Prediction of Cisplatin-Induced Acute Kidney Injury Using an Interpretable Machine Learning Model and Electronic Medical Record Information.

Predicting cisplatin-induced acute kidney injury (Cis-AKI) before its onset is important. We aimed to develop a predictive model for Cis-AKI using patient clinical information based on an interpretable machine learning algorithm. This single-center retrospective study included hospitalized patients aged ≥ 18 years who received the first course of cisplatin chemotherapy from January 1, 2011, to December 31, 2020, at Nagoya City University Hospital.

Machine Learning-Based Prediction of the Inhibitory Activity of Chemical Substances Against Rat and Human Cytochrome P450s.

The prediction of cytochrome P450 inhibition by a computational (quantitative) structure-activity relationship approach using chemical structure information and machine learning would be useful for toxicity research as a simple and rapid tool. However, there are few models focusing on the species differences between rat and human in the P450s inhibition. This study aimed to establish models to classify chemical substances as inhibitors or non-inhibitors of various rat and human P450s, using only molecular descriptors.

Direct Comparison of the Effectiveness and Safety Among Direct Oral Anticoagulants and Warfarin in Japanese Patients: Nationwide Cohort Study in Japan.

Direct oral anticoagulant drugs (DOACs) are available in addition to warfarin for the treatment of patients with non-valvular atrial fibrillation (NVAF). Anticoagulants are useful for practical pharmacotherapy in Asian populations, but their responses are different from those in Caucasian populations. Therefore, we aimed to identify the most useful anticoagulant using a nationwide insurance claims database in Japan.

Streamlining Considerations for Safety Measures: A Predictive Model for Addition of Clinically Significant Adverse Reactions to Japanese Drug Package Inserts.

The addition of clinically significant adverse reactions (CSARs) to Japanese package inserts (PIs) is an important safety measure that can be used to inform medical personnel of potential health risks; however, determining the necessity of their addition can be lengthy and complex. Therefore, we aimed to construct a machine learning-based model that can predict the addition of CSARs at an early stage due to the accumulation of both Japanese and overseas adverse drug reaction (ADR) cases. The target comprised CSARs added to PIs from August 2011 to March 2022.

[Exploration of Risk Factors of the Onset of Antibiotics-induced Acute Kidney Injury and Its Transfer to Chronic Kidney Disease Using the Medical Information Database].

Drug-induced acute kidney injury (AKI) is a serious adverse drug reaction, which results in a significant decline in renal function and is known to progress to chronic kidney disease (CKD). Therefore, appropriate drug therapy is important to avoid the risk of drug-induced AKI and CKD, which are serious concerns in clinical practice. In this study, using the medical information database of Hamamatsu University Hospital, we investigated the risk factors that accelerate the onset of drug-induced AKI or its progression to CKD in patients who received aminoglycoside antibiotics (AGs) or glycopeptide antibiotics (GPs), which are strongly associated with drug-induced AKI and CKD.

Predicting the Addition of Information Regarding Clinically Significant Adverse Drug Reactions to Japanese Drug Package Inserts Using a Machine-Learning Model.

Purpose: To develop a machine learning (ML)-based model for predicting the addition of clinically significant adverse reaction (CSAR)-associated information to drug package inserts (PIs) based on information of adverse drug reaction (ADR) cases during the post-marketing stage in Japan.

Methods: We collected data on CSARs added to PIs from August 2011 to March 2020. ADR cases that led to CSARs resulting in PI revisions were considered as a positive case, and ML was used to construct a binary classification model to predict the PI revisions.

Epidemiology and predictors of hyponatremia in a contemporary cohort of patients with malignancy: a retrospective cohort study.

Background: Hyponatremia is associated with worse outcomes among patients with malignancy. However, contemporary cohort data on epidemiology and risk factors are lacking.

Methods: In this single-centre, retrospective cohort study, patients who received intravenous antineoplastic agents from 2018 to 2020 at Nagoya City University Hospital were enrolled.

Comparison of Efficacy and Safety of Direct Oral Anticoagulants and Warfarin between Patients in Asian and Non-Asian Regions: A Systematic Review and Meta-Regression Analysis.

Direct oral anticoagulants (DOACs) have increasingly replaced warfarin for treating patients with non-valvular atrial fibrillation (NVAF). DOACs have been demonstrated to be more useful than warfarin, which was highlighted at its ethnic differences in efficacy and safety; however, the regional differences of DOACs remain unclear. We conducted a systematic review, meta-analysis, and meta-regression to evaluate the efficacy and safety of DOACs in patients from Asian and non-Asian regions with NVAF.

