Population pharmacokinetics of molnupiravir in adults with COVID-19: Lack of clinically important exposure variation across individuals.

Effective antiviral treatments for coronavirus disease 2019 (COVID-19) are needed to reduce the morbidity and mortality associated with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection, particularly in patients with risk factors for severe disease. Molnupiravir (MK-4482, EIDD-2801) is an orally administered, ribonucleoside prodrug of ß-D-N4-hydroxycytidine (NHC) with submicromolar potency against SARS-CoV-2. A population pharmacokinetic (PopPK) analysis for molnupiravir exposure was conducted using 4202 NHC plasma concentrations collected in 1207 individuals from a phase I trial in healthy participants, a phase IIa trial in non-hospitalized participants with COVID-19, a phase II trial in hospitalized participants with COVID-19, and a phase II/III trial in non-hospitalized participants with COVID-19. Molnupiravir pharmacokinetics (PK) was best described by a two-compartment model with a transit-compartment absorption model and linear elimination. Molnupiravir apparent elimination clearance increased with body weight less-than-proportionally (power 0.412) and was estimated as 70.6 L/h in 80-kg individuals with a moderate interindividual variability (43.4% coefficient of variation). Additionally, effects of sex and body mass index on apparent central volume and food status and formulation on the absorption mean transit time were identified as statistically significant descriptors of variability in these PK parameters. However, none of the identified covariate effects caused clinically relevant changes in the area under the NHC concentration versus time curve between doses, the exposure metric most closely related to clinical response. Overall, the PopPK model indicates that molnupiravir can be administered in adults without dose adjustment based on age, sex, body size, food, and mild-to-moderate renal or mild hepatic impairment.

Evaluating performance of a decision support system to improve methotrexate pharmacotherapy in children and young adults with cancer.

The management of high-dose methotrexate (MTX) therapy in patients with cancer depends on the routine monitoring of drug exposures in conjunction with leucovorin (LV), urine pH, patient hydration, and other clinical indices of patient well-being. A key factor in patient oversight is the facilitation of MTX clearance to minimize drug-related toxicity. The aim of this investigation was to evaluate the performance of a clinical decision support system and Bayesian forecasting algorithm in the prediction of MTX concentrations and assessment of LV dosing requirements in pediatric and young adult patients with cancer based on the current practice at the Children's Hospital of Philadelphia. Fifty patients ranging in age from 8 months to 21 years (weight range, 7.6-163.3 kg) contributing 80 total dosing events (183 MTX serum concentrations) were studied. The forecasting model was able to consistently predict future MTX concentrations with the knowledge of one prior concentration and continued to improve with additional concentration data made available through daily therapeutic drug monitoring. Precision was good at 12.9% with low bias at 2.2%. Comparison between the decision support system recommendations for LV rescue relative to the actual LV administration was also made. Sixteen patients would have initiated rescue therapy earlier, seven patients would have received a larger dose (42 smaller), and LV would have been given less often for 37 patients. The forecasting algorithm in the MTX dashboard was reasonably accurate in predicting MTX concentrations and should improve further as the underlying model and prediction algorithm evolves. This decision support system can be useful in helping physicians decide if a patient is clearing MTX as expected or if more aggressive rescue therapy is warranted.

Fluconazole dosing for the prevention or treatment of invasive candidiasis in young infants.

BACKGROUND: Young infants are susceptible to developmental factors influencing the pharmacokinetics of drugs. Fluconazole is increasingly used to prevent and treat invasive candidiasis in infants. Dosing guidance remains empiric and variable because limited pharmacokinetic data exist. METHODS: Our population pharmacokinetic model derived from 357 fluconazole plasma concentrations from 55 infants (23-40 week gestation) illustrates expected changes in fluconazole clearance based upon gestational age, postnatal age, weight, and creatinine. We used a Monte Carlo simulation approach based on parametric description of a patient population's pharmacokinetic response to fluconazole to predict fluconazole exposure (median: 10th and 90th percentile population variability range) after 3, 6, and 12 mg/kg dosing. RESULTS: For the treatment of invasive candidiasis, a dose of at least 12 mg/kg/d in the first 90 days after birth is needed to achieve an area under the concentration curve (AUC) of >400 mg*h/L and an AUC/minimum inhibitory concentration (MIC) >50 for Candida species with MIC <8 microg/mL in > or =90% of <30 week gestation infants and 80% of 30 to 40 week gestation infants. The more preterm infants achieve a higher median AUC (682 mg*hr/L) compared with more mature infants (520 mg*hr/L). For early prevention of candidiasis in 23 to 29 week infants, a dose of 3 or 6 mg/kg twice weekly during the first 42 days of life is equivalent to an AUC of 50 and 100 mg*hr/L, respectively, and maintains fluconazole concentrations > or =2 or 4 microg/mL, respectively, for half of the dosing interval. For late prevention, the 6 mg/kg dose every 72 hours provides similar exposure to 3 mg/kg daily dose. Infants with serum creatinine > or =1.3 mg/dL have delayed drug clearance and dose adjustment is indicated if creatinine does not improve within 96 hours. CONCLUSIONS: A therapeutic concentration of fluconazole in premature infants with invasive candidiasis requires dosing substantially greater than commonly recommended in most reference texts. To prevent invasive candidiasis, twice weekly prophylaxis regimens can provide adequate exposure when unit specific MICs are taken into account.

