Physiologically-Based Pharmacokinetic Modeling to Investigate the Effect of Maturation on Buprenorphine Pharmacokinetics in Newborns with Neonatal Opioid Withdrawal Syndrome.

Neonatal opioid withdrawal syndrome (NOWS) is a major public health concern whose incidence has paralleled the opioid epidemic in the United States. Sublingual buprenorphine is an emerging treatment for NOWS, but given concerns about long-term adverse effects of perinatal opioid exposure, precision dosing of buprenorphine is needed. Buprenorphine pharmacokinetics (PK) in newborns, however, is highly variable. To evaluate underlying sources of PK variability, a neonatal physiologically-based pharmacokinetic (PBPK) model of sublingual buprenorphine was developed using Simcyp (version 19.1). The PBPK model included metabolism by cytochrome P450 (CYP) 3A4, CYP2C8, UDP-glucuronosyltransferase (UGT) 1A1, UGT1A3, UGT2B7, and UGT2B17, with additional biliary excretion. Maturation of metabolizing enzymes was incorporated, and default CYP2C8 and UGT2B7 ontogeny profiles were updated according to recent literature. A biliary clearance developmental profile was outlined using clinical data from neonates receiving sublingual buprenorphine as NOWS treatment. Extensive PBPK model validation in adults demonstrated good predictability, with geometric mean (95% confidence interval (CI)) predicted/observed ratios (P/O ratios) of area under the curve from zero to infinity (AUC0-∞ ), peak concentration (Cmax ), and time to reach peak concentration (Tmax ) equaling 1.00 (0.74-1.33), 1.04 (0.84-1.29), and 0.95 (0.72-1.26), respectively. In neonates, the geometric mean (95% CI) P/O ratio of whole blood concentrations was 0.75 (95% CI 0.64-0.87). PBPK modeling and simulation demonstrated that variability in biliary clearance, sublingual absorption, and CYP3A4 abundance are likely important drivers of buprenorphine PK variability in neonates. The PBPK model could be used to guide development of improved buprenorphine starting dose regimens for the treatment of NOWS.

Physiologic Indirect Response Modeling to Describe Buprenorphine Pharmacodynamics in Newborns Treated for Neonatal Opioid Withdrawal Syndrome.

BACKGROUND AND OBJECTIVE: Buprenorphine has been shown to be effective in treating infants with neonatal opioid withdrawal syndrome. However, an evidence-based buprenorphine dosing strategy has not been established in the treatment of neonatal opioid withdrawal syndrome because of a lack of exposure-response data. The aim of this study was to develop an integrated pharmacokinetic and pharmacodynamic model to predict buprenorphine treatment outcomes in newborns with neonatal opioid withdrawal syndrome. METHODS: Clinical data were obtained from 19 newborns with a median (range) gestational age of 37 (34-41) weeks enrolled in a pilot pharmacokinetic study of buprenorphine. Sparse blood sampling, comprising three specimens obtained around the second dose of buprenorphine, was performed using heel sticks with dried blood spot technology. Standardized neonatal opioid withdrawal syndrome severity scores (Finnegan scores) were collected every 3-4 h based on symptoms by bedside nursing staff. Mean Finnegan scores were used as a pharmacodynamic marker in the exposure-response modeling. The blood concentration-Finnegan score relationship was described using a physiologic indirect response model with inclusion of natural disease remission. RESULTS: A total of 52 buprenorphine blood concentrations and 780 mean Finnegan scores were available for the pharmacokinetic/pharmacodynamic modeling and exposure-response analysis. A one-compartment model with first-order absorption adequately described the pharmacokinetic data. The buprenorphine blood concentration at 50% of maximum effect for the inhibition of disease progression was 0.77 ng/mL (95% confidence interval 0.32-1.2). The inclusion of natural disease remission described as a function of postnatal age significantly improved the model fit. CONCLUSIONS: A buprenorphine pharmacokinetic/pharmacodynamic model was successfully developed. The model could facilitate model-informed optimization of the buprenorphine dosing regimen in the treatment of neonatal opioid withdrawal syndrome.

Suggestions for Model-Informed Precision Dosing to Optimize Neonatal Drug Therapy.

Evidence for dosing, efficacy, and safety of most medications used to treat neonates is sparse. Thus, dosing is usually derived by extrapolation from adult and pediatric pharmacologic data with scaling by body weight or body surface area. This may lead to drug dosing that is unsafe or ineffective. However, new strategies are being developed and studied to dose medications in critically ill neonates. Mass spectroscopy technology capable of quickly analyzing drug levels is readily available. Software that integrates population pharmacokinetics and pharmacodynamics with data from sparse samples from neonates allows for timely adjustments of dosing to achieve the desired effect while minimizing adverse outcomes. Some genetic polymorphisms that affect drug response in neonates have also been reported. This review highlights aspects of drug response and how it is impacted by prematurity, assesses pharmacogenomic studies in neonates, and offers suggestions for innovative pharmacokinetic/pharmacodynamic model-based approaches that combine population- or physiology-based pharmacology data, Bayesian analysis, and electronic decision support tools for precision dosing in neonates while illustrating examples where this approach can be used to optimize medical therapy in neonates. Barriers to implementing precision dosing in neonates and how to overcome them are also discussed.

Intensive insulin therapy in brain injury: a meta-analysis.

Many studies have addressed the question of whether intensive insulin therapy (IIT) provides better outcomes for brain-injured patients than does conventional insulin therapy (CIT), with conflicting results. We performed a systematic review and meta-analysis of the literature to estimate the effect of IIT on patients with brain injury. We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), and citations of key articles and selected "all randomized controlled trials" (RCTs) comparing the effect of IIT to CIT among adult patients with acute brain injury (traumatic brain injury, stroke, subarachnoid hemorrhage, and encephalitis). Of the 2807 studies, we identified 9 RCTs with a total of 1160 patients for analysis. IIT did not appear to decrease the risk of in-hospital or late mortality (RR=1.04, 95% CI=0.75, 1.43 and RR=1.07, 95%CI=0.91, 1.27 respectively). No significant heterogeneity was found (I(2)=0.0%). IIT also did not have a protective effect on long-term neurological outcomes (LTNO) (RR=1.10, 95% CI=0.96, 1.27). IIT, however, did decrease the rate of infections (RR=0.76, 95% CI=0.58, 0.98). Heterogeneity was present (I(2)=64%), which was eliminated upon sensitivity analysis bringing the RR to 0.66 (95% CI=0.55, 0.80, I(2)=0%). IIT increased the rate of hypoglycemic episodes (RR=1.72, 95% CI=1.20, 2.46) however there was intractable heterogeneity present (I(2)=89%), which did not resolve upon sensitivity analysis. We found no evidence of publication bias by Egger's test (p=0.50). To conclude, IIT has no mortality or LTNO benefit to patients with brain injury, but is beneficial at decreasing infection rates.