Empowering Healthcare through Comprehensive Informatics Education: The Status and Future of Biomedical and Health Informatics Education.

OBJECTIVES: Education in biomedical and health informatics is essential for managing complex healthcare systems, bridging the gap between healthcare and information technology, and adapting to the digital requirements of the healthcare industry. This review presents the current status of biomedical and health informatics education domestically and internationally and proposes recommendations for future development. METHODS: We analyzed evidence from reports and papers to explore global trends and international and domestic examples of education. The challenges and future strategies in Korea were also discussed based on the experts' opinions. RESULTS: This review presents international recommendations for establishing education in biomedical and health informatics, as well as global examples at the undergraduate and graduate levels in medical and nursing education. It provides a thorough examination of the best practices, strategies, and competencies in informatics education. The review also assesses the current state of medical informatics and nursing informatics education in Korea. We highlight the challenges faced by academic institutions and conclude with a call to action for educators to enhance the preparation of professionals to effectively utilize technology in any healthcare setting. CONCLUSIONS: To adapt to the digitalization of healthcare, systematic and continuous workforce development is essential. Future education should prioritize curriculum innovations and the establishment of integrated education programs, focusing not only on students but also on educators and all healthcare personnel in the field. Addressing these challenges requires collaboration among educational institutions, academic societies, government agencies, and international bodies dedicated to systematic and continuous workforce development.

LDP-GAN : Generative adversarial networks with local differential privacy for patient medical records synthesis.

Electronic medical records(EMR) have considerable potential to advance healthcare technologies, including medical AI. Nevertheless, due to the privacy issues associated with the sharing of patient's personal information, it is difficult to sufficiently utilize them. Generative models based on deep learning can solve this problem by creating synthetic data similar to real patient data. However, the data used for training these deep learning models run into the risk of getting leaked because of malicious attacks. This means that traditional deep learning-based generative models cannot completely solve the privacy issues. Therefore, we suggested a method to prevent the leakage of training data by protecting the model from malicious attacks using local differential privacy(LDP). Our method was evaluated in terms of utility and privacy. Experimental results demonstrated that the proposed method can generate medical data with reasonable performance while protecting training data from malicious attacks.

Comprehensive in vitro and in silico assessments of metabolic capabilities of 24 genomic variants of CYP2C19 using two different substrates.

Introduction: Most hepatically cleared drugs are metabolized by cytochromes P450 (CYPs), and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provide curated clinical references for CYPs to apply individual genome data for optimized drug therapy. However, incorporating novel pharmacogenetic variants into guidelines takes considerable time. Methods: We comprehensively assessed the drug metabolizing capabilities of CYP2C19 variants discovered through population sequencing of two substrates, S-mephenytoin and omeprazole. Results: Based on established functional assays, 75% (18/24) of the variants not yet described in Pharmacogene Variation (PharmVar) had significantly altered drug metabolizing capabilities. Of them, seven variants with inappreciable protein expression were evaluated as protein damaging by all three in silico prediction algorithms, Sorting intolerant from tolerant (SIFT), Polymorphism Phenotyping v2 (PolyPhen-2), and Combined annotation dependent depletion (CADD). The five variants with decreased metabolic capability (<50%) of wild type for either substrates were evaluated as protein damaging by all three in silico prediction algorithms, except CADD exact score of NM_000769.4:c.593T>C that was 19.68 (<20.0). In the crystal structure of the five polymorphic proteins, each altered residue of all those proteins was observed to affect the key structures of drug binding specificity. We also identified polymorphic proteins indicating different tendencies of metabolic capability between the two substrates (5/24). Discussion: Therefore, we propose a methodology that combines in silico prediction algorithms and functional assays on polymorphic CYPs with multiple substrates to evaluate the changes in the metabolism of all possible genomic variants in CYP genes. The approach would reinforce existing guidelines and provide information for prescribing appropriate medicines for individual patients.

HLA-A*24:02 increase the risk of allopurinol-induced drug reaction with eosinophilia and systemic symptoms in HLA-B*58:01 carriers in a Korean population; a multicenter cross-sectional case-control study.

