Development of an online warfarin dosing platform using R programming language to facilitate healthcare professional duties and limit medication related errors.

Development of an online warfarin dosing platform using R programming language to facilitate healthcare professional duties and limit medication related errors. Monther Alsultan, Joshua M. Morriss, Daniel Contaifer Jr, Suad Alshammari; Silas Contaifer, Rachel W Flurie, Dayanjan S. Wijesinghe# Department of Pharmacotherapy and Outcome Sciences Objective: 1) Gain experience in developing platform agnostic, fully operational and clinically relevant web applications for effective pharmacist led patient care. 2) Create a decision- support tool using open source software to facilitate evidence-based management therapy of warfarin in clinical settings where it is available for everyone to use at anytime and anywhere. Introduction: Healthcare is continuously growing and modern technologies provide opportunities for the creation of effective tools to manage multiple diseases. Mobile devices such as smartphones enable easy access to a variety of websites remotely and make data and information readily available for use. Additionally, mobile devices can offer healthcare providers with fast and easy access to essential medical information to support patient care. The profession of pharmacy is fast changing from one primarily focused on dispensing medicinal goods to one intensely focused on the delivery of patient care. This has led pharmacists to be involved in a diverse clinical service such as patient\u27s education, Medication Therapy Management (MTM) and medications dose adjustment. Implementing such services often place additional stress on the daily routine of pharmacists. Therefore, there is a high need to find efficient ways to support healthcare related clinical services. One of the widely used anticoagulant medications is warfarin. Warfarin has been available on the market as effective therapy in management of thrombotic disorders. However, warfarin is frequently associated with medications errors which may lead to serious adverse events. The purpose of this paper is to demonstrate this fact fully via warfarin dosing web application to help support healthcare professionals in clinical settings. Methods: Open-source programming language R in conjunction with RStudio version 1.2.5033 were used to develop and implement our warfarin dosing platform. Shiny packages for R with other packages were used to create our platform as a web-based app. We based our calculations and function of our platform on the UW health warfarin management- adult- ambulatory clinical practice guidelines. Results: The platform contains three tools users can use:1) Calculating the warfarin maintenance dose,2) Selecting INR goals and duration of therapy,3) Assessment of Bleeding risk. Additionally, the app has a hyperlink to direct the users to the resource used in this app. On the first page of the app, the user can select their INR target and input a patients INR and weekly dose. Then, the app will immediately display the results. On the second page of the app, there is a feature for users helps to choose the INR target recommended based on patient conditions; There is a drop down menu contains different type of antithrombotic indications. Additionally, on the third page of the app, there is a feature for users helps to calculate the bleeding risk using HAS-BLED score. The users can answer “Yes” or “No” on multiple risk factors to stratify patients’ risk into low, moderate or high. Conclusion: Our warfarin dosing platform demonstrates the feasibility of creating a free-tool for healthcare professionals to facilitate their daily practice and potential for reducing medication related errors. Additionally, we demonstrate that pharmacists can take advantage of open-sources resources available to develop any health-related application suitable to their needs. Future Directions: The skills gained in the implementation of this full stack web application development will be further improved upon to develop additional clinical support tools for pharmacists. Further implementations will also incorporate fully or partially trained machine learning models. Our ultimate goal is to allow pharmacists to utilize data driven decision making strategies to implement fast and effective patient care.https://scholarscompass.vcu.edu/gradposters/1160/thumbnail.jp

Development of an R script for simple lipidomic and metabolomic data analysis

Background: Metabolomic and lipidomic studies generate vast quantities of data that are often analysed in a closed software environment with little to no access to the underlying algorithms. As a result, data processed via different software pipelines yield different results thus leading to a widespread problem of low reproducibility within these fields. To address this problem, we are developing LipidAnalyst; an R based lipidomics software pipeline. As a part of this project, we are creating a simple statistical analysis and graphing module in R to generate accurate, reproducible, high-resolution figures. Methods: R scripts were developed under version 3.5.3 with the capability to undertake statistical analyses (e.g. ANOVA) and post-hoc tests (e.g. Tukey). Additional code plotted resultant information as high resolution violin and box plots that depicted statistical significance. Thereafter, lipidomic and metabolomic data were analysed by this code and compared against commercial software and Metaboanalyst, a primary software used in metabolomic and lipidomic research. Results: Code generated in house demonstrated the same results as those generated using commercial software (e.g. JMP 14.0 Pro) but were different from results obtained by using the MetaboAnalyst pipeline. Conclusions: This study demonstrated the prevalent danger of using closed-source software pipelines for the analysis of lipidomic and metabolomic data without validating the analysis outcomes via open-source software. Open source software such as LipidAnalyst, that has also been independently validated using multiple data sets, can then be published with the results to enable transparency of data analysis and improve the replicability of results across different labs.https://scholarscompass.vcu.edu/gradposters/1092/thumbnail.jp

Acute Fish Oil supplementation and Aspirin treatment modulates lipid profile in Platelet Rich Plasma: a randomized pilot trial

