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.

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.

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.

Factors Influencing Pharmacokinetics of Tamoxifen in Breast Cancer Patients: A Systematic Review of Population Pharmacokinetic Models

BACKGROUND

Tamoxifen is useful in managing breast cancer and it is reported to have significant variability in its pharmacokinetics. This review aimed to summarize reported population pharmacokinetics studies of tamoxifen and to identify the factors affecting the pharmacokinetics of tamoxifen in adult breast cancer patients.

METHOD

A systematic search was undertaken in Scopus, Web of Science, and PubMed for papers published in the English language from inception to 20 August 2022. Studies were included in the review if the population pharmacokinetic modeling was based on non-linear mixed-effects modeling with a parametric approach for tamoxifen in breast cancer patients.

RESULTS

After initial selection, 671 records were taken for screening. A total of five studies were selected from Scopus, Web of Science, PubMed, and by manual searching. The majority of the studies were two-compartment models with first-order absorption and elimination to describe tamoxifen and its metabolites' disposition. The CYP2D6 phenotype and CYP3A4 genotype were the main covariates that affected the metabolism of tamoxifen and its metabolites. Other factors influencing the drug's pharmacokinetics included age, co-medication, BMI, medication adherence, CYP2B6, and CYP2C19 genotype.

CONCLUSION

The disposition of tamoxifen and its metabolites varies primarily due to the CYP2D6 phenotype and CYP3A4 genotype. However