Background: HLA-B*58:01 is a well-known risk factor for allopurinol-induced severe cutaneous adverse reactions (SCARs). However, only a minority of HLA-B*58:01 carriers suffer SCARs after taking allopurinol. The aim of this study was to investigate subsidiary genetic markers that could identify those at further increased risk of developing allopurinol-induced drug reaction with eosinophilia and systemic symptoms (DRESS) in subjects with HLA-B*58:01. Methods: Subjects with B*58:01 were enrolled (21 allopurinol-induced DRESS and 52 allopurinol-tolerant control). HLA-A, -B, -C and -DRB1 alleles were compared. Comparison of risk between HLAs and allopurinol-induced SCAR in separate populations was performed to support the results. Kruskal-Wallis test, Pearson's chi-square test, Fisher's exact test and binary logistic regression were used to analyze the risk of SCAR development. Results: Frequencies of A*24:02 (71.4 vs. 17.3%, p < 0.001, odds ratio [OR] = 12.0; 95% confidence interval [CI], 3.6-39.2) were significantly higher in B*58:01 (+) DRESS than B*58:01 (+) tolerant controls. In addition, DRB1*13:02 further increased the risk of DRESS. The phenotype frequency of A*24:02/DRB1*13:02 was significantly higher in the B*58:01 (+) DRESS group than in the B*58:01 (+) tolerant controls (52.4% vs. 5.8%, p < 0.001, OR, 66.0; 95% CI, 6.1-716.2). In 2782 allopurinol user cohort, the overall prevalence of DRESS was 0.22%, which increased to 1.62% and 2.86% in the presence of B*58:01 and B*58:01/A*24:02, respectively. Conclusion: The additional secondary screening with A*24:02 and DRB1*13:02 alleles may identify those at further increased risk of allopurinol-induced DRESS in B*58:01 carriers.

ANNO: A General Annotation Tool for Bilingual Clinical Note Information Extraction.

OBJECTIVE: This study was conducted to develop a generalizable annotation tool for bilingual complex clinical text annotation, which led to the design and development of a clinical text annotation tool, ANNO. METHODS: We designed ANNO to enable human annotators to support the annotation of information in clinical documents efficiently and accurately. First, annotations for different classes (word or phrase types) can be tagged according to the type of word using the dictionary function. In addition, it is possible to evaluate and reconcile differences by comparing annotation results between human annotators. Moreover, if the regular expression set for each class is updated during annotation, it is automatically reflected in the new document. The regular expression set created by human annotators is designed such that a word tagged once is automatically labeled in new documents. RESULTS: Because ANNO is a Docker-based web application, users can use it freely without being subjected to dependency issues. Human annotators can share their annotation markups as regular expression sets with a dictionary structure, and they can cross-check their annotated corpora with each other. The dictionary-based regular expression sharing function, cross-check function for each annotator, and standardized input (Microsoft Excel) and output (extensible markup language [XML]) formats are the main features of ANNO. CONCLUSIONS: With the growing need for massively annotated clinical data to support the development of machine learning models, we expect ANNO to be helpful to many researchers.

Flat Pattern Peaks of Tacrolimus Absorption and Associated Pharmacogenomic Variants in Kidney Transplantation Recipients.

BACKGROUND: Tacrolimus is the most commonly used immunosuppressive drug in solid organ transplantation. After administering a conventional twice-daily dose of tacrolimus, peak levels were achieved within the first 1.5 to 2 hours. A group of patients showed different early absorption phase of tacrolimus after kidney transplantation. METHODS: Trough(C0) and 1.5-hour blood levels (C1.5) of tacrolimus were measured in 95 kidney transplantation recipients. Patients with a C1.5/C0 < 1.5 and > 1.5 were defined as those having flat pattern peaks and as controls, respectively. Transplantation outcomes were compared between the groups. Whole exome sequencing was performed to investigate the genetic susceptibility to flat pattern peaks. RESULTS: Twenty-eight patients showed flat pattern peaks. The mean C1.5/C0 values were 1.13 ± 0.22 and 3.78 ± 1.25 in the flat pattern peak and control groups, respectively. In multivariate analysis, flat pattern peak was an independent risk factor for biopsy-proven acute rejection (BPAR) and/or borderline change (P = 0.014). Patients having flat pattern peaks showed significantly lower post-transplant 36-month estimated glomerular filtration rate (P = 0.001). Two single nucleotide variants in ABCB1 genes, rs1922242 and rs2235035, were associated with flat pattern peaks (P = 0.019 and P = 0.027, respectively). CONCLUSION: Both of C1.5 and C0 should be measured to distinguish the patients showing unique initial absorption. A C1.5/C0 ratio lower than 1.5 was associated with an increased risk of BPAR and/or borderline change. Single nucleotide variants s in ABCB1 gene might influence the flat pattern peaks of tacrolimus absorption.

