Dr. Abdullah Al-Mamun is an Assistant Professor in the Department of Pharmaceutical Systems and Policy in the School of Pharmacy. He received his PhD in Computing and Information Sciences from the University of Northumbria at Newcastle, UK.

Assistant Professor

Organization:

West Virginia University School of Pharmacy

Department:

Pharmaceutical Systems & Policy

Classification:

Faculty

• PhD, University of Northumbria, Newcastle, UK

1. Ramazani, M., Brothers, T., Ahmed, I,., Al-Mamun, M.A., Synthetic Data-Driven Early Prediction Framework for Acute Kidney Injury in Patients Receiving Vancomycin and Ceftazidime/Avibactam, Pharmacotherapy, 2025. DOI: 10.1002/phar.70064
2. Corcoran, K.E., Martinez, S.A., Tsikis, S., Al‐Mamun, M.A. and Intestinal Malrotation Clinician Group. Long‐term gastrointestinal outcomes in pediatric intestinal malrotation patients following operative treatment. Journal of Pediatric Gastroenterology and Nutrition, 2025. DOI: 10.1002/jpn3.70204
3. Al-Mamun MA, Jeun KJ, Brothers T, Asare EO, Shawwa K, Ahmed I. Evaluating the kidney disease progression using a comprehensive patient profiling algorithm: A hybrid clustering approach. Plos one. 2025 Jul 11;20(7):e0310749. DOI: 10.1371/journal.pone.0310749
4. Dangpiaei S, Al-Mamun MA. Evaluating health-related quality of life and health resource utilization among Gabapentinoid users with substance use disorder in the US: Trends, co-prescriptions, and cost analysis. Exploratory Research in Clinical and Social Pharmacy. 2025 Jun 8:100618.DOI: 10.1016/j.rcsop.2025.100618
5. Kido K, Al-Mamun MA. Risk Assessment of Amiodarone Use in Patients with Cirrhosis and Heart Failure. Current Drug Safety. 2025 May 8. DOI: 10.2174/0115748863361411250419155302
6. Kido K, Al-Mamun MA. Evaluation of patients with heart failure with reduced ejection fraction treated with bumetanide versus torsemide. Cardiology. 2025 Apr 14. DOI: 10.1159/000545876
7. Ramesh A, Doddi A, Abbasi A, Al-Mamun MA, Sakhuja A, Shawwa K. Use of vasopressors in patients with acute kidney injury on continuous kidney replacement therapy. PLoS One. 2024 Dec 19;19(12):e0315643. DOI: 10.1371/journal.pone.0315643
8. Dai Z, Abate MA, Al-Mamun MA, Kraner JC, Mock AR, Smith GS. Male Predominance in West Virginia Unintentional Overdose Deaths Is Influenced by Alcohol and Co-Intoxicants. Journal of Studies on Alcohol and Drugs. 2025 May;86(3):358-66.https://doi.org/10.15288/jsad.24-00054
9. Jeun KJ, Al-Mamun M. Impact of Treatment with Central Nervous System Stimulant and Risk of Substance Use Disorder in Adults with Attention-Deficit/Hyperactivity Disorder. International Journal of Mental Health and Addiction. 2024 May 28:1-4.https://doi.org/10.1007/s11469-024-01324-x
10. Adjeroh L, Brothers T, Shawwa K, Ikram M, Al-Mamun MA. The association between polypharmacy and health-related quality of life among non-dialysis chronic kidney disease patients. Plos one. 2023 Nov 13;18(11):e0293912. https://doi.org/10.1371/journal.pone.0293912

The full publications list can be found here

https://scholar.google.com/citations?user=9Ga2RnYAAAAJ&hl=en

ResearchGate profile can be found here

https://www.researchgate.net/profile/Mohammad-Al-Mamun-5

Dr. Al-Mamun has taught the following courses.                                                                    

1. PHAR 786: Health Svcs Res/Sec Databases, Spring 2022                                               

2. PHAR 769: Adv Hlth Service Rsrch Methods, Fall 2022                                                    

3. PHAR 788: Grad Sem-Hlth Outcomes Rsrch, Fall 2022                                                                                                                            

Dr. Abdullah Al-Mamun is an Assistant Professor in the Department of Pharmaceutical Systems and Policy in the School of Pharmacy at West Virginia University (WVU). He received his PhD in Computing and Information Sciences from the University of Northumbria at Newcastle, UK. Prior to joining WVU, he worked as a Health Outcomes Data Science faculty in the College of Pharmacy at the University of Rhode Island. He completed two postdoctoral fellowships in Epidemiology of Microbial Diseases in the Department of Population Medicine & Diagnostic Sciences at Cornell University and in the Yale School of Public Health at Yale University.

