Among healthcare-associated infections, catheter-related bloodstream infection (CRBSI) shows a high case fatality rate and is serious threat. CRBSI are a problem to be eradicated. This study was conducted to reveal the growth characteristics of the causative microorganisms of CRBSI and investigate relevant control methods. The effects of biotin on growth of Candida albicans (C. albicans) in the nutrient solutions were investigated. Upon comparing general solutions and biotin-containing solutions, C. albicans showed auxotrophy against biotin, resulting in significant proliferative potential. CRBSI is caused by biofilm formation in the catheter lumen and subsequent proliferation. The effect of biotin on the colonization of C. albicans in the catheter lumen was evaluated. Candida albicans colonization in the catheter lumen and subsequent proliferation were significantly higher than those in control solutions. To investigate methods for CRBSI control, effects on pathogenic microorganisms were examined by screening for nutrient solutions with antimicrobial activity, using a catheter-lumen contamination model. A commercially available solution (PLAS-AMINO^® injection; PA) containing the highest amount of sodium bisulfite was selected. Gram-positive or negative bacteria and C. albicans were used as the causative microorganisms of CRBSI in the study. Dripping PA into each catheter-lumen contamination model demonstrated bactericidal effects against all bacteria tested and strong growth-inhibitory effects on C. albicans. By using PA for contamination inside the catheter, sterilization and suppression of bacterial growth can be expected without having to remove central venous catheters and/or central venous access devices. This review provides valuable findings for the development of novel control methods for CRBSI.

Industrial reforms utilizing artificial intelligence (AI) have been progressing remarkably around the world in recent years. In medical informatics, the application of medical big data analytics using AI is also being promoted, and it is expected to provide screening methods for predicting potential adverse drug reactions (ADRs) and discovering new effects. Previously, we developed a unique ADRs analysis system that incorporates Accord.NET, an open-source machine learning (ML) framework written in the programming language C#, and uses the Japanese Adverse Drug Event Report (JADER) database. By using this system to analyze ADRs and screening the cause and severity of ADRs, information can be obtained to evaluate efficacy as well as ADRs. Although both statistical methods and ML are commonly used for prediction, a characteristic difference between them is that the former emphasizes causal relationships and the latter emphasizes prediction results. Therefore, it is important to distinguish between cases where decisions must be made with an emphasis on causality and those where decisions must be made by focusing on unknown risks, and statistical methods and ML should be selected and used as appropriate. Against this backdrop, this paper describes a use case and suggests that the proper use of AI tools to analyze medical big data will help clinical pharmacists practice optimal drug management for each patient.

Medical big data are accumulated daily by medical staff in clinical settings. We developed a formulary in 2016 using medical big data from eight hospitals affiliated with Showa University, Japan (3200 beds). In 2019, we revised the procedure from the perspective of authenticity, reproducibility, and clarity to develop a medicine formulary with unbiased data. Briefly, we organized two teams of expert physicians. Team 1 was a systematic review team that conducted a literature search using systematic review. Team 2 was a medical big data team that conducted the analysis using medical big data. Both teams developed a bisphosphonate formulary. First and second team recommendations were alendronic acid and minodronic acid, and alendronic acid and risedronic acid, respectively. Discussion between the two teams yielded alendronic acid only in the bisphosphonate formulary. We developed reports for the bisphosphonate formulary that included conflicts of interest, the role of each staff member in developing the formulary, and the process for determining the formulary. To use our formulary in a community context, we updated the formulary on our website. We tried to substantiate our bisphosphonate formulary and make a recommendation to change the bisphosphonates according to our formulary. The formulary is focused on controlling the economic burden of medical expenses. We believe that the formulary needs to represent authenticity, reproducibility, and clarity in the procedure and conflicts of interest, with unbiased data to preclude context (hospital)-convenient decisions.

The JMDC Claims Database^® contains completely anonymized receipt information on the insured members of health insurance associations. The number of registered users is approximately 9.6 million (6% of the population) as of May 2020. In this database, it is possible to track even outpatient treatment, even if the patient changes the medical facility, as long as the insurer of the subscriber's health insurance does not change, so that long-term medical treatment could be targeted as a research theme. However, as the data do not contain medical record information, it is not possible to obtain laboratory values, although it is possible to know whether clinical tests have been performed. For pharmaceutics-related research, the most suitable use of the receipt database like JMDC Claims Database^® seems to be the investigation of actual prescriptions. However, the research topics that pharmacists are interested in are probably comparisons of drug effects, drug-drug interactions, or causal analysis of drugs and side effects. However, laboratory data for evaluating drug efficacy is not available in the receipt database, and the accuracy of the disease name in the database becomes problematic when using the disease name as information indicating the occurrence of side effects. In this review, we introduce our studies performed by using JMDC Claims Database^® and how to manage the above-described problems. We hope that this study will be helpful to those who are going to engage in research using medical big data.