Reducing severe cutaneous adverse and type B adverse drug reactions using pre-stored human leukocyte antigen genotypes.

BACKGROUND: Several type B adverse drug reactions (ADRs), especially severe cutaneous adverse reactions (SCARs), are associated with particular human leukocyte antigen (HLA) genotypes. However, pre-stored HLA information obtained from other clinical workups has not been used to prevent ADRs. We aimed to simulate the preemptive use of pre-stored HLA information in electronic medical records to evaluate whether this information can prevent ADRs. METHODS: We analyzed the incidence and the risk of ADRs for selected HLA alleles (HLA-B*57:01, HLA-B*58:01, HLA-A*31:01, HLA-B*15:02, HLA-B*15:11, HLA-B*13:01, HLA-B*59:01, and HLA-A*32:01) and seven drugs (abacavir, allopurinol, carbamazepine, oxcarbazepine, dapsone, methazolamide, and vancomycin) using pre-stored HLA information of transplant patients based on the Pharmacogenomics Knowledge Base guidelines and experts' consensus. RESULTS: Among 11,988 HLA-tested transplant patients, 4092 (34.1%) had high-risk HLA alleles, 4583 (38.2%) were prescribed risk drugs, and 580 (4.8%) experienced type B ADRs. Patients with HLA-B*58:01 had a significantly higher incidence of type B ADR and SCARs associated with allopurinol use than that of patients without HLA-B*58:01 (17.2% vs. 11.9%, odds ratio [OR] 1.53 [95% confidence interval {CI} 1.09-2.13], p = 0.001, 2.3% versus 0.3%, OR 7.13 [95% CI 2.19-22.69], p < 0.001). Higher risks of type B ADR and SCARs were observed in patients taking carbamazepine or oxcarbazepine if they had one of HLA-A*31:01, HLA-B*15:02, or HLA-B*15:11 alleles. Vancomycin and dapsone use in HLA-A*32:01 and HLA-B*13:01 carriers, respectively, showed trends toward increased risk of type B ADRs. CONCLUSION: Utilization of pre-stored HLA data can prevent type B ADRs including SCARs by screening high-risk patients.

Development and Validation of Targeted Gene Sequencing Panel Based Companion Diagnostic for Korean Patients with Solid Tumors.

Recently, several panels using two representative targeting methods have been developed but they do not reflect racial specificity, especially for Asians. We have developed and analytically validated the Korean Pan-cancer Companion Diagnostic (CDX) Panel to apply targeted anticancer drugs to Korean patients based on the molecular characteristics of tumors using tumor samples without matched patient normal samples. The panel included 31 genes with reported single nucleotide variants, 9 genes with reported copy number variations, and 15 genes with predictive responses to targeted drugs under clinical testing, enabling the panel to be analyzed for the targets of 30 targeted anticancer drugs. It is cost-effective and optimized for cancer type-specific therapy in Korean cancer patients across solid cancer types while minimizing the limitations of existing approaches. In addition, the optimized filtering protocol for somatic variants from tumor-only samples enables researchers to use this panel without matched normal samples. To verify the panel, 241 frozen tumor tissues and 71 formalin-fixed paraffin-embedded (FFPE) samples from several institutes were registered. This gene screening method is expected to reduce test turnaround time and cost, making it a balanced approach to investigate solid cancer-related gene regions.

Time-sequential change in immune-related gene expression after irradiation in glioblastoma: next-generation sequencing analysis.

The time-sequential change in immune-related gene expression of the glioblastoma cell line after irradiation was evaluated to speculate the effect of combined immunotherapy with radiotherapy. The U373 MG glioblastoma cell line was irradiated with 6 Gy single dose. Next-generation sequencing (NGS) transcriptome data was generated before irradiation (control), and at 6, 24, and 48 h post-irradiation. Immune-related pathways were analyzed at each time period. The same analyses were also performed for A549 lung cancer and U87 MG glioblastoma cell lines. Western blotting confirmed the programmed death-ligand 1 (PD-L1) expression levels over time. In the U373 MG cell line, neutrophil-mediated immunity, type I interferon signaling, antigen cross-presentation to T cell, and interferon-γ signals began to increase significantly at 24 h and were upregulated until 48 h after irradiation. The results were similar to those of the A549 and U87 MG cell lines. Without T cell infiltration, PD-L1 did not increase even with upregulated interferon-γ signaling in cancer cells. In conclusions, in the glioblastoma cell line, immune-related signals were significantly upregulated at 24 and 48 h after irradiation. Therefore, the time interval between daily radiotherapy might not be enough to expect full immune responses by combined immune checkpoint inhibitors and newly infiltrating immune cells after irradiation.

