Population pharmacokinetics of ciprofloxacin in newborns with early onset neonatal sepsis and suspected meningitis.

BACKGROUND: Neonatal Sepsis accounts for significant proportion of neonatal mortality globally. Ciprofloxacin can be used as an effective antimicrobial against common causative agents of neonatal sepsis. However, there is only limited information about its pharmacokinetic distribution in plasma and Cerebrospinal fluid (CSF) of neonates. METHODS: Plasma and CSF samples were taken using a sparse sampling technique from neonates who received at least one dose of intravenous ciprofloxacin. Ciprofloxacin levels were analysed using high-performance liquid chromatography (HPLC). Population pharmacokinetic analysis was conducted using a non-linear mixed-effects modelling using Pumas® (Pharmaceutical Modelling and Simulation) package (Version 2.0). RESULTS: 53 neonates were enroled in the study of whom; 9 (17%) had meningitis. The median concentration of ciprofloxacin in CSF was 1.4 (0.94-2.06) ug/ml and plasma was 2.94 (1.8-5.0) ug/ml. A one-compartment model with first-order elimination fitted the data. Body weight was found to be a significant covariate on volume of distribution (Vd). Simulations based on the final model suggest that dose of 10 mg/kg, intravenous b.d may not be able to achieve the desirable indices. CONCLUSIONS: One compartment model with weight as a covariate explained the available data. Further studies with modified sampling strategy, larger sample size and variable dose levels are needed.

Pharmacometric approach to assist dosage regimen design in neonates undergoing therapeutic hypothermia.

BACKGROUND: Therapeutic hypothermia (TH) is the treatment of choice for neonates diagnosed with perinatal asphyxia (PA). Dosing recommendations of various therapeutic agents including antimicrobials were not specifically available for the neonates undergoing TH. METHODS: A systematic search methodology was used to identify pharmacokinetic (PK) studies of antimicrobials during TH. Antimicrobials with multiple PK studies were identified to create a generalizable PK model. Pharmacometric simulations were performed using the PUMAS software platform to reproduce the results of published studies. A suitable model that could reproduce the results of all other published studies was identified. With the help of a generalizable model, an optimal dosage regimen was designed considering the important covariates of the identified model. RESULTS: With the systematic search, only gentamicin had multiple PK reports during TH. A generalizable model was identified and the model predictions could match the reported/observed concentrations of publications. Birth weight and serum creatinine were the significant covariates influencing the PK of gentamicin in neonates. A dosage nomogram was designed using pharmacometric simulations to maintain gentamicin concentrations below 10 µg/mL at peak and below 2 µg/mL at trough. CONCLUSIONS: A generalizable PK model for gentamicin during TH in neonates was identified. Using the model, a dosing nomogram for gentamicin was designed. IMPACT: Dosing guidelines for antimicrobials during TH in neonates is lacking. This is the first study to identify the generalizable model for gentamicin during TH in neonates. Nomogram, proposed in the study, will aid the clinicians to individualize gentamicin dosing regimen for neonates considering the birth weight and serum creatinine.

Influence of N-acetyltransferase 2 (NAT2) genotype/single nucleotide polymorphisms on clearance of isoniazid in tuberculosis patients: a systematic review of population pharmacokinetic models.

PURPOSE: Significant pharmacokinetic variabilities have been reported for isoniazid across various populations. We aimed to summarize population pharmacokinetic studies of isoniazid in tuberculosis (TB) patients with a specific focus on the influence of N-acetyltransferase 2 (NAT2) genotype/single-nucleotide polymorphism (SNP) on clearance of isoniazid. METHODS: A systematic search was conducted in PubMed and Embase for articles published in the English language from inception till February 2022 to identify population pharmacokinetic (PopPK) studies of isoniazid. Studies were included if patient population had TB and received isoniazid therapy, non-linear mixed effects modelling, and parametric approach was used for building isoniazid PopPK model and NAT2 genotype/SNP was tested as a covariate for model development. RESULTS: A total of 12 articles were identified from PubMed, Embase, and hand searching of articles. Isoniazid disposition was described using a two-compartment model with first-order absorption and linear elimination in most of the studies. Significant covariates influencing the pharmacokinetics of isoniazid were NAT2 genotype, body weight, lean body weight, body mass index, fat-free mass, efavirenz, formulation, CD4 cell count, and gender. Majority of studies conducted in adult TB population have reported a twofold or threefold increase in isoniazid clearance for NAT2 rapid acetylators compared to slow acetylators. CONCLUSION: The variability in disposition of isoniazid can be majorly attributed to NAT2 genotype. This results in a trimodal clearance pattern with a multi-fold increase in clearance of NAT2 rapid acetylators compared to slow acetylators. Further studies exploring the generalizability/adaptability of developed PopPK models in different clinical settings are required.