Aims: Platelet rich plasma (PRP) has been used in tissue repair to treat numerous inflammatory pathophysiologies. Recent studies have elucidated that the bioactive lipid fraction of PRP significantly contributes towards the resolution of inflammation. There has been great interest in how therapeutics could modulate the PRP lipidome to formulate a more pro-resolving matrix. Many of the pathways used to produce either pro-resolving or pro-inflammatory lipids are shared between ω-3 and ω-6 polyunsaturated fatty acids (PUFA). Here, we explored the separate and interacting effects acute exogenous ω-3 PUFA supplementation and aspirin had on the lipidome of PRP within 6 hours. Methods:PRP from 45 patients was obtained at baseline and after 6-hours from either control or those receiving one 1400 mg fish oil tablet, Bayer low-dose aspirin (81mg), or combinational therapy. Lipids were acquired by liquid chromatography mass spectrometry. Spearman rank correlation analysis visually assessed what effects treatments had on the relative abundance of PUFA derivatives. The control group was referenced for lipid selection across groups; lipids were selected on the basis that they significantly (p Results: Fish oil ω-3 PUFA supplementation and aspirin had separate and interacting effects on oxylipin and neutral lipid correlations. Strongly correlated (rho \u3e 0.65) ω-6 PUFA metabolites were reversed or reduced in magnitude following either treatment. A total of 24 lipid species were significantly modulated in the fish oil treatment group, with notable (p4), and lipoxin A4 (LXA4). Conclusion: We can confirm that fish oil supplementation and aspirin do exert modulatory effects on the lipid fraction of PRP within a short period of time (6-hours). The PUFAs composing fish oil impacted a wide range of the lipidome – possibly though a mechanism of ω-3/ω-6 enzymatic competition. Our results support that ω-3 PUFA supplementation may improve the efficacy of PRP for short-term use

Molecular Predictors of Anakinra Treatment Success in Heart Failure Patients with Reduced Ejection Fraction

Background. Kineret (Anakinra) is an interleukin-1 antagonist that is under investigation for its novel clinical application treating patients that have heart failure with reduced (\u3c50%) ejection fraction (HFrEF). A prior study from our group indicated that Anakinra may restore heart function by addressing dysregulations in HFrEF metabolic pathways. Herein, we attempt to elicit Anakinra’s effects on both metabolome and lipidome. Methods. Lipids and metabolites that had previously been quantified by mass spectrometry (MS) from patients (n=49) who had ≥2 mg/L of high-sensitivity C-reactive protein (hs-CRP) were mTIC normalized and transformed. We conducted a stepwise Linear Discriminant Analysis (r- LDA) to test Anakinra (2 and 12 weeks) vs placebo for separation from combined baseline. Metabolic pathway analysis was performed with Fisher’s exact test algorithm for detection of over-represented and enriched analytes. Univariate analysis (one tailed t-test p\u3c0.05) compared placebo and Anakinra after 12-weeks for effect(s). Metaboanalyst 4.0, JMP Pro 14.0, and a proprietary package in R (version 3.4.4) were the software for all analyses and data wrangling. Results. Analytes such as acylcarnitines C10:0 and C16:0 and hsCRP showed significant improvements after 12 weeks of Anakinra, leading to improved mitochondrial function, reduced inflammation, and overall better health outcomes. Statistically significant (p\u3c0.05) pathways including the citrate cycle, cysteine and methionine metabolism, galactose metabolism among others were associated with treatment. Conclusions. We were able to determine significant alterations to metabolomic and lipidomic concentrations after 12 weeks of Anakinra therapy. Our biochemical analyses verifies that Anakinra did improve heart function within our HFrEF pilot cohort.https://scholarscompass.vcu.edu/gradposters/1081/thumbnail.jp

OVERCOMING CONTEMPORARY CHALLENGES IN KIDNEY DISEASE TREATMENT THROUGH METABOLOMIC AND DATA SCIENCE APPROACHES

Early identification and therapy are essential for preventing the worsening of kidney function. However, the lack of predictive, noninvasive biomarkers has posed a challenge in the diagnosis and management of this prevalent condition. Furthermore, there are barriers to effective treatment that limit our capacity to provide improved health management for individuals with kidney failure. The main objectives are to: Identify the challenges of current biomarkers in kidney disease and propose a metabolomic approach to overcome them by investigating metabolomic alterations associated with the etiology of renal disease, and discuss barriers to optimal care in CKD and discusses the role of data science in improving healthcare. To explore biomarkers and etiology of kidney dysfunction, untargeted lipidomic analysis was performed from a prospective observational cohort of adult kidney transplant patients. To overcome the barriers to optimal care in CKD, an open-source programming language was used to develop and implement an anticoagulant agents platform. Our lipidomic study of kidney transplant patients identified lipid predictors of kidney rejection. This study’ findings show that the lipidome may be used to predict graft function in kidney transplant recipients. A clinical decision support application was developed to provide anticoagulation management guidance. It provides tools for calculating warfarin dosing, and providing anticoagulation methods for individuals with renal impairment. This dissertation also illustrates that lipidomic biomarkers have the potential to provide valuable insights into the health status of patients. Further research is needed to strengthen our lipid biomarker findings and to validate our decision-making tool in real-world practice