Smart Decentralization of Personal Health Records with Physician Apps and Helper Agents on Blockchain: Platform Design and Implementation Study.

BACKGROUND: The Health Avatar Platform provides a mobile health environment with interconnected patient Avatars, physician apps, and intelligent agents (termed IoA3) for data privacy and participatory medicine; however, its fully decentralized architecture has come at the expense of decentralized data management and data provenance. OBJECTIVE: The introduction of blockchain and smart contract technologies to the legacy Health Avatar Platform with a clinical metadata registry remarkably strengthens decentralized health data integrity and immutable transaction traceability at the corresponding data-element level in a privacy-preserving fashion. A crypto-economy ecosystem was built to facilitate secure and traceable exchanges of sensitive health data. METHODS: The Health Avatar Platform decentralizes patient data in appropriate locations (ie, on patients' smartphones and on physicians' smart devices). We implemented an Ethereum-based hash chain for all transactions and smart contract-based processes to guarantee decentralized data integrity and to generate block data containing transaction metadata on-chain. Parameters of all types of data communications were enumerated and incorporated into 3 smart contracts, in this case, a health data transaction manager, a transaction status manager, and an application programming interface transaction manager. The actual decentralized health data are managed in an off-chain manner on appropriate smart devices and authenticated by hashed metadata on-chain. RESULTS: Metadata of each data transaction are captured in a Health Avatar Platform blockchain node by the smart contracts. We provide workflow diagrams each of the 3 use cases of data push (from a physician app or an intelligent agents to a patient Avatar), data pull (request to a patient Avatar by other entities), and data backup transactions. Each transaction can be finely managed at the corresponding data-element level rather than at the resource or document levels. Hash-chained metadata support data element-level verification of data integrity in subsequent transactions. Smart contracts can incentivize transactions for data sharing and intelligent digital health care services. CONCLUSIONS: Health Avatar Platform and interconnected patient Avatars, physician apps, and intelligent agents provide a decentralized blockchain ecosystem for health data that enables trusted and finely tuned data sharing and facilitates health value-creating transactions with smart contracts.

Interplay between IL6 and CRIM1 in thiopurine intolerance due to hematological toxicity in leukemic patients with wild-type NUDT15 and TPMT.

NUDT15 and TPMT variants are strong genetic determinants of thiopurine-induced hematological toxicity. Despite the impact of homozygous CRIM1 on thiopurine toxicity, several patients with wild-type NUDT15, TPMT, and CRIM1 experience thiopurine toxicity, therapeutic failure, and relapse of acute lymphoblastic leukemia (ALL). Novel pharmacogenetic interactions associated with thiopurine intolerance from hematological toxicities were investigated using whole-exome sequencing for last-cycle 6-mercaptopurine dose intensity percentages (DIP) tolerated by pediatric ALL patients (N = 320). IL6 rs13306435 carriers (N = 19) exhibited significantly lower DIP (48.0 ± 27.3%) than non-carriers (N = 209, 69.9 ± 29.0%; p = 0.0016 and 0.0028 by t test and multiple linear regression, respectively). Among 19 carriers, 7 with both heterozygous IL6 rs13306435 and CRIM1 rs3821169 showed significantly decreased DIP (24.7 ± 8.9%) than those with IL6 (N = 12, 61.6 ± 25.1%) or CRIM1 (N = 94, 68.1 ± 28.4%) variants. IL6 and CRIM1 variants showed marked inter-ethnic variability. Four-gene-interplay models revealed the best odds ratio (8.06) and potential population impact [relative risk (5.73), population attributable fraction (58%), number needed to treat (3.67), and number needed to genotype (12.50)]. Interplay between IL6 rs13306435 and CRIM1 rs3821169 was suggested as an independent and/or additive genetic determinant of thiopurine intolerance beyond NUDT15 and TPMT in pediatric ALL.