Tenofovir Plasma Concentration from Preexposure Prophylaxis at the Time of Potential HIV Exposure: a Population Pharmacokinetic Modeling and Simulation Study Involving Serodiscordant Couples in East Africa.

The Partners Demonstration Project was a prospective, open-label, implementation science-driven study of preexposure prophylaxis (PrEP) among heterosexual HIV serodiscordant couples in Kenya and Uganda. Adherence data were collected using the Medication Event Monitoring System (MEMS), and time of sexual activity was collected using the mobile phone short message service (SMS). Two plasma samples were collected at a single study visit. We integrated adherence, pharmacokinetics, and SMS data using a population pharmacokinetic (PopPK) model to simulate tenofovir plasma concentrations from PrEP at the time of sexual activity. In the first stage of this analysis, we used data from the current study to update a prior PopPK model of tenofovir (TFV) developed with data from the Partners PrEP Study (a phase III clinical trial). The second stage involved simulating plasma concentrations at the time of sexual activity using empirical Bayes estimates (EBEs) derived from the final model. In addition, EBEs from a previously published parent metabolite model of TFV (MTN-001, an open-label 3-way crossover study in healthy women) was used to simulate tenofovir diphosphate (TFV-DP) concentrations. We estimated percent PrEP "coverage" as the number of reported sexual events during which simulated concentrations were above an a priori threshold concentrations associated with a high degree of protection from HIV infection: plasma TFV of >40 ng/ml and peripheral blood mononuclear cell (PBMC) TFV-DP concentration of >36 fmol/million cells. The levels of coverage were 72% for TFV and 81% for TFV-DP. These levels are consistent with a high degree of protection against HIV acquisition in this study of a pragmatic delivery model for antiretroviral-based HIV prevention.

Preparation, validation and user-testing of pictogram-based patient information leaflets for hemodialysis patients.

BACKGROUND: Patient information leaflets are universally-accepted resources to educate the patients/users about their medications, disease and lifestyle modification. OBJECTIVES: The objective of the study was to prepare, validate and perform user-testing of pictogram-based patient information leaflets (P-PILs) among hemodialysis (HD) patients. METHODS: The P-PILs are prepared by referring to the primary, secondary and tertiary resources. The content and pictograms of the leaflet have been validated by an expert committee consisting of three nephrologists and two academic pharmacists. The Baker Able Leaflet Design has been applied to develop the layout and design of the P-PILs. RESULTS: Quasi-experimental pre- and post-test design without control group was conducted on 81 HD patients for user-testing of P-PILs. The mean Baker Able Leaflet Design assessment score for English version of the leaflet was 28, and 26 for Kannada version. The overall user-testing knowledge assessment mean scores were observed to have significantly improved from 44.25 to 69.62 with p value <0.001. CONCLUSION: The overall user opinion of content and legibility of the leaflets was good. Pictogram-based patient information leaflets can be considered an effective educational tool for HD patients.

Precision Medicine Strategies to Improve Isoniazid Therapy in Patients with Tuberculosis.

