Browsing by Author "Trembath, Andrea"

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    Opportunistic dried blood spot sampling validates and optimizes a pediatric population pharmacokinetic model of metronidazole
    (American Society for Microbiology, 2024) Randell, Rachel L.; Balevic, Stephen J.; Greenberg, Rachel G.; Cohen-Wolkowiez, Michael; Thompson, Elizabeth J.; Venkatachalam, Saranya; Smith, Michael J.; Bendel, Catherine; Bliss, Joseph M.; Chaaban, Hala; Chhabra, Rakesh; Dammann, Christiane E. L.; Downey, L. Corbin; Hornik, Chi; Hussain, Naveed; Laughon, Matthew M.; Lavery, Adrian; Moya, Fernando; Saxonhouse, Matthew; Sokol, Gregory M.; Trembath, Andrea; Weitkamp, Joern-Hendrik; Hornik, Christoph P.; Best Pharmaceuticals for Children Act – Pediatric Trials Network Steering Committee; Pediatrics, School of Medicine
    Pharmacokinetic models rarely undergo external validation in vulnerable populations such as critically ill infants, thereby limiting the accuracy, efficacy, and safety of model-informed dosing in real-world settings. Here, we describe an opportunistic approach using dried blood spots (DBS) to evaluate a population pharmacokinetic model of metronidazole in critically ill preterm infants of gestational age (GA) ≤31 weeks from the Metronidazole Pharmacokinetics in Premature Infants (PTN_METRO, NCT01222585) study. First, we used linear correlation to compare 42 paired DBS and plasma metronidazole concentrations from 21 preterm infants [mean (SD): post natal age 28.0 (21.7) days, GA 26.3 (2.4) weeks]. Using the resulting predictive equation, we estimated plasma metronidazole concentrations (ePlasma) from 399 DBS collected from 122 preterm and term infants [mean (SD): post natal age 16.7 (15.8) days, GA 31.4 (5.1) weeks] from the Antibiotic Safety in Infants with Complicated Intra-Abdominal Infections (SCAMP, NCT01994993) trial. When evaluating the PTN_METRO model using ePlasma from the SCAMP trial, we found that the model generally predicted ePlasma well in preterm infants with GA ≤31 weeks. When including ePlasma from term and preterm infants with GA >31 weeks, the model was optimized using a sigmoidal Emax maturation function of postmenstrual age on clearance and estimated the exponent of weight on volume of distribution. The optimized model supports existing dosing guidelines and adds new data to support a 6-hour dosing interval for infants with postmenstrual age >40 weeks. Using an opportunistic DBS to externally validate and optimize a metronidazole population pharmacokinetic model was feasible and useful in this vulnerable population.
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    Rapid Whole-Genomic Sequencing and a Targeted Neonatal Gene Panel in Infants With a Suspected Genetic Disorder
    (American Medical Association, 2023) Maron, Jill L.; Kingsmore, Stephen; Gelb, Bruce D.; Vockley, Jerry; Wigby, Kristen; Bragg, Jennifer; Stroustrup, Annemarie; Poindexter, Brenda; Suhrie, Kristen; Kim, Jae H.; Diacovo, Thomas; Powell, Cynthia M.; Trembath, Andrea; Guidugli, Lucia; Ellsworth, Katarzyna A.; Reed, Dallas; Kurfiss, Anne; Breeze, Janis L.; Trinquart, Ludovic; Davis, Jonathan M.; Pediatrics, School of Medicine
    Importance: Genomic testing in infancy guides medical decisions and can improve health outcomes. However, it is unclear whether genomic sequencing or a targeted neonatal gene-sequencing test provides comparable molecular diagnostic yields and times to return of results. Objective: To compare outcomes of genomic sequencing with those of a targeted neonatal gene-sequencing test. Design, setting, and participants: The Genomic Medicine for Ill Neonates and Infants (GEMINI) study was a prospective, comparative, multicenter study of 400 hospitalized infants younger than 1 year of age (proband) and their parents, when available, suspected of having a genetic disorder. The study was conducted at 6 US hospitals from June 2019 to November 2021. Exposure: Enrolled participants underwent simultaneous testing with genomic sequencing and a targeted neonatal gene-sequencing test. Each laboratory performed an independent interpretation of variants guided by knowledge of the patient's phenotype and returned results to the clinical care team. Change in clinical management, therapies offered, and redirection of care was provided to families based on genetic findings from either platform. Main outcomes and measures: Primary end points were molecular diagnostic yield (participants with ≥1 pathogenic variant or variant of unknown significance), time to return of results, and clinical utility (changes in patient care). Results: A molecular diagnostic variant was identified in 51% of participants (n = 204; 297 variants identified with 134 being novel). Molecular diagnostic yield of genomic sequencing was 49% (95% CI, 44%-54%) vs 27% (95% CI, 23%-32%) with the targeted gene-sequencing test. Genomic sequencing did not report 19 variants found by the targeted neonatal gene-sequencing test; the targeted gene-sequencing test did not report 164 variants identified by genomic sequencing as diagnostic. Variants unidentified by the targeted genomic-sequencing test included structural variants longer than 1 kilobase (25.1%) and genes excluded from the test (24.6%) (McNemar odds ratio, 8.6 [95% CI, 5.4-14.7]). Variant interpretation by laboratories differed by 43%. Median time to return of results was 6.1 days for genomic sequencing and 4.2 days for the targeted genomic-sequencing test; for urgent cases (n = 107) the time was 3.3 days for genomic sequencing and 4.0 days for the targeted gene-sequencing test. Changes in clinical care affected 19% of participants, and 76% of clinicians viewed genomic testing as useful or very useful in clinical decision-making, irrespective of a diagnosis. Conclusions and relevance: The molecular diagnostic yield for genomic sequencing was higher than a targeted neonatal gene-sequencing test, but the time to return of routine results was slower. Interlaboratory variant interpretation contributes to differences in molecular diagnostic yield and may have important consequences for clinical management.