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McCann S, Helfer VE, Balevic SJ, Hornik CD, Goldstein SL, Autmizguine J, Meyer M, Al-Uzri A, Anderson SG, Payne EH, Turdalieva S, Gonzalez D. Using Real-World Data to Externally Evaluate Population Pharmacokinetic Models of Dexmedetomidine in Children and Infants. J Clin Pharmacol 2024; 64:963-974. [PMID: 38545761 PMCID: PMC11286355 DOI: 10.1002/jcph.2434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 03/04/2024] [Indexed: 07/30/2024]
Abstract
Dexmedetomidine is a sedative used in both adults and off-label in children with considerable reported pharmacokinetic (PK) interindividual variability affecting drug exposure across populations. Several published models describe the population PKs of dexmedetomidine in neonates, infants, children, and adolescents, though very few have been externally evaluated. A prospective PK dataset of dexmedetomidine plasma concentrations in children and young adults aged 0.01-19.9 years was collected as part of a multicenter opportunistic PK study. A PubMed search of studies reporting dexmedetomidine PK identified five population PK models developed with data from demographically similar children that were selected for external validation. A total of 168 plasma concentrations from 102 children were compared with both population (PRED) and individualized (IPRED) predicted values from each of the five published models by quantitative and visual analyses using NONMEM (v7.3) and R (v4.1.3). Mean percent prediction errors from observed values ranged from -1% to 120% for PRED, and -24% to 60% for IPRED. The model by James et al, which was developed using similar "real-world" data, nearly met the generalizability criteria from IPRED predictions. Other models developed using clinical trial data may have been limited by inclusion/exclusion criteria and a less racially diverse population than this study's opportunistic dataset. The James model may represent a useful, but limited tool for model-informed dosing of hospitalized children.
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Affiliation(s)
- Sean McCann
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The Universiy of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Victória E. Helfer
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The Universiy of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Stephen J. Balevic
- Department of Pediatrics, Duke University Medical Center, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | - Chi D. Hornik
- Department of Pediatrics, Duke University Medical Center, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | | | - Julie Autmizguine
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada
| | - Marisa Meyer
- Critical Care Medicine, Nemours Children’s Hospital, Delaware, Wilmington, DE, USA
| | - Amira Al-Uzri
- Oregon Health and Science University, Portland, OR, USA
| | | | | | | | - Daniel Gonzalez
- Duke Clinical Research Institute, Durham, NC, USA
- Division of Clinical Pharmacology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
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Thompson EJ, Foote HP, Hill KD, Hornik CP. A point-of-care pharmacokinetic/pharmacodynamic trial in critically ill children: Study design and feasibility. Contemp Clin Trials Commun 2023; 35:101182. [PMID: 37485397 PMCID: PMC10362170 DOI: 10.1016/j.conctc.2023.101182] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 06/01/2023] [Accepted: 07/02/2023] [Indexed: 07/25/2023] Open
Abstract
Background High-quality, efficient, pharmacokinetic (PK), pharmacodynamic (PD), and safety studies in children are needed. Point-of-care trials in adults have facilitated clinical trial participation for patients and providers, minimized the disruption of clinical workflow, and capitalized on routine data collection. The feasibility and value of point-of-care trials to study PK/PD in children are unknown, but appear promising. The Opportunistic PK/PD Trial in Critically Ill Children with Heart Disease (OPTIC) is a programmatic point-of-care approach to PK/PD trials in critically ill children that seeks to overcome barriers of traditional pediatric PK/PD studies to generate safety, efficacy, PK, and PD data across multiple medications, ages, and disease processes. Methods This prospective, open-label, non-randomized point-of-care trial will characterize the PK/PD and safety of multiple drugs given per routine care to critically ill children with heart disease using opportunistic and scavenged biospecimen samples and data collected from the electronic health record. OPTIC has one informed consent form with drug-specific appendices, streamlining study structure and institutional review board approval. OPTIC capitalizes on routine data collection through multiple data sources that automatically capture demographics, medications, laboratory values, vital signs, flowsheets, and other clinical data. This innovative automatic data collection minimizes the burden of data collection and facilitates trial conduct. Data will be validated across sources to ensure accuracy of dataset variables. Discussion OPTIC's point-of-care trial design and automated data acquisition via the electronic health record may provide a mechanism for conducting minimal risk, minimal burden, high efficiency trials and support drug development in historically understudied patient populations. Trial registration clinicaltrials.gov number: NCT05055830. Registered on September 24, 2021.
