Lawrence C. Ku

Dosing in neonates: special considerations in physiology and trial design

Determining the right dose for drugs used to treat neonates is critically important. Neonates have significant differences in physiology affecting drug absorption, distribution, metabolism, and elimination that make extrapolating dosages from adults and older children inappropriate. In spite of recent legislative efforts requiring drug studies in this population, most drugs given to neonates remain insufficiently studied. Many ethical and logistical concerns make designing studies in this age group difficult. Fortunately, specialized analytical techniques, such as the use of dried blood spots, scavenged sampling, population pharmacokinetics analyses, and sparse sampling, have helped investigators better define doses that maximize efficacy and safety. Through the use of these methods, successful clinical trials have resulted in recent changes to drug dosing in this population.

Bacterial Meningitis in Infants

Neonatal bacterial meningitis is uncommon but devastating. Morbidity among survivors remains high. The types and distribution of pathogens are related to gestational age, postnatal age, and geographic region. Confirming the diagnosis is difficult. Clinical signs are often subtle, lumbar punctures are frequently deferred, and cerebrospinal fluid (CSF) cultures can be compromised by prior antibiotic exposure. Infants with bacterial meningitis can have negative blood cultures and normal CSF parameters. Promising tests such as the polymerase chain reaction require further study. Prompt treatment with antibiotics is essential. Clinical trials investigating a vaccine for preventing neonatal Group B Streptococcus infections are ongoing.

Sedatives and Analgesics Given to Infants in Neonatal Intensive Care Units at the End of Life

OBJECTIVE To describe the administration of sedatives and analgesics at the end of life in a large cohort of infants in North American neonatal intensive care units. STUDY DESIGN Data on mortality and sedative and analgesic administration were from infants who died from 1997-2012 in 348 neonatal intensive care units managed by the Pediatrix Medical Group. Sedatives and analgesics of interest included opioids (fentanyl, methadone, morphine), benzodiazepines (clonazepam, diazepam, lorazepam, midazolam), central alpha-2 agonists (clonidine, dexmedetomidine), ketamine, and pentobarbital. We used multivariable logistic regression to evaluate the association between administration of these drugs on the day of death and infant demographics and illness severity. RESULTS We identified 19 726 infants who died. Of these, 6188 (31%) received a sedative or analgesic on the day of death; opioids were most frequently administered, 5366/19 726 (27%). Administration of opioids and benzodiazepines increased during the study period, from 16/283 (6%) for both in 1997 to 523/1465 (36%) and 295/1465 (20%) in 2012, respectively. Increasing gestational age, increasing postnatal age, invasive procedure within 2 days of death, more recent year of death, mechanical ventilation, inotropic support, and antibiotics on the day of death were associated with exposure to sedatives or analgesics. CONCLUSIONS Administration of sedatives and analgesics increased over time. Infants of older gestational age and those more critically ill were more likely to receive these drugs on the day of death. These findings suggest that drug administration may be driven by severity of illness.

Therapeutic Index Estimation of Antiepileptic Drugs: A Systematic Literature Review Approach.

ObjectivesOur study aimed to determine whether data obtained from the medical literature can be used to estimate the therapeutic index of 5 antiepileptic drugs (AEDs): carbamazepine, lamotrigine, phenobarbital, phenytoin, and valproate. MethodsWe performed a literature search using PubMed and EMBASE to collect published safety, efficacy, and therapeutic monitoring data for 5 AEDs and extracted all relevant information into a drug- and study-specific drug database. For each AED, we summarized (1) type, severity, and incidence of toxicity-related adverse events and toxicity-associated range of drug doses or concentrations; (2) effective versus toxic concentration and dose (therapeutic range); and (3) therapeutic drug monitoring practices. We defined therapeutic index as the ratio of the minimum toxic concentration to the minimum effective concentration. ResultsWe reviewed a total of 810 full-text articles and extracted data from 163. The literature suggests that the therapeutic index of phenytoin is 2. The therapeutic indices of phenobarbital and valproate exceed 2. There were insufficient data to precisely quantify the therapeutic indices of carbamazepine and lamotrigine. ConclusionsFor some drugs, this approach offers a low-cost method of therapeutic index estimation. Our results can serve as preliminary data for future trials and as guidance for US Food and Drug Administration decision making regarding narrow therapeutic index classification.