Different Seasonal Variations of Potassium in Hemodialysis Patients with High Longitudinal Potassium Levels: A Multicenter Cohort Study Using DialysisNet.

PURPOSE: To determine seasonal variations in serum potassium levels among hemodialysis patients. MATERIALS AND METHODS: This was a multicenter cohort study of patients whounderwent hemodialysis and were registered in DialysisNet at our four associated general hospitals between January and December 2016. Month-to-month potassium variability was quantified as SD/√{n/(n-1)}, and a non-hierarchical method was used to cluster groups according to potassium trajectories. Seasonal variations in potassium levels were analyzed using a cosinor analysis. RESULTS: The analysis was performed on 279 patients with a mean potassium level of 5.08±0.58 mmol/L. After clustering, 52.3% (n=146) of patients were included in the moderate group (K+, 4.6±0.4 mmol/L) and 47.7% (n=133) in the high group (K+, 5.6±0.4 mmol/L). The mean potassium level peaked in January in the moderate group (4.83±0.74 mmol/L) and in August in the high group (5.51±0.70 mmol/L). In the high potassium group, potassium levels were significantly higher in summer than in autumn (p<0.001) and spring (p=0.007). Month-to-month potassium variability was greater in the high group than in the moderate group (0.59±0.19 mmol/L vs. 0.52±0.21 mmol/L, respectively, p=0.012). Compared to patients in the first quartile of potassium variability (≤0.395 mmol/L), those with higher variability (2nd-4th quartiles) were 2.8-4.2 fold more likely to be in the high potassium group. CONCLUSION: Different seasonal patterns of serum potassium were identified in the moderate and high potassium groups, with potassium levels being significantly higher in the summer season in the high potassium group and in winter for the moderate potassium group.

In Silico Inference of Synthetic Cytotoxic Interactions from Paclitaxel Responses.

To exploit negatively interacting pairs of cancer somatic mutations in chemotherapy responses or synthetic cytotoxicity (SC), we systematically determined mutational pairs that had significantly lower paclitaxel half maximal inhibitory concentration (IC50) values. We evaluated 407 cell lines with somatic mutation profiles and estimated their copy number and drug-inhibitory concentrations in Genomics of Drug Sensitivity in Cancer (GDSC) database. The SC effect of 142 mutated gene pairs on response to paclitaxel was successfully cross-validated using human cancer datasets for urogenital cancers available in The Cancer Genome Atlas (TCGA) database. We further analyzed the cumulative effect of increasing SC pair numbers on the TP53 tumor suppressor gene. Patients with TCGA bladder and urogenital cancer exhibited improved cancer survival rates as the number of disrupted SC partners (i.e., SYNE2, SON, and/or PRY) of TP53 increased. The prognostic effect of SC burden on response to paclitaxel treatment could be differentiated from response to other cytotoxic drugs. Thus, the concept of pairwise SC may aid the identification of novel therapeutic and prognostic targets.

Effects of Patient-Generated Health Data: Comparison of Two Versions of Long-Term Mobile Personal Health Record Usage Logs.

Patient-generated health data (PGHD) can be managed easily by a mobile personal health record (mPHR) and can increase patient engagement. This study investigated the effect of PGHD functions on mPHR usage. We collected usage log data from an mPHR app, My Chart in My Hand (MCMH), for seven years. We analyzed the number of accesses and trends for each menu by age and sex according to the version-up. Generalized estimating equation (GEE) analysis was used to determine the likelihood of continuous app usage according to the menus and version-up. The total number of users of each version were 15,357 and 51,553, respectively. Adult females under 50 years were the most prevalent user group (30.0%). The "My Chart" menu was the most accessed menu, and the total access count increased by ~10 times after the version-up. The "Health Management" menu designed for PGHD showed the largest degree of increase in its likelihood of continuous usage after the version-up (1.245; p < 0.0001) across menus (range: 0.925-1.050). Notably, improvement of PGHD management in adult females over 50 years is needed.

Identification of synthetic chemosensitivity genes paired with BRAF for BRAF/MAPK inhibitors.

