict complex structures and conformational changes the proteins adopt while interacting with other proteins or performing vital biological processes. In this review, we have discussed the significance of AlphaFold in structural biology.