Recently, social implementations of artificial intelligence (AI) have been rapidly advancing. Many papers have investigated the use of AI in the field of healthcare. However, there have been few studies on the adaptation of AI to clinical pharmaceutical services. We reported attempts to adapt clinical pharmaceutical services with AI in the following areas of machine learning application in prescription audits: solutions for pharmaceutical problems via speech recognition and automatic assignment of standard code to drug name information by natural language processing. Though both were exploratory attempts, we showed the usefulness of adapting AI to clinical pharmaceutical services. AI is expected to support and alter all industries in the future, including healthcare and clinical pharmaceutical services. However, AI is not magic that can solve any problem. When using an AI-adapted program, it is necessary to be aware of its features and limitations. For the coming AI era, clinical pharmacists need to improve their AI literacy.

Nowadays, medical big data has been developed and made available in a variety of fields such as epidemiology and pharmacovigilance. Spontaneous reporting databases are one category of medical big data and that has been adequate for analysing events related to side effects that rarely occur in general practice. These data are freely available in several countries. In Japan, the Pharmaceuticals and Medical Devices Agency has developed the Japanese Adverse Drug Event Report (JADER), and the Food and Drug Administration (FDA) developed the FDA Adverse Events Reporting System (FAERS) in the United States. Since the release of these medical big data, many researchers in academic and research setting have accessed them, but it is still difficult for many medical professionals to analyse these data due to costs and operation of requisite statistical software. In this section, we give some tips to study spontaneous reporting databases resulting from our learning experiences.

Natural products are an important source of medicinal seeds. The discovery of novel biosynthetic enzymes from nature is important for their use as biocatalysts for the enzymatic synthesis of useful natural products. In this review, I describe our recent research on the exploitation of a novel secondary metabolite enzyme and the production of unnatural bioactive products in the microbial host, as presented in the S02 symposium in the 141st annual meeting in the Pharmaceutical Society of Japan.

Although natural products are rich sources for drug discovery, only a small percentage of natural products themselves have been approved for clinical use, thus it is necessary to modulate various properties, such as efficacy, toxicity, and metabolic stability. A question in natural product drug discovery is how to logically design natural product derivatives with desired biological properties. This review describes our recent studies regarding the medicinal chemistry of tunicamycin. Tunicamycin inhibits bacterial phospho-N-acetylmuramic acid (MurNAc)-pentapeptide translocase (MraY), which is an essential enzyme in bacteria and a good target for antibacterial drug discovery. The usefulness of tunicamycin as antibacterial agents is limited by off-target inhibition of human UDP-N-acetylglucosamine (GlcNAc): polyprenol phosphate translocase (GPT). We positioned the total synthesis of tunicamycin as a starting point for the research and have accomplished the synthesis of tunicamycin V by using the Achmatowicz reaction, [3,3] sigmatropic rearrangement of allyl cyanate, and stereoselective glycosylation as key reactions. Next, the minimum structural requirements for tunicamycin V for MraY inhibition were established by systematic structure-activity relationship studies with truncated analogs of tunicamycin V. Our collaborative study elucidated a crystal structure of human GPT in complex with tunicamycin. This structural information was then exploited to rationally design an MraY-specific inhibitor of tunicamycin V in which the GlcNAc moiety was modified to a MurNAc amide. The analog was identified as a highly selective MraY_AA inhibitor.

Sufficient aqueous solubility is a key requirement for small molecular drug candidates, and improvement of the aqueous solubility of bioactive compounds is often a major issue for medicinal chemists. Decreasing the partition coefficient (Log P) by the introduction of a hydrophilic group is the conventional approach for improving the aqueous solubility of drug candidates, but is not always effective. On the other hand, the solubility of a solid solute in water is also dependent on the crystal packing of the solute suggesting the existence of another principle of solvation. We have developed alternative strategies to improve solubility by means of chemical modification to weaken intermolecular interaction in the solid state, thereby lowering the melting point and increasing the solubility. In this review, we summarize the strategies for improving solubility, that is, modification of molecules in ways that would disrupt molecular planarity by increasing the dihedral angle, that would bend the molecular structure, that would disrupt molecular symmetry, or that introduce a non-flat substituent at the meta position of a benzene substructure. We showed that these strategies can increase the aqueous solubility of molecules even if their hydrophobicity is concomitantly increased. Furthermore, we found that disruption of intermolecular interaction resulted in better aqueous solubility than a decrease of hydrophobicity in some cases.