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Affiliation(s)
| | - Henry P. Foote
- Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA
| | - Kevin D. Hill
- Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | - Christoph P. Hornik
- Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
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Shannon ML, Muhammad A, James NT, Williams ML, Breeyear J, Edwards T, Mosley JD, Choi L, Kannankeril P, Van Driest S. Variant-based heritability assessment of dexmedetomidine and fentanyl clearance in pediatric patients. Clin Transl Sci 2023; 16:1628-1638. [PMID: 37353859 PMCID: PMC10499425 DOI: 10.1111/cts.13574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/12/2023] [Accepted: 06/01/2023] [Indexed: 06/25/2023] Open
Abstract
Despite complex pathways of drug disposition, clinical pharmacogenetic predictors currently rely on only a few high effect variants. Quantification of the polygenic contribution to variability in drug disposition is necessary to prioritize target drugs for pharmacogenomic approaches and guide analytic methods. Dexmedetomidine and fentanyl, often used in postoperative care of pediatric patients, have high rates of inter-individual variability in dosing requirements. Analyzing previously generated population pharmacokinetic parameters, we used Bayesian hierarchical mixed modeling to measure narrow-sense (additive) heritability (h SNP 2 ) of dexmedetomidine and fentanyl clearance in children and identify relative contributions of small, moderate, and large effect-size variants toh SNP 2 . We used genome-wide association studies (GWAS) to identify variants contributing to variation in dexmedetomidine and fentanyl clearance, followed by functional analyses to identify associated pathways. For dexmedetomidine, median clearance was 33.0 L/h (interquartile range [IQR] 23.8-47.9 L/h) andh SNP 2 was estimated to be 0.35 (90% credible interval 0.00-0.90), with 45% ofh SNP 2 attributed to large-, 32% to moderate-, and 23% to small-effect variants. The fentanyl cohort had median clearance of 8.2 L/h (IQR 4.7-16.7 L/h), with estimatedh SNP 2 of 0.30 (90% credible interval 0.00-0.84). Large-effect variants accounted for 30% ofh SNP 2 , whereas moderate- and small-effect variants accounted for 37% and 33%, respectively. As expected, given small sample sizes, no individual variants or pathways were significantly associated with dexmedetomidine or fentanyl clearance by GWAS. We conclude that clearance of both drugs is highly polygenic, motivating the future use of polygenic risk scores to guide appropriate dosing of dexmedetomidine and fentanyl.
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Affiliation(s)
| | - Ayesha Muhammad
- School of MedicineVanderbilt UniversityNashvilleTennesseeUSA
| | - Nathan T. James
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
- Present address:
Berry Consultants, LLCAustinTexasUSA
| | - Michael L. Williams
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
- Present address:
Department of Clinical Pharmacology and Quantitative PharmacologyAstraZenecaGothenburgSweden
| | - Joseph Breeyear
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Todd Edwards
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Jonathan D. Mosley
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Biomedical InformaticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Leena Choi
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Prince Kannankeril
- Center for Pediatric Precision Medicine, Department of PediatricsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Sara Van Driest
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
- Center for Pediatric Precision Medicine, Department of PediatricsVanderbilt University Medical CenterNashvilleTennesseeUSA
- Present address:
All of Us Research ProgramNational Institutes of HealthWashingtonDCUSA
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Ding Y, Liu A, Wang Y, Zhao S, Huang S, Zhu H, Ma L, Han L, Shu S, Zheng L, Chen X. Genetic polymorphisms are associated with individual susceptibility to dexmedetomidine. Front Genet 2023; 14:1187415. [PMID: 37693312 PMCID: PMC10483403 DOI: 10.3389/fgene.2023.1187415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 08/09/2023] [Indexed: 09/12/2023] Open
Abstract
Introduction: Dexmedetomidine (DXM) is widely used as an adjuvant to anesthesia or a sedative medicine, and differences in individual sensitivity to the drug exist. This study aimed to investigate the effect of genetic polymorphisms on these differences. Methods: A total of 112 patients undergoing hand surgery were recruited. DXM 0.5 μg/kg was administered within 10 min and then continuously injected (0.4 μg/kg/h). Narcotrend index, effective dose and onset time of sedation, MAP, and HR were measured. Forty-five single nucleotide polymorphisms (SNPs) were selected for genotype. Results: We observed individual differences in the sedation and hemodynamics induced by DXM. ABCG2 rs2231142, CYP2D6 rs16947, WBP2NL rs5758550, KATP rs141294036, KCNMB1 rs11739136, KCNMA1 rs16934182, ABCC9 rs11046209, ADRA2A rs1800544, and ADRB2 rs1042713 were shown to cause statistically significant (p < 0.05) influence on the individual variation of DXM on sedation and hemodynamics. Moreover, the multiple linear regression analysis indicated sex, BMI, and ADRA2A rs1800544 are statistically related to the effective dose of DXM sedation. Discussion: The evidence suggests that the nine SNPs involved in transport proteins, metabolic enzymes, and target proteins of DXM could explain the individual variability in the sedative and hemodynamic effects of DXM. Therefore, with SNP genotyping, these results could guide personalized medication and promote clinical and surgical management.
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Affiliation(s)
- Yuanyuan Ding
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Aiqing Liu
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yafeng Wang
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shuai Zhao
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shiqian Huang
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongyu Zhu
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lulin Ma
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Linlin Han
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shaofang Shu
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lidong Zheng
- Department of Anesthesiology, Lu’an Hospital Affiliated to Anhui Medical University, Lu’an, China
| | - Xiangdong Chen
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Abstract
Precision medicine is a developing strategy for individualized treatment of a wide range of diseases. Congenital heart disease is the most common of all congenital defects and carries a high degree of variability in outcomes because of unidentified causes. Advances have identified individual genetic and environmental factors that have helped understand variations in morbidity and mortality in pediatric cardiology. A focus on genomics and pharmacogenetics has also been key to risk prediction and improvement in drug safety and efficacy in the pediatric population. With the rapidly evolving understanding of these individual factors, there also come challenges in implementation of personalized medicine into our health care model. This review outlines the key features of precision medicine in pediatric cardiology and highlights the clinical effects of these findings in patients with congenital heart disease. [Pediatr Ann. 2022;51(10):e390-e395.].
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