Population pharmacokinetics of imatinib mesylate and its metabolite in children and young adults.

BACKGROUND: Imatinib mesylate (Gleevec) is a small molecule tyrosine kinase inhibitor approved for use in the management of chronic myeloid leukemia in adults and children and in gastrointestinal stromal tumors in adults. Population pharmacokinetic (PPK) studies evaluating the effect of population covariates on the pharmacokinetics of imatinib and its active metabolite have been developed in adults with chronic myeloid leukemia (CML) and gastrointestinal stromal tumor (GIST). However, this still remains to be described in children. PURPOSE: The objectives of the analysis were to develop a PPK model of imatinib and its active metabolite, CGP74588, to describe exposure in children and young adults and to identify covariates that are predictors of variability in disposition. METHODS: Plasma concentrations from 26 subjects with Philadelphia (Ph+) leukemia (Phase I study) and 15 subjects with refractory solid tumors (Phase II study), who received oral imatinib at doses ranging from 260 to 570 mg/m(2), were available for the PPK analysis in NONMEM. Blood samples were drawn prior to dosing and over 24-48 h on days 1 and 8 of the studies. Covariates studied included weight, age, albumin, alanine aminotransferase and the study population. RESULTS: The pharmacokinetics of imatinib and CGP 74588 were well described by one and two compartment models, respectively. Total body weight was the only covariate found to significantly affect Cl/F and V/F. The final imatinib-CGP 74588 model is summarized as follows: CL/F (imatinib) (L/h) = 10.8 x (WT/70)(0.75), V/F (imatinib) (L) = 284 x (WT/70) and D1(duration of zero order absorption,imatinib) (h) = 1.67 and CL/F (CGP 74588) (L/h) = 9.65 x (WT/70)(0.75), V1/F (CGP 74588) (L) = 11.6 x (WT/70), Q (CGP 74588) (L/h) = 2.9 x (WT/70)(0.75) and V2/F (CGP 74588) (L) = 256*(WT/70). Model evaluation indicated that the final model was robust and satisfactory. CONCLUSIONS: Current imatinib dosing guidelines in pediatrics is based on the achievement of exposures consistent with doses known to be safe and efficacious in adults. Dose adjustments in children are guided empirically by the observance of drug-related toxicities. While, the pharmacokinetics of imatinib and its active metabolite, CGP 74588 in children are consistent with prior knowledge in adults, the model will form the basis to support the design of future trials, particularly with a view to managing toxicities and exploring dosing in this population.

A SAS-based solution to evaluate study design efficiency of phase I pediatric oncology trials via discrete event simulation.

Previous exploration of oncology study design efficiency has focused on Markov processes alone (probability-based events) without consideration for time dependencies. Barriers to study completion include time delays associated with patient accrual, inevaluability (IE), time to dose limiting toxicities (DLT) and administrative and review time. Discrete event simulation (DES) can incorporate probability-based assignment of DLT and IE frequency, correlated with cohort in the case of DLT, with time-based events defined by stochastic relationships. A SAS-based solution to examine study efficiency metrics and evaluate design modifications that would improve study efficiency is presented. Virtual patients are simulated with attributes defined from prior distributions of relevant patient characteristics. Study population datasets are read into SAS macros which select patients and enroll them into a study based on the specific design criteria if the study is open to enrollment. Waiting times, arrival times and time to study events are also sampled from prior distributions; post-processing of study simulations is provided within the decision macros and compared across designs in a separate post-processing algorithm. This solution is examined via comparison of the standard 3+3 decision rule relative to the "rolling 6" design, a newly proposed enrollment strategy for the phase I pediatric oncology setting.

Shortening the timeline of pediatric phase I trials: the rolling six design.