Glycoconjugates are present in various organisms, ranging from animals to viruses. Glycoconjugates are involved in several biologically significant functions, including viral infection and neurotransmission. However, the role of glycoconjugates in virus replication and neural function remains unknown. We discovered that the influenza A virus (IAV) binds to sulfatide, which lacks a sialic acid residue, and that delivering sulfatide combined with newly synthesized IAV hemagglutinin (HA) to the target plasma membrane induces the translocation of viral ribonucleoprotein complexes from the nucleus to the cytoplasm. Molecular species of sialic acid are largely classified as N-acetylneuraminic acid (Neu5Ac) and N-glycolylneuraminic acid (Neu5Gc). We discovered that two amino acids in IAV H3 HA play a critical role in the recognition of Neu5Ac and Neu5Gc. Also, we observed that human parainfluenza virus types 1 (hPIV-1) and 3 (hPIV-3) bind to different forms of gangliosides. These viruses preferentially recognized oligosaccharides containing branched N-acetyllactosaminoglycans with terminal Neu5Acα2-3Gal. Neu5Gcα2-3Gal- and NeuAcα2-6Gal-containing receptors were identified by hPIV-3, but not by hPIV-1. We constructed a novel sialidase fluorescent substrate, 2-benzothiazol-2-yl-phenol derivative-based N-acetylneuraminic acid (BTP3-Neu5Ac), which detects sialidase activity in living mammalian tissues and virus-infected cells expressing viral neuraminidase. We discovered that neural activity-dependent desialylation by sialidase contributes to rat hippocampal memory processing. Using BTP3-Neu5Ac, we developed a rapid and sensitive approach for detecting and isolating drug-resistant influenza viruses. This review summarizes the role of sialylglycoconjugates and sulfatide in virus replication as well as mammalian sialidases involved in neural function and insulin secretion.

Cyclodextrins (CDs) are used not only as pharmaceutical excipients but also as active pharmaceutical ingredients. CDs can act as artificial carriers or shuttles to ameliorate lipid transport disorders. Niemann-Pick disease type C (NPC) is an inherited, progressive neurodegenerative disorder caused by mutations in NPC1 or NPC2 genes, in which unesterified cholesterol accumulates in lysosomes and the transport of cholesterol from lysosomes to the endoplasmic reticulum is impaired. 2-Hydroxypropyl-β-CD (HPBCD) has activity as a cholesterol shuttle and can attenuate NPC-related manifestations in model cells and animals. HPBCD can also be an effective treatment for NPC patients, but has produced lung damage and ototoxicity at therapeutic doses in clinical trials. Like HPBCD, 2-hydroxypropyl-γ-CD (HPGCD) can normalize disrupted cholesterol homeostasis in cells derived from NPC patients and NPC model mice. HPGCD interacts with unesterified cholesterol with a mode of interaction distinct from that of HPBCD and acts as a fine-tuned cholesterol shuttle for the treatment of NPC with a wider safety margin than HPBCD in terms of ototoxicity and pulmonary toxicity. By bridging clinical and basic research, it is hoped that progress will be made in the development of therapeutic agents against neurodegenerative lipid storage disorders that share common pathogenic mechanisms with NPC.

Ophthalmic viscosurgical devices (OVDs) are mainly divided into two general categories: cohesive and dispersive. Dispersive OVDs such as the 3% hyaluronic acid and 4% chondroitin sulfate (HA/CS) combination have excellent adhesion to ocular tissues and protect the corneal endothelium to a greater extent than cohesive OVDs. Herein, we summarize our recent findings regarding one of the properties of the HA/CS combination related to clinical performance. (i) The room temperature stability of OVDs and needle clogging by OVDs remain clinical issues. We demonstrated that adding d-sorbitol to the HA/CS combination preserved its viscosity, which was equivalent after 2 year-storage at room temperature to the viscosity of HA/CS combination stored under refrigeration for 2 years without d-sorbitol. Besides, the HA/CS combination with d-sorbitol could be used repeatedly without cleaning or replacing the needle, suggesting that the addition of d-sorbitol prevents drying and solidification of the OVD on the needle. (ii) Although it can be inferred from numerous studies that the tissue adhesion of OVDs influences their retention by the eye, little is known about the physical properties of OVDs that contribute to intraocular retention. To address this issue, we compared two types of adhesive forces, detachment force and repulsive force, for each OVD. Compared with other dispersive OVDs, the HA/CS combination showed higher values for both adhesive forces. These results suggest that adhesive forces may be used as an index of dispersive OVD retention in the eye.