Significant association between HLA-B*35:01 and onset of drug-induced liver injury caused by Kampo medicines in Japanese patients.

Aim: Drug-induced liver injury (DILI) is a severe and life-threatening immune-mediated adverse effect, occurring rarely among treated patients. We examined genomic biomarkers in the Japanese population that predict the onset of DILI after using a certain class of drugs, such as Kampo products (Japanese traditional medicines).

Methods: A total of 287 patients diagnosed as DILI by hepatology specialists were recruited after written informed consent was obtained.

Development of quantitative model of a local lymph node assay for evaluating skin sensitization potency applying machine learning CatBoost.

The estimated concentrations for a stimulation index of 3 (EC3) in murine local lymph node assay (LLNA) is an important quantitative value for determining the strength of skin sensitization to chemicals, including cosmetic ingredients. However, animal testing bans on cosmetics in Europe necessitate the development of alternative testing methods to LLNA. A machine learning-based prediction method can predict complex toxicity risks from multiple variables.

BRAF/MEK inhibitor-associated nephrotoxicity in a real-world setting and human kidney cells.

Acute kidney injury (AKI) associated with cancer chemotherapy can be life-threatening. Inhibitors of rapidly accelerated fibrosarcoma kinase B (BRAF)-mutants and mitogen-activated extracellular signal-regulated kinase (MEK) administered as combination therapy are effective against BRAF-mutant melanoma, but drug-associated AKI events were reported after marketing. Here, we examined the nephrotoxicity of two BRAF inhibitors, vemurafenib and dabrafenib, and two MEK inhibitors, cobimetinib and trametinib, in a real-world setting and human kidney cells.

Development of template systems for ligand interactions of CYP3A5 and CYP3A7 and their distinctions from CYP3A4 template.

Starting from established CYP3A4 Template (DMPK. 2019, and 2020), CYP3A5 and CYP3A7 Templates have been constructed to be reliable tools for verification of their distinct catalytic properties. A distinct occupancy was observed on CYP3A4-selective ligands, but not on the non-selective ligands, in simulation experiments.

In Silico Approach to Predict Severe Cutaneous Adverse Reactions Using the Japanese Adverse Drug Event Report Database.

Severe cutaneous adverse reactions (SCARs), such as Stevens-Johnson syndrome/toxic epidermal necrolysis and drug-induced hypersensitivity syndrome, are rare and occasionally fatal. However, it is difficult to detect SCARs at the drug development stage, necessitating a new approach for prediction. Therefore, in this study, using the chemical structure information of SCAR-causative drugs from the Japanese Adverse Drug Event Report (JADER) database, we tried to develop a predictive classification model of SCAR through deep learning.

Efficacy Comparison for a Schizophrenia and a Dysuria Drug Among East Asian Populations: A Retrospective Analysis Using Multi-regional Clinical Trial Data.

Background And Objectives: Multi-regional clinical trials (MRCTs) are an efficient drug development strategy for eliminating drug lag in East Asian countries. In planning MRCTs according to the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use E17 guideline, it is expected that East Asian populations with relatively similar ethnicity can be pooled as one population. However, evidence supporting this assumption is limited.

Real-world evidence of population differences in allopurinol-related severe cutaneous adverse reactions in East Asians: A population-based cohort study.

Allopurinol-related severe cutaneous adverse reactions (SCARs) are strongly associated with HLA-B*58:01, the allele frequency (AF) of which is largely different among East Asians. However, evidence of population differences in SCAR development and relevance of genetic and/or other risk factors in the real-world remain unelucidated. This study aimed to evaluate population differences in allopurinol-related SCAR incidence related to genetic and/or other risk factors among East Asians in the real-world.

Points to Consider for Implementation of the ICH E17 Guideline: Learning from Past Multiregional Clinical Trials in Japan.

We identified the major points that are described in the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) E17 guideline but have not been considered in the past multiregional clinical trials (MRCTs) used for drug approval in Japan to elucidate potential challenges in the implementation of the ICH E17 guideline in Japan. Based on the analysis of 167 MRCTs of 130 drugs, several points, such as the same dose setting and consistency between the overall and Japanese populations, in addition to good clinical practice compliance, have been well considered in ≥ 75% of MRCTs. In contrast, the use of relevant guidelines for disease and primary end point definitions, standardization of efficacy/safety information, sample size allocation, as well as training/validation on subject selection and primary end point, have been addressed less adequately and may need to be considered when planning future MRCTs.

