Development of a System for Postmarketing Population Pharmacokinetic and Pharmacodynamic Studies Using Real‐World Data From Electronic Health Records

Choi, Leena; Beck, Cole; McNeer, Elizabeth; Weeks, Hannah L.; Williams, Michael L.; James, Nathan T.; Niu, Xinnan; Abou‐Khalil, Bassel; Birdwell, Kelly A.; Roden, Dan M.; Stein, C. Michael; Bejan, Cosmin Adrian; Denny, Joshua C.; Driest, Sara L. Van

doi:10.1002/cpt.1787

Cited by 26 publications

(39 citation statements)

References 23 publications

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“…This process contributed to increasing the sample size of drug exposure cohorts and to identifying exposure of drugs that were not prescribed at VUMC (e.g., over‐the‐counter drugs or drugs prescribed by outside providers). For this, we used MedXN‐v1.0.3, 15 a high‐performance NLP drug extractor previously evaluated on the Vanderbilt EHR, 16 , 17 to parse > 1 million notes with dates between February 15, 2019, and PCR test time. There was no filter restriction by note type for NLP‐based drug extraction; thus, notes such as problem lists, clinical communications, and outpatient Rx order summaries were also included in this process.…”

Section: Methodsmentioning

confidence: 99%

DrugWAS: Drug‐wide Association Studies for COVID‐19 Drug Repurposing

Bejan

Cahill

Staso

et al. 2021

Clin Pharma and Therapeutics

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This study aimed to systematically investigate if any of the available drugs in the electronic health record (EHR) can be repurposed as potential treatment for coronavirus disease 2019 . Based on a retrospective cohort analysis of EHR data, drug-wide association studies (DrugWAS) were performed on 9,748 patients with COVID-19 at Vanderbilt University Medical Center (VUMC). For each drug study, multivariable logistic regression with overlap weighting using propensity score was applied to estimate the effect of drug exposure on COVID-19 disease outcomes. Patient exposure to a drug between 3-months prior to the pandemic and the COVID-19 diagnosis was chosen as the exposure of interest. All-cause of death was selected as the primary outcome. Hospitalization, admission to the intensive care unit, and need for mechanical ventilation were identified as secondary outcomes. Overall, 17 drugs were significantly associated with decreased COVID-19 severity. Previous exposure to two types of 13-valent pneumococcal conjugate vaccines, PCV13 (odds ratio (OR), 0.31, 95% confidence interval (CI), 0.12-0.81 and OR, 0.33, 95% CI, 0.15-0.73), diphtheria toxoid and tetanus toxoid vaccine (OR, 0.38, 95% CI, 0.15-0.93) were significantly associated with a decreased risk of death (primary outcome). Secondary analyses identified several other significant associations showing lower risk for COVID-19 outcomes: acellular pertussis vaccine, 23-valent pneumococcal polysaccharide vaccine (PPSV23), flaxseed extract, ethinyl estradiol, estradiol, turmeric extract, ubidecarenone, azelastine, pseudoephedrine, dextromethorphan, omega-3 fatty acids, fluticasone, and ibuprofen. In conclusion, this cohort study leveraged EHR data to identify a list of drugs that could be repurposed to improve COVID-19 outcomes. Further randomized clinical trials are needed to investigate the efficacy of the proposed drugs.Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has triggered a pandemic infection leading to unprecedented excess mortality and adverse consequences to global economy. 1,2 According to the World Health Organization (WHO), SARS-CoV-2 has spread to over 222 countries and territories resulting in > 81 million

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Section: Methodsmentioning

confidence: 99%

DrugWAS: Drug‐wide Association Studies for COVID‐19 Drug Repurposing

Bejan

Cahill

Staso

et al. 2021

Clin Pharma and Therapeutics

Self Cite

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“…This process was particularly useful to identify exposure to over-the-counter drugs or to drugs prescribed by outside providers. For this, we employed MedXN-v1.0.3, 24 a high-performance NLP drug extractor previously evaluated on Vanderbilt EHR, 25,26 to parse >789,000 notes with dates between February 15, 2019 and PCR test time. There was no filter restriction by note type for NLP-based drug extraction; thus, notes such as problem lists, clinical communications, and outpatient Rx order summaries were also included in this process.…”

Section: Methodsmentioning

confidence: 99%

DrugWAS: Leveraging drug-wide association studies to facilitate drug repurposing for COVID-19