In training, he is a health data scientist specializing in the areas of health outcomes, data science and epidemiology. He brings interdisciplinary research experiences in building mathematical modeling and health data science tools (predictive models, machine learning) to understand disease dynamics at both individual- and population level. His research provides cutting-edge methods and tools to interpret and address the research questions related to health outcomes, big data, and epidemiological surveillance systems. His current research is expanded on three themes: (1) understanding polysubstance use among the people who use opioids using state- and national-level surveillance datasets, (2) understanding medication regimen complexity among critically ill patients using the intensive care unit data, and (3) understanding spatiotemporal dynamics of vector-borne diseases (West Nile and Eastern Equine Encephalitis Viruses) in the USA using national-level surveillance datasets.

Health Outcomes and BigData Informatics (HealBig)

Dr. Al-Mamun’s research lab name is HealBig- Health Outcomes and BigData Informatics. HealBig mainly focuses on understanding complex data problems in health outcomes and services-related research problems. HealBig develops and improves methods like mathematical and agent-based models, decision support systems, data mining, and machine learning within the health outcomes research domain. The overarching goal of HealBig is to develop health data science tools through interdisciplinary collaboration among health data scientists, physicians, clinical pharmacists, and other healthcare professionals.

Research Projects

Acute Kidney Injury (AKI) and Chronic Kidney Disease (CKD)

HealBig develops new and novel methods and tools to understand AKI among hospitalized patients. AKI occurred in over 1 of 5 hospitalizations in the U.S. Acute kidney injury (AKI) is a common and severe clinical event affecting up to 15.0% of hospitalized patients and up to 50.0% of intensive care unit patients. AKI can sometimes lead to chronic kidney disease (CKD). The existing epidemiology studies identify AKI as an independent risk factor for CKD, including End Stage Renal Disease (ESRD). In our lab, we utilized a range of datasets (e.g., EHR data, hospitalization data, national-level clinical and survey data) to understand the correlates of AKI and CKD among different populations. The existing projects related to AKI and CKD are provided below.

1. AKI among the critically ill patients
2. CKD progression and Clinical outcomes
3. Impact of nephrotoxic medications
4. Complex medication regimens and polypharmacy

Polysubstance Use and Opioid Epidemic

West Virginia (WV) is currently the 8th highest opioid prescribing state but has the highest opioid overdose fatality rate. Most fatal overdoses involved synthetic illicit opioids such as fentanyl or fentanyl analogs, usually with multiple drugs, including other opioids, benzodiazepines, methamphetamine/other stimulants, or antidepressants. However, polysubstance involvement in fatal and non-fatal WV overdoses is unpredictable and poorly characterized. Thus, it is important to address multiple substance use in overdose response programs and opioid misuse treatment. Our project team works on multiple projects to develop data mining and machine learning tools to understand the patterns of polysubstance use and correlates of fatal and non-fatal drug overdoses. We utilized state-level datasets from WVOCME: West Virginia Office of Chief Medical Examiner - Forensic Drug Database [FDD]), WV CSMP: West Virginia Board of Pharmacy Controlled Substance Monitoring Program, and TriNetx: an electronic health records dataset consisting of 2 million unique patient records.

Rare Diseases

The HealBig created a project team consisting of clinicians, pharmacists and nurses to understand the diagnosis delays and correlates to multiple rare diseases. So far, we have investigated two rare diseases: Transthyretin Amyloid Cardiomyopathy (ATTR-CM) and Merkel Cell Carcinoma (MCC). Our goal is to develop prognostic and prediction tools to identify rare diseases timely promptly.

Research Interests

• Digital Health
• Clinical Decision Support System
• Health Outcomes
• Health Resource Utilizations
• Health Outcomes Data Science
• Machine Learning

Disease Area

• Acute and Chronic Kidney Injury 
• Fatal and non-fatal drug overdoses
• Rare Diseases
• Infectious Diseases

Methodologies

• Large Language and natural language processing models
• Advanced statistical modeling (Survival models, time series models, propensity score matching) 
• Data mining (association rule mining, clustering)
• Mathematical modeling (infectious disease, agent-based, cellular automata, and dynamic models)
• Machine learning and Synthetic data modeling

Media Coverage

• https://health.wvu.edu/research/grants/optocs-ai-optimizing-pharmacy-transition-of-care-services-using-artificial-intelligence/
• https://www.youtube.com/watch?v=wmfMqY97cqI (7:10-10:10 minutes)
• https://wvutoday.wvu.edu/stories/2024/03/21/wvu-pharmacists-using-ai-to-help-lower-patient-readmission-rates
• https://www.register-herald.com/wvu-pharmacists-using-ai-to-help-lower-patient-re-admission-rates/article_26fd9a46-ed18-11ee-8454-3feb47497535.html
• https://wvctsi.org/news/story?headline=wvctsi-announces-latest-recipients-of-research-project-funding_1

Google Scholar link https://scholar.google.com/citations?user=9Ga2RnYAAAAJ&hl=en

ResearchGate link https://www.researchgate.net/profile/Mohammad-Al-Mamun-5