Due to interindividual variability in drug metabolism and pharmacokinetics, traditional isoniazid fixed-dose regimens may lead to suboptimal or toxic isoniazid concentrations in the plasma of patients with tuberculosis, contributing to adverse drug reactions, therapeutic failure, or the development of drug resistance. Achieving precision therapy for isoniazid requires a multifaceted approach that could integrate various clinical and genomic factors to tailor the isoniazid dose to individual patient characteristics. This includes leveraging molecular diagnostics to perform the comprehensive profiling of host pharmacogenomics to determine how it affects isoniazid metabolism, such as its metabolism by N-acetyltransferase 2 (NAT2), and studying drug-resistant mutations in the Mycobacterium tuberculosis genome for enabling targeted therapy selection. Several other molecular signatures identified from the host pharmacogenomics as well as other omics-based approaches such as gut microbiome, epigenomic, proteomic, metabolomic, and lipidomic approaches have provided mechanistic explanations for isoniazid pharmacokinetic variability and/or adverse drug reactions and thereby may facilitate precision therapy of isoniazid, though further validations in larger and diverse populations with tuberculosis are required for clinical applications. Therapeutic drug monitoring and population pharmacokinetic approaches allow for the adjustment of isoniazid dosages based on patient-specific pharmacokinetic profiles, optimizing drug exposure while minimizing toxicity and the risk of resistance. Current evidence has shown that with the integration of the host pharmacogenomics-particularly NAT2 and Mycobacterium tuberculosis genomics data along with isoniazid pharmacokinetic concentrations in the blood and patient factors such as anthropometric measurements, comorbidities, and type and timing of food administered-precision therapy approaches in isoniazid therapy can be tailored to the specific characteristics of both the host and the pathogen for improving tuberculosis treatment outcomes.

Predictive performance of population pharmacokinetic models of imatinib in chronic myeloid leukemia patients.

BACKGROUND AND AIM: Chronic myeloid leukemia is a myeloproliferative neoplasm associated with the specific chromosomal translocation known as the Philadelphia chromosome. Imatinib is a potent BCR-ABL tyrosine kinase inhibitor, which is approved as the first line therapy for CML patients. There are various population pharmacokinetic studies available in the literature for this population. However, their use in other populations outside of their cohort for the model development has not been evaluated. This study was aimed to perform the predictive performance of the published population pharmacokinetic models for imatinib in CML population and propose a dosing nomogram. METHODS: A systematic review was conducted through PubMed, and WoS databases to identify PopPK models. Clinical data collected in adult CML patients treated with imatinib was used for evaluation of these models. Various prediction-based metrics were used for assessing the bias and precision of PopPK models using individual predictions. RESULTS: Eight imatinib PopPK model were selected for evaluating the model performance. A total of 145 plasma imatinib samples were collected from 43 adult patients diagnosed with CML and treated with imatinib. The PopPK model reported by Menon et al. had better performance than all other PopPK models. CONCLUSION: Menon et al. model was able to predict well for our clinical data where it had the relative mean prediction error percentage ≤ 20%, relative median absolute prediction error ≤ 30% and relative root mean square error close to zero. Based on this final model, we proposed a dosing nomogram for various weight groups, which could potentially help to maintain the trough concentrations in the therapeutic range.

Influence of N-acetyltransferase 2 polymorphisms and clinical variables on liver function profile of tuberculosis patients.

BACKGROUND: Single nucleotide polymorphisms (SNPs) in the N-acetyltransferase 2 (NAT2) gene as well as several other clinical factors can contribute to the elevation of liver function test values in tuberculosis (TB) patients receiving antitubercular therapy (ATT). RESEARCH DESIGN AND METHODS: A prospective study involving dynamic monitoring of the liver function tests among 130 TB patients from baseline to 98 days post ATT initiation was undertaken to assess the influence of pharmacogenomic and clinical variables on the elevation of liver function test values. Genomic DNA was extracted from serum samples for the assessment of NAT2 SNPs. Further, within this study population, we conducted a case control study to identify the odds of developing ATT-induced drug-induced liver injury (DILI) based on NAT2 SNPs, genotype and phenotype, and clinical variables. RESULTS: NAT2 slow acetylators had higher mean [90%CI] liver function test values for 8-28 days post ATT and higher odds of developing DILI (OR: 2.73, 90%CI: 1.05-7.09) than intermediate acetylators/rapid acetylators. CONCLUSION: The current study findings provide evidence for closer monitoring among TB patients with specific NAT2 SNPs, genotype and phenotype, and clinical variables, particularly between the period of more than a week to one-month post ATT initiation for better treatment outcomes.

Validated HPLC method for ceftriaxone from dried blood spots for pharmacokinetic studies and therapeutic drug monitoring in neonatal population.