Bejan

Cahill

Staso

et al. 2021

Preprint

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Importance: There is an unprecedented need to rapidly identify safe and effective treatments for the novel coronavirus disease 2019 (COVID-19). Objective: To systematically investigate if any of the available drugs in Electronic Health Record (EHR), including prescription drugs and dietary supplements, can be repurposed as potential treatment for COVID-19. Design, Setting, and Participants: Based on a retrospective cohort analysis of EHR data, drug-wide association studies (DrugWAS) were performed on COVID-19 patients at Vanderbilt University Medical Center (VUMC). For each drug study, multivariable logistic regression with overlap weighting using propensity score was applied to estimate the effect of drug exposure on COVID-19 disease outcomes. Exposures: Patient exposure to a drug during 1-year prior to the pandemic and COVID-19 diagnosis was chosen as exposure of interest. Natural language processing was employed to extract drug information from clinical notes, in addition to the prescription drug data available in structured format. Main Outcomes and Measures: All-cause of death was selected as primary outcome. Hospitalization, admission to the intensive care unit (ICU), and need for mechanical ventilation were identified as secondary outcomes. Results: The study included 7,768 COVID-19 patients, of which 509 (6.55%) were hospitalized, 82 (1.06%) were admitted to ICU, 64 (0.82%) received mechanical ventilation, and 90 (1.16%) died. Overall, 15 drugs were significantly associated with decreased COVID-19 severity. Previous exposure to either Streptococcus pneumoniae vaccines (adjusted odds ratio [OR], 0.38; 95% CI, 0.14-0.98), diphtheria toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98), and tetanus toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98) were significantly associated with a decreased risk of death (primary outcome). Secondary analyses identified several other significant associations showing lower risk for COVID-19 outcomes: 2 vaccines (acellular pertussis, Streptococcus pneumoniae), 3 dietary supplements (turmeric extract, flaxseed extract, omega-3 fatty acids), methylprednisolone acetate, pseudoephedrine, ethinyl estradiol, estradiol, ibuprofen, and fluticasone. Conclusions and Relevance: This cohort study leveraged EHR data to identify a list of drugs that could be repurposed to improve COVID-19 outcomes. Further randomized clinical trials are needed to investigate the efficacy of the proposed drugs.

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“…Our study results will be useful for PK studies performing using observational data such as EHRs for many medications having similar PK characteristics, such as a long half-life. 20…”

Section: Discussionmentioning

confidence: 99%

“…We recently developed a natural language processing (NLP) system, medExtractR , 18 to extract medication information from free-text clinical notes as part of a system to enable the use of EHRs in retrospective studies of drugs. 19,20 The system, once finalized, should relieve the primary burden in data generation and manual extraction of medication data. In addition to drug dosing information, medExtractR is designed to extract explicit last dosing times (timing of the dose prior to a recorded blood concentration) if present in the notes.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of Estimated Tacrolimus Population Pharmacokinetic Profile to Inaccurate Assumptions about Dose Timing and Absorption: An Investigation in Real-World and Simulated Data

Williams

Weeks

Beck

et al. 2021

Preprint

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A tacrolimus population pharmacokinetic (PK) study with 440 subjects was performed using real world data extracted from electronic heath records (EHRs) to identify patient factors affecting variability in tacrolimus PK parameters. Using last-dose times extracted by our own natural language processing system, medExtractR, we assessed the effects of incorporating last-dose times in the data on tacrolimus PK parameter estimates. The estimates of population level PK parameters were Cl = 24.9 L/h [23.5, 26.3] and V = 6310 L [5461, 7159]. There was no appreciable difference in parameters estimates with vs. without last-dose time incorporated in the data. We also investigated the effects of absorption rate constants that are often fixed at a published value in tacrolimus population PK analysis. Our sensitivity analysis revealed little difference between parameters estimated assuming a range of absorption rate constants.

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Development of a System for Postmarketing Population Pharmacokinetic and Pharmacodynamic Studies Using Real‐World Data From Electronic Health Records

Cited by 26 publications

References 23 publications

DrugWAS: Drug‐wide Association Studies for COVID‐19 Drug Repurposing

DrugWAS: Drug‐wide Association Studies for COVID‐19 Drug Repurposing

DrugWAS: Leveraging drug-wide association studies to facilitate drug repurposing for COVID-19

Sensitivity of Estimated Tacrolimus Population Pharmacokinetic Profile to Inaccurate Assumptions about Dose Timing and Absorption: An Investigation in Real-World and Simulated Data

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