Applications of a grid-based CYP3A4 Template system to understand the interacting mechanisms of large-size ligands; part 4 of CYP3A4 Template study.

Catalytic interactions of CYP3A4 with large-size ligands have been studied on the Template established in our previous studies using polyaromatic hydrocarbon and steroid ligands (DMPK 34: 113-125 and 351-364 2019 and in press 2020). Typical CYP3A4-substrates including erythromycin, cyclosporin A (ca.1200 Da), ivermectin B1a and taxanes were applied successfully and regioselective metabolisms of these ligands were reconstituted faithfully on Template.

Versatile applicability of a grid-based CYP3A4 Template to understand the interacting mechanisms with the small-size ligands; part 3 of CYP3A4 Template study.

Modes of interactions of small ligands with CYP3A4 have been defined using the Template established in our previous studies (DMPK. 34: 113-125 2019 and 34 351-364 2019). Interactions of polyaromatic hydrocarbons such as benzo[a]pyrene, pyrene and dibenzo[a,j]acridine were refined with the idea of Right-side movement of ligands at Rings A and B of Template.

Expression, mutation, and methylation of cereblon-pathway genes at pre- and post-lenalidomide treatment in multiple myeloma.

Cereblon (CRBN) is a target for immunomodulatory drugs. This study investigated the prognostic value of the expression of CRBN-pathway genes on the clinical relevance of lenalidomide (Len) treatment and evaluated the levels of CRBN-binding proteins and mutations in these genes after Len treatment. Forty-eight primary multiple myeloma cells were collected prior to treatment with Len and dexamethasone (Ld) and 25 paired samples were obtained post-Ld therapy.

Clinical study designs and patient selection methods based on genomic biomarkers: Points-to-consider documents.

Recently, genomic biomarkers have been widely used clinically for prediction of the efficacy and safety of pharmacotherapy and diagnosis and prognosis of pathological conditions. Therefore, genomic biomarkers are anticipated to accelerate not only precision medicine for pharmacotherapy but also development of molecularly targeted drugs. Because the design of clinical studies involving biomarkers may differ from conventional clinical study designs, a concept paper focused on clinical studies and patient selection methods based on genomic biomarkers is desired to prompt innovative drug development.

Comparison of Efficacy of Dipeptidyl Peptidase-4 Inhibitors and Sodium-Glucose Co-Transporter 2 Inhibitors Between Japanese and Non-Japanese Patients: A Meta-Analysis.

We explored efficacy of dipeptidyl peptidase-4 inhibitors (DPP-4is) and sodium-glucose co-transporter 2 inhibitors (SGLT2is) between Japanese and non-Japanese patients with type 2 diabetes mellitus by conducting a systematic review and meta-analysis. A literature search of public databases before May 2017 identified 91 (DPP-4i) and 63 (SGLT2i) randomized placebo-controlled trials (> 12-week treatment). Multivariate meta-regression analysis identified baseline hemoglobin A1c (HbA1c) levels and placebo responses as covariates affecting efficacy of two agent classes independently of study region (Japanese/non-Japanese).

Tumor lysis syndrome associated with bortezomib: A post-hoc analysis after signal detection using the US Food and Drug Administration Adverse Event Reporting System.

Tumor lysis syndrome (TLS) is a cancer chemotherapy-associated oncologic emergency. Although there have recently been substantial developments in cancer chemotherapy, these may increase the risk of TLS. In this study, we aimed to identify anticancer agents that increase TLS risk, as classified by a TLS panel consensus, using the US Food and Drug Administration Adverse Event Reporting System (FAERS) database.

Solving the interactions of steroidal ligands with CYP3A4 using a grid-base template system.

Using over fifty steroidal ligands, CYP3A4 Template system established in our previous study (DMPK 34: 113-125, 2019) has been evaluated for the applicability for prediction of regioselective metabolisms of steroids in the present study. Plural regional interactions near Site of Oxidation of CYP3A4 (Slide-down and Adaptation) are newly defined for steroid ligands in addition to previously characterized Trigger- and IJL-interactions on Template. Interaction of steroids at ring-A with CYP3A4 residue (Front-residue), at the facial side of Ring B of Template, determined the availability of ligand sitting at Rings A and B of Template.