PURPOSE: To shorten the study conduct timeline of pediatric phase I oncology trials by employing a novel trial design. METHODS: A comparison of the traditional 3 + 3 patients per cohort, phase I trial design with a novel, rolling six design was performed by using discrete event simulation. The rolling six design allows for accrual of two to six patients concurrently onto a dose level based on the number of patients currently enrolled and evaluable, the number experiencing dose-limiting toxicity (DLT), and the number still at risk of developing a DLT. Clinical trial simulations (n = 1,000) were based on historical data and were performed using SAS 9.1.3 (SAS Institute, Cary, NC). Study timelines and patient numbers were determined for each design, and safety was assessed as a function of the number of DLTs observed. RESULTS: In twelve completed historical studies, the median time to study completion was 452 days (range, 220 to 606 days); number of evaluable participants enrolled was 22 (range, 11 to 33), and DLTs occurring per study was three (range, 0 to 5). In 1,000 study simulations, in which the average time to new patient accrual was 10 days, the average +/- standard deviation (SD) time to study completion was 294 +/- 75 days for the rolling six design versus 350 +/- 84 days for the 3 + 3 design, whereas the number of DLTs per study was the same (average +/- SD, 3.3 +/- 1.1 v 3.2 +/- 1.1 for the rolling six and 3 + 3 designs, respectively). CONCLUSION: The rolling six design may significantly decrease the duration of pediatric phase I studies without increasing the risk of toxicity. The design will be tested prospectively in upcoming Children's Oncology Group phase I trials.

Key performance indicators for the assessment of pediatric pharmacotherapeutic guidance.

Given the paucity of actual guidance provided for managing pediatric drug therapy, prescribing caregivers must be able to draw on the limited published information in pediatrics and/or guidance provided in adults with some account for expected pediatric response. Guidance for managing drug therapy in children is clearly desirable. Our objectives were to construct key performance indicators (KPIs) for pediatric pharmacotherapy guidance to identify drugs where pharmacotherapy guidance would be most beneficial. A pilot survey to assess variation in caregiver appreciation for pediatric dosing guidance has also been constructed to provide a complementary subjective assessment. Three KPI categories, drug utilization (based on hospital admission and billing data collected from 2001 through 2006), medical need, and guidance outcome value along with a KPI composite score have been proposed. Low scores are favored with respect to prioritization for pharmacotherapy guidance. The pilot survey consisted of 15 questions to assess 1) physician knowledge regarding dosing guidance, 2) attitudes toward dose modification and patient individualization, 3) the accessibility, ease of use and appropriateness of existing data stores, and 4) frequency of dosing modification, consultation of dosing compendiums and estimate of success rate in dosing guidance. Pilot results suggest that dosing guidance is generally viewed as important and that the existing resources are insufficient to guide recommendations for all drugs. While the majority of respondents check more than one resource less than 25% of the time, at least 25% of the respondents check more than one resource 25-50% of the time. The majority viewed the relevance of dosing guidance very important to the management of drug therapy. The questionnaire is being extended to the primary care centers, the Kids First Network and specialty care centers. Results will guide the development of decision support systems (DSS) that provide patient-specific pharmacotherapy guidance as part of our pediatric knowledgebase initiative. For the top 25 most utilized agents at our institution over the last 6 years, KPI score ranged from 35 (dexamethasone) to 77 (cefazolin and ampicillin) with an average score of 55. Prototype DSS for tacrolimus and methotrexate are strongly supported by the KPI scoring which ranks their selection in the top 5% of drugs on formulary. KPI metrics provide an objective means of ranking agents for which pediatric pharmacotherapeutic guidance is clearly needed.

An informatics approach to assess pediatric pharmacotherapy: design and implementation of a hospital drug utilization system.

Drug utilization in the inpatient setting can provide a mechanism to assess drug prescribing trends, efficiency, and cost-effectiveness of hospital formularies and examine subpopulations for which prescribing habits may be different. Such data can be used to correlate trends with time-dependent or seasonal changes in clinical event rates or the introduction of new pharmaceuticals. It is now possible to provide a robust, dynamic analysis of drug utilization in a large pediatric inpatient setting through the creation of a Web-based hospital drug utilization system that retrieves source data from our accounting database. The production implementation provides a dynamic and historical account of drug utilization at the authors' institution. The existing application can easily be extended to accommodate a multi-institution environment. The creation of a national or even global drug utilization network would facilitate the examination of geographical and/or socioeconomic influences in drug utilization and prescribing practices in general.