Pharmacists play a key role in optimizing the safe and effective use of medicines in the super-aged society in Japan. Recently, community pharmacists' role has been transformed and expanded to provide patient-centered care. This study aimed to simulate a change in the demand for community pharmacists resulting from this shift in their role, from 2019 to 2035. The change in demand was estimated by the number of prescriptions obtained from publicly available sources of information. The number of required community pharmacists was calculated separately for full-time and part-time pharmacists and the pharmacists engaged in home medical care. This number was calculated using the estimated demand, the number of prescriptions dispensed per day, and annual working days. We evaluated the effect of changes in the working conditions, which include changes in the dispensing process time, rate of part-time staff and their work time, and number of home medical care per day, on the number of community pharmacists. When the number of prescriptions dispensed per day was set at 19.8, the demand for community pharmacists was estimated as 188,314 in 2035. Furthermore, due to the changes in the working conditions, the demand is expected to change from 153,362 to 266,944. Although the increasing provision of drug information time leads to an increasing number of pharmacists, combining it with work efficiency services could prevent or decrease it. The optimal supply and demand balance of community pharmacists should be determined by both, promoting pharmaceutical care services and improving work efficiency.

Clobetasol propionate ointment (CLP_O) formulations have been classified as members of the “strongest” steroidal efficacy group, with eight of these formulations currently marketed in Japan. Evaluations of pharmaceutical properties of each formulation revealed three classification types: droplet dispersion type containing propylene glycol (PG) and surfactant, type with surfactant but not PG, and other types. These rheological properties were diverse, with no correlation found between viscosity and ointment type. However, when CLP_O and six types of heparinoid oil-based cream (HP_OC) formulation mixtures were stored at 37℃, a liquid layer was observed starting at 24 h for one CLP_O formulation in which polyoxyethylene hydrogenated castor oil 40 was used as a surfactant out of the four droplet-dispersion type ointments and two low-viscosity HP_OC formulations. In contrast, one other type of CLP_O formulation that contained a surfactant with polysorbate 80, but not PG, exhibited a liquid layer for all of HP_OC formulations. This suggests that CLP_O formulations that contain a surfactant with a high hydrophilic-lipophilic balance value are likely to generate a liquid layer for mixtures containing HP_OC formulation. The present results demonstrate that not only the pharmaceutical properties of the eight CLP_O formulations differ from one another, but also that the stabilities of HP_OC formulation mixtures are significantly different. Therefore, pharmacists need to focus on inactive as well as active pharmaceutical ingredients to select formulations that patients will want to use, in addition to successfully treating their pathological conditions.

Various reports have been published in recent years on the effects of histone deacetylase (HDAC) inhibitors on programmed death ligand 1 (PD-L1) expression in cancer cells. The combination therapy of immune checkpoint inhibitors and HDAC inhibitors utilizing these effects has attracted attention as a new clinical treatment of triple-negative breast cancers. We investigated how the expression level of PD-L1 changes depending on the type of HDAC inhibitor exposed to triple-negative breast cancer cell line MDA-MB-231. We found that the mRNA expression level of PD-L1 was significantly decreased by Vorinostat and K-32 (pan-HDAC inhibitors) at high concentrations exhibiting low cell viability, while it was increased by high concentrations of K-560 (HDAC1,2 inhibitor) and Entinostat (HDAC1,3 inhibitor). On the other hand, the mRNA level of PD-L1 was increased by all of these HDAC inhibitors at low concentrations showing high cell viability. Of particular note, K-32 induced more PD-L1 mRNA than all the other HDAC inhibitors at the lowest concentration of 0.5 μM. This finding might suggest the usefulness of pan-HDAC inhibitors in clinical treatment in combination with immune checkpoint inhibitors.