Molecular-targeted approaches are important for personalised cancer treatment, which requires knowledge regarding drug target specificity. Here, we used the synthetic lethality concept to identify candidate gene pairs with synergistic effects on drug responses. A synergistic chemo-sensitivity response was identified if a drug had a significantly lower half-maximal inhibitory concentration (IC50) in cell lines with a pair of mutated genes compared with those in other cell lines (wild-type or one mutated gene). Among significantly damaging mutations in the Genomics of Drug Sensitivity in Cancer database, we found 580 candidate synergistic chemo-sensitivity interaction sets for 456 genes and 54 commercial drugs. Clustering analyses according to drug/gene and drug/tissue interactions showed that BRAF/MAPK inhibitors clustered together; 11 partner genes for BRAF were identified. The combined effects of these partners on IC50 values were significant for both drug-specific and drug-combined comparisons. Survival analysis using The Cancer Genome Atlas data showed that patients who had mutated gene pairs in synergistic interaction sets had longer overall survival compared with that in patients with other mutation profiles. Overall, this analysis demonstrated that synergistic drug-responsive gene pairs could be successfully used as predictive markers of drug sensitivity and patient survival, offering new targets for personalised medicine.

Identifying genetic variants associated with ritodrine-induced pulmonary edema.

INTRODUCTION: Ritodrine is one of the most commonly used tocolytics in preterm labor, acting as a ß2-adrenergic agonist that reduces intracellular calcium levels and prevents myometrial activation. Ritodrine infusion can result in serious maternal complications, and pulmonary edema is a particular concern among these. The cause of pulmonary edema following ritodrine treatment is multifactorial; however, the contributing genetic factors remain poorly understood. This study investigates the genetic variants associated with ritodrine-induced pulmonary edema. METHODS: In this case-control study, 16 patients who developed pulmonary edema during ritodrine infusion [case], and 16 pregnant women who were treated with ritodrine and did not develop pulmonary edema [control] were included. The control pregnant women were selected after matching for plurality and gestational age at the time of tocolytic use. Maternal blood was collected during admission for tocolytic treatment, and whole exome sequencing was performed with the stored blood samples. RESULTS: Gene-wise variant burden (GVB) analysis resulted in a total of 71 candidate genes by comparing the cumulative effects of multiple coding variants for 19729 protein-coding genes between the patients with pulmonary edema and the matched controls. Subsequent data analysis selected only the statistically significant and deleterious variants compatible with ritodrine-induced pulmonary edema. Two final candidate variants in CPT2 and ADRA1A were confirmed by Sanger sequencing. CONCLUSIONS: We identified new potential variants in genes that play a role in cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA) regulation, which supports their putative involvement in the predisposition to ritodrine-induced pulmonary edema in pregnant women.

Immune expression signatures as candidate prognostic biomarkers of age and gender survival differences in cutaneous melanoma.

This study aims to investigate the difference of gene expression and its prognostic significance in younger women with melanoma. Significantly upregulated genes in tumors compared to normal skin tissues were extracted. Among these genes, genes that significantly affected survival according to expression level were selected, and pathway annotation was performed. The patient proportion with high/low expression of the most significant pathways was analyzed in each age (< 50, 50-59, ≥ 60) and gender group. Survival was analyzed according to age, gender, and pathways. The most significant pathways that were upregulated in tumor tissues and also had impacts on survival were programmed cell death protein [PD]-1, interferon-γ, and interferon-α/ß pathways. In women, the immune signaling rate in patients was higher than men and decreased with age (63.5%, 53.8%, and 47.6%). In men, the decreasing tendency was minimal (47.6%, 50.0%, and 41.6%). In patients aged < 60 years, women had a favorable survival rate than men (p = 0.055). Except for patients with high immune signaling, no survival difference was observed between genders (p = 0.6). In conclusion, younger female melanoma patients had high immune signaling than older women and men. This immune signaling improved survival of the younger female patients.

High-Throughput Algorithm for Discovering New Drug Indications by Utilizing Large-Scale Electronic Medical Record Data.

