The purpose of this paper is to visualize drug discovery research projects in academia in order to assess their progress and provide strategies for facilitating collaboration with industry. We divided academia’s drug discovery research data package into in vitro and in vivo milestones. Then, we set up the Drug Seeds Alliance Network Japan (DSANJ) original study data package required in each milestone by analyzing an oncology academic drug discovery research project. The Proof of Mechanism (PoM) data was the key to the realization of research alliances in Japan. We discuss ideal support systems to 1) visualize, 2) assess, and 3) revise the progress of academic research projects based on common milestones with industry partners.

For many years, pathologists have performed histopathological diagnoses by observing tissue specimens under a microscope. Recently, however, it has become possible to scan whole slides of tissue specimens using a dedicated slide scanner and store the resultant high-resolution digital images, i.e., whole slide images. This has led to the emergence of digital pathology, a field in which whole slide images are used for histopathological diagnoses. This field is gradually expanding, especially in large hospitals such as university hospitals. In addition, dramatic advancements in image recognition technology have been made since 2012 when deep learning won the general image recognition competition ILSVRC with overwhelming accuracy. Subsequently, deep learning has been applied to various medical images, including X-ray, ocular fundus, and skin images, and is reported to have achieved generalist- or even professional-level diagnostic accuracy in each field. Similarly, the use of deep learning, directed towards digital histopathological images, for assistance with pathological diagnoses is gradually becoming practicable, especially for diseases in which many cases occur. Recently, advanced applications have been developed such as searching for similar cases, predicting genetic mutations from histological images, and generating special stained images from hematoxylin and eosin-stained images. These emerging applications have the potential to greatly expand the field of diagnostic pathology and contribute to the further development of medicine. In this review, we introduce the use of deep learning technology in the field, detail the current advanced applications, and speculate on future perspectives.

African trypanosomiasis is a parasitic zoonosis that is fatal without treatment and has been recognized as a neglected tropical disease. In humans, this disease is referred to as human African trypanosomiasis (HAT) or sleeping sickness, which is characterized by severe sleep disorders. An overwhelming number of African people have experienced HAT without adequate treatment, as some currently available drugs remain unsuitable to the needs of endemic areas. Since 2001, efforts to eliminate HAT have been reinforced worldwide, thus reducing the number of new HAT cases. In addition, this has led to the discovery of several drugs that are easily applicable for therapy; however, additional chemicals and drug targets need to be explored. In the present review, we summarize the symptoms and epidemiology of HAT, the biology of the causative parasitic protozoa Trypanosoma brucei, and therapeutics used in the present treatments. Lastly, we introduce two representative drug discovery studies that are ongoing.

The most common cause of death among adult or older dogs is malignancy. Dogs spontaneously develop malignant tumors with age, and the incidence of malignant tumors in dogs is higher than that in humans. Basic research on treatment of tumors is generally conducted using syngeneic or immunodeficient mice, which have some shortcomings as a model for human tumors that develop over a long period of time, while interacting with the host immune system. On the other hand, naturally occurring canine tumors develop under immunocompetent conditions and may be suitable for preclinical studies, especially for the development of therapies that affect host immunity. In this review, some of the canine tumors and immunotherapies that have been implemented thus far will be discussed, with the intent of helping establish cancer treatment research, using dogs with naturally occurring tumors, for translational studies in humans.

The worldwide pandemic of the novel coronavirus disease 2019 (COVID-19) had an immediate impact on acceleration of the introduction of alternative methods of operation for Institutional Review Boards (IRBs) defined in ICH E6 (GCP) guidelines. This study was carried out to compare the operational status of IRBs in Korea during the COVID-19 outbreak with the results of a survey conducted in Japan during the same period. An online survey of IRBs was conducted in Korea from May 5 to July 31, 2020. A self-administered questionnaire about the profiles of IRB organization, impact of the COVID-19 outbreak on IRB operation, and status of using Information and Communication Technology (ICT) tools such as electronic document management systems and digital communication systems was distributed by e-mail to 169 IRBs in Korea. Responses were collected electronically via the online questionnaire survey. The survey results were then analyzed and compared with those from our previous survey in Japan containing the same questionnaire items, which was distributed to 520 IRBs. A total of 43 IRBs in Korea participated in the survey, and the results were compared with those from 97 Japanese IRBs. Although the local IRB has the largest share in both Japan and Korea, the frequency of review meetings and the impact of the COVID-19 outbreak were greater in Korea than in Japan. Both countries used ICT during the COVID-19 outbreak, but Korea was less concerned about ICT use compared to Japan.

An antibody–drug conjugate (ADC) is a biological drug that binds a drug to a monoclonal antibody via an appropriate linker. ADCs use antibodies to selectively deliver a potent cytotoxic agent to tumor cells, thus drastically improving the therapeutic index of chemotherapeutic agents. We discovered trastuzumab deruxtecan (T-DXd) via study of ADC linker-payload technology that combined a DNA topoisomerase I inhibitor with an anti- human epidermal growth factor receptor 2 (HER2) antibody. T-DXd achieves a high drug-to-antibody ratio with homogeneous conjugation and is highly potent against heterogeneous tumors via the bystander antitumor effect. It is also considered to mitigate safety concerns in systemic circulation due to the linker-payload stability. The non-clinical profile of T-DXd was assessed and its pharmacological advantages were evaluated by in vivo xenograft studies. T-DXd was confirmed to be a valuable therapeutic tool with strong potential to treat breast cancer and other HER2-expressing cancers in a clinical setting. Indeed, T-DXd was recently approved for the treatment of patients with HER2-positive unresectable or recurrent breast cancers in the US, Japan, EU, UK, and Canada and those with HER2-positive unresectable or recurrent gastric cancers in the US and Japan.