Background: Pharmacokinetic evaluation is essential for the precise dosing of ceftriaxone in neonates. There is a need for developing a sensitive, affordable and convenient analytical method that can estimate ceftriaxone from dried blood spot (DBS) samples of neonates. Method: An HPLC-UV method was developed and validated as per ICH M10 for ceftriaxone from DBS and plasma using an Inertsil-ODS-3V column with gradient elution. DBS samples were extracted with methanol. Clinical validation was performed using neonatal samples. Results: The developed plasma- and DBS-based-HPLC method were linear from 2-700 µg/ml and 2-500 µg/ml, respectively, for ceftriaxone. Bland-Altman analysis indicated a strong interconvertibility between the plasma and DBS assays. Conclusion: Observed concentrations in clinical samples were comparable to the predicted concentrations, proving the clinical validity of the method.

Neonatal meningitis is usually treated with the drug ceftriaxone. It is essential to determine the amount of ceftriaxone in the blood for precise dosing that is safe and effective in newborn children. Dried blood spot (DBS) sampling from a heel prick is a less invasive sample collection method for newborn children than withdrawing blood from a vein. In this study we developed a robust analytical method based on a commonly available analytical platform to measure ceftriaxone in DBS samples. The results of ceftriaxone analysis obtained using the developed DBS-based method were compared with the results of traditional plasma sample analysis to make sure that they are accurate and reproducible. The range of analysis of the method is 2­500 µg/ml, which is suitable for the measurement of ceftriaxone concentration levels in newborns' blood. The effect of varying proportions of red blood cells in whole blood (30­50%) and volume of blood (20­60 µl) applied on the DBS card were not found to influence the results. The method was validated with clinical samples from newborn children and resulted in the expected concentrations. The developed method is affordable and can be used for therapeutic drug monitoring and precise dosing of ceftriaxone in newborn children.

Predictive Performance of Population Pharmacokinetic Models for Amikacin in Term Neonates.

BACKGROUND AND OBJECTIVE: Amikacin is preferred in treating Gram-negative infections in neonates and it has a narrow therapeutic window. The population pharmacokinetic modeling approach can aid in designing optimal dosage regimens for amikacin in neonates. In this study, we attempted to identify the suitable population pharmacokinetic model from the published reports for the study population from an Indian setting. METHODS: Published population pharmacokinetic studies for amikacin in neonates were identified. Data on structural models and typical pharmacokinetic parameters were extracted from the studies. For the clinical study, neonates who met the inclusion criteria were enrolled in the study from the NICU, Kasturba Medical College, Manipal, during Jan 2020 to March 2022. Drug concentrations were estimated, and demographic and clinical data were collected. Identified population pharmacokinetic models were used to predict the amikacin concentrations in neonates. Predicted concentrations were compared against the observed concentrations. Differences between predicted and observed concentrations were quantified using statistical measures. The population pharmacokinetic model, which was able to predict the data well, is considered a suitable model for the study population. Dosing regimens were suggested for neonates using the pharmacometric simulation approach generated by the selected model. RESULTS: A total of 43 plasma samples were collected from 31 neonates. Twelve population pharmacokinetic models were found for amikacin in neonates. The predictive performance of the 12 studies was performed using clinical data. A two-compartment model reported by Illamola et al. predicted the amikacin concentrations better than other models. Illamola et al. reported creatinine clearance and body weight as the significant covariates impacting the pharmacokinetic parameters of amikacin. This model was able to predict the clinical data with 29.97% and 0.686 of relative median absolute prediction error and relative root mean square error, respectively, which is the best among the published models. The Illamola et al. model was selected as the final model to perform pharmacometric simulations for the subjects with different combinations of creatinine clearance and body weight. Dosage regimens were designed to attain target therapeutic concentrations for the virtual subjects and a nomogram was developed. CONCLUSIONS: The population pharmacokinetic model reported by the Illamola et al. model was selected as the final model to explain the clinical data with the lowest relative median absolute prediction error and relative root mean square error when compared with other models. An amikacin nomogram was developed for the neonates whose creatinine clearance and body weight ranged between 10 and 90 mL/min and between 2 and 4 kg, respectively. A developed nomogram can assist clinicians to design an optimal dosage regimen of amikacin for term neonates.