Drug repositioning is an effective way to mitigate the production problem in the pharmaceutical industry. Electronic medical record (EMR) databases harbor a large amount of data on drug prescriptions and laboratory test results and may thus be useful for finding new indications for existing drugs. Here, we present a novel high-throughput data-driven algorithm that identifies and prioritizes drug candidates that show significant effects on specific clinical indicators by utilizing large-scale EMR data. We chose four laboratory tests as clinical indicators: hemoglobin A1c (HbA1c), low-density lipoprotein (LDL) cholesterol, triglycerides (TGs), and high-density lipoprotein (HDL) cholesterol. From a 5-year EMR database, we generated datasets consisting of paired data with averaged measurement values during on and off each drug in each patient, adjusted for co-administered drug effects at each timepoint, and applied one sample t-test with the Bonferroni correction for statistical analysis. Among 1,774 drugs, 45 were associated with increases in HDL cholesterol, and 41, 146, and 65 were associated with reductions in HbA1c, LDL cholesterol, and TGs, respectively. We compared the list of candidate drugs with that of drugs indicated for relevant clinical conditions and found that the algorithm had high values for both sensitivity (range 0.95-1.00) and negative predictive value (range 0.95-1.00). Our algorithm was able to rediscover well-known drugs that are used for diabetes and dyslipidemia while revealing potential candidates without current indications but have shown promising results in the literature. Our algorithm may facilitate the repositioning of drugs with proven safety profiles.

Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach.

BACKGROUND: Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a severe mismatch reaction, and the result can also support the diagnosis of various disease or prediction of drug side effects. However, such secondary applications of HLA typing results are limited because they are typically provided in free-text format or PDFs on electronic medical records. We here propose a method to convert HLA genotype information stored in an unstructured format into a reusable structured format by extracting serotype/allele information. METHODS: We queried HLA typing reports from the clinical data warehouse of Seoul National University Hospital (SUPPREME) from 2000 to 2018 as a rule-development data set (64,024 reports) and from the most recent year (6,181 reports) as a test set. We used a rule-based natural language approach using a Python regex function to extract the 1) number of patients in the report, 2) clinical characteristics such as indication of the HLA testing, and 3) precise HLA genotypes. The performance of the rules and codes was evaluated by comparison between the extracted results from the test set and a validation set generated by manual curation. RESULTS: Among 11,287 reports for development set and 1,107 for the test set describing HLA typing for a single patient, iterative rule generation developed 124 extracting rules and 8 cleaning rules for HLA genotypes. Application of these rules extracted HLA genotypes with 0.892-0.999 precision and 0.795-0.998 recall for the five HLA genes. The precision and recall of the extracting rules for the number of patients in a report were 0.997 and 0.994 and those for the clinical variable extraction were 0.997 and 0.992, respectively. All extracted HLA alleles and serotypes were transformed according to formal HLA nomenclature by the cleaning rules. CONCLUSION: The rule-based HLA genotype extraction method shows reliable accuracy. We believe that there are significant number of patients who takes profit when this under-used genetic information will be return to them.

Real-world treatment patterns of renal anemia in hemodialysis patients: A multicenter cohort study performed using DialysisNet (RRAHD study).

A multicenter cohort study.The DialysisNet was previously developed for the management of hemodialysis (HD) patients based on the American Society for Testing and Materials Continuity of Care Records by metadata transformation. DialysisNet is a dialysis patient management program created by using the personal health record care platform to overcome the problems of registry studies, in real-time.Here, we aimed to investigate the pattern of treatment for renal anemia in HD patients using DialysisNet.We performed a multicenter cohort study among HD patients who were treated at one of the three Korean university-affiliated hospitals from January 2016 to December 2016. Subjects were divided into 4 hemoglobin variability groups by quartiles. The variable anemia treatment pattern was reviewed. To determine renal anemia treatment patterns, we automatically collected information on the practice of anemia treatment patterns such as erythropoietin stimulating agent (ESA) doses and administration frequencies, and targeted hemoglobin maintenance rate. Individual hemoglobin variabilities were expressed as (standard deviations)/(√(n/[n-1]).The records of 159 patients were analyzed (Hospital A: 35, Hospital B: 21, Hospital C: 103). Mean patients' age was 65.6 ±â€Š12.8 years, and 61.6% were men. Overall, hemoglobin level was 10.5[7.43;13.93] g/dL. 158 (99.3%) patients were using ESA; and overall, the epoetin alfa dose was 33,000[4000;136,800] U per week. Hemoglobin levels (P = .206) and epoetin alfa doses were similar (P = .924) for patients with different hemoglobin variabilities. The hemoglobin target maintenance rate was lower in the highest hemoglobin variability group than in the lowest variability group (P = .045).In this study, detailed information on the actual anemia treatment patterns were obtained using the DialysisNet. We expect that DialysisNet will simplify and improve the renal anemia management for both dialysis patients and health care providers.