Use of Population Pharmacokinetics and Electronic Health Records to Assess Piperacillin–Tazobactam Safety in Infants

Background: Piperacillin, in combination with tazobactam, is frequently used in infants for treating nosocomial infections, although safety data in this population are limited. Electronic health record (EHR) data can be used to evaluate drug safety in infants, but measures of drug exposure are lacking. Methods: To relate simulated piperacillin exposure with adverse events (AEs) in infants using EHR data, we identified infants discharged from 333 neonatal intensive care units managed by the Pediatrix Medical Group between 1997 and 2012. Using a previously published population pharmacokinetic model in the target population, we simulated piperacillin steady state area under the concentration versus time curve from zero to &tgr; (AUCss,0-&tgr;) and steady state maximal drug concentration (Cmaxss). Next, we used multivariable logistic regression to evaluate the association between simulated AUCss,0-&tgr; and Cmaxss with clinical AEs (seizure and rash) and laboratory AEs controlling for gestational age. The odds ratios (95% confidence intervals) comparing the third versus the first tertiles for AUCss,0-&tgr; and Cmaxss were reported. Results: We identified 746 infants with a median (interquartile range) gestational age of 30 weeks (26–33) and postnatal age of 11 days (6–25). The median (interquartile range) piperacillin dose was 225 mg/kg/d (176–300). No significant associations were found between simulated piperacillin exposure (AUCss,0-&tgr; and Cmaxss) and clinical and laboratory AEs. Conclusions: We found no associations between predicted piperacillin exposures and the occurrence of AEs. This study confirms the feasibility of using population pharmacokinetics and EHR to relate drug exposure with safety.

Risk factors for group B streptococcal disease in neonates of mothers with negative antenatal testing

Objective:The aim of this study was to identify risk factors for early-onset group B Streptococcus (EOGBS) disease in neonates of mothers with negative antenatal screening.Study Design:We performed a retrospective cohort study of neonates born to mothers with negative antenatal GBS screening between 2002 and 2012. Our primary outcome was EOGBS infection. We used multivariable logistic regression to assess factors associated with EOGBS.Results:EOGBS was confirmed in 492 of the 179 818 neonates that met the study inclusion criteria. Risk factors for EOGBS included black race (reference: white, odds ratio (OR) =1.81 (95% confidence interval: 1.43, 2.31)), maternal age <18 years (reference: >35 years, OR=2.63 (1.54, 4.51)) and maternal age 18 to 35 years (reference: >35 years, OR=1.94 (1.30, 2.88)).Conclusion:Maternal age <18 years and black race were the strongest predictors of EOGBS. Further research investigating contributors to the discordance between screening results and neonatal outcomes in these populations is needed.

Therapeutic drug monitoring, electronic health records, and pharmacokinetic modeling to evaluate sirolimus drug exposure-response relationships in renal transplant patients.

Background: Sirolimus, an immunosuppressive agent used in renal transplantation, can prevent allograft rejection. Identification of the therapeutic index (the ratio of minimum toxic concentration to minimum therapeutic concentration) for immunosuppresants is necessary to optimize the care of patients and set standards for bioequivalence evaluation of sirolimus products. However, the therapeutic index for sirolimus has been inconsistently defined, potentially because of inconsistencies in sirolimus exposure–response relationships. Methods: The authors used retrospective therapeutic drug monitoring data from the electronic health records of patients treated in a tertiary health care system from 2008 to 2014 to (1) develop a population pharmacokinetic (PK) model, (2) use the model to simulate sirolimus concentrations, and (3) characterize the exposure–response relationship. Using Wilcoxon rank-sum and Fisher exact tests, the authors determined relationships between sirolimus exposure and adverse events (AEs) (anemia, leukopenia, thrombocytopenia, hyperlipidemia, and decline in renal function) and the composite efficacy end point of graft loss or rejection. Results: The developed 2-compartment population PK model showed appropriate goodness of fit. In a late-phase (>12 months), postrenal transplant population of 27 inpatients, the authors identified statistically significant relationships between 83 simulated peak and trough sirolimus concentrations and outcomes: graft loss or rejection (P = 0.018) and decline in renal function (P = 0.006), respectively. Conclusions: Use of therapeutic drug monitoring results and PK modeling permitted correlation of sirolimus concentrations with graft loss or rejection and decline in renal function. However, the method was limited in its assessment of other AEs. To better evaluate sirolimus exposure–response relationships, the method should be applied to a larger sample of newly transplanted patients with a higher propensity toward AEs or efficacy failure.

Population Pharmacokinetics and Exploratory Exposure-Response Relationships of Diazepam in Children Treated for Status Epilepticus

Diazepam is labeled for status epilepticus (SE) in children, but there are limited data characterizing its disposition in pediatric patients. We developed a population pharmacokinetic (PK) model of i.v. diazepam in children with SE. We evaluated relationships between PK parameters and both safety and efficacy, and simulated exposures using dosing regimens from the product label and clinical practice. The model was developed using prospective data from a pediatric clinical trial comparing diazepam to lorazepam for treatment of SE. Altogether, 87 patients aged ≥ 3 months to < 18 years contributed 162 diazepam concentrations. Diazepam PKs were well characterized by a two‐compartment model scaled by body size. No significant or clinically important relationships were observed between diazepam PKs and safety or efficacy. Simulations demonstrated that, compared with label dosing, the study dose (0.2 mg/kg i.v., maximum 8 mg) resulted in greater frequency in rapidly achieving the target therapeutic range of 200–600 ng/mL.

Use of Therapeutic Drug Monitoring, Electronic Health Record Data, and Pharmacokinetic Modeling to Determine the Therapeutic Index of Phenytoin and Lamotrigine.

Background: Defining a drugs therapeutic index (TI) is important for patient safety and regulating the development of generic drugs. For many drugs, the TI is unknown. A systematic approach was developed to characterize the TI of a drug using therapeutic drug monitoring and electronic health record (EHR) data with pharmacokinetic (PK) modeling. This approach was first tested on phenytoin, which has a known TI, and then applied to lamotrigine, which lacks a defined TI. Methods: Retrospective EHR data from patients in a tertiary hospital were used to develop phenytoin and lamotrigine population PK models and to identify adverse events (anemia, thrombocytopenia, and leukopenia) and efficacy outcomes (seizure-free). Phenytoin and lamotrigine concentrations were simulated for each day with an adverse event or seizure. Relationships between simulated concentrations and adverse events and efficacy outcomes were used to calculate the TI for phenytoin and lamotrigine. Results: For phenytoin, 93 patients with 270 total and 174 free concentrations were identified. A de novo 1-compartment PK model with Michaelis-Menten kinetics described the data well. Simulated average total and free concentrations of 10–15 and 1.0–1.5 mcg/mL were associated with both adverse events and efficacy in 50% of patients, resulting in a TI of 0.7–1.5. For lamotrigine, 45 patients with 53 concentrations were identified. A published 1-compartment model was adapted to characterize the PK data. No relationships between simulated lamotrigine concentrations and safety or efficacy endpoints were seen; therefore, the TI could not be calculated. Conclusions: This approach correctly determined the TI of phenytoin but was unable to determine the TI of lamotrigine due to a limited sample size. The use of therapeutic drug monitoring and EHR data to aid in narrow TI drug classification is promising, but it requires an adequate sample size and accurate characterization of concentration–response relationships.

An adolescent on peritoneal dialysis with acute encephalopathy: Answers

Total parenteral nutrition (TPN) was started on hospital day 7 as the patient was still intubated and stuporous. Prior to initiation of TPN, serum thiamine and cobalamin levels were obtained given the patient’s history of malnutrition and chronic peritoneal dialysis (PD). On hospital day 11, the patient began to improve. She was extubated, able to respond to basic questions but remained withdrawn and taciturn and not back to baseline. A repeat echocardiogram showed resolution of abnormal left ventricular function. TPN was discontinued as the patient began to tolerate small amounts of food. The patient was then transferred back to the Nephrology service for further care. On the Nephrology service, she continued to act withdrawn and minimally responsive. On hospital day 15, results for serum thiamine levels came back as 28 nMol/l (reference range 70 – 180 nMol/l). Cobalamin levels were within normal limits. She was given a 25 mg bolus of intravenous (IV) thiamine. Within several hours after this bolus, the patient showed a dramatic improvement in her neurological status. She became more responsive and was able to sit up on a chair at the bedside, order a meal on her own from the hospital menu and text her mother. She was later seen to be ambulating with assistance and interacting with her family members. Thiamine was continued at a dose of 50 mg IV for 1 week, and then continued orally at the same dose. Repeat measurements of the thiamine level obtained after 4 days of thiamine replacement therapy was shown to be >2,000 mMol/l. The patient required physical and occupational therapy services for deconditioning. On hospital day 29, she was discharged home in a much improved condition. Since then the patient has been doing well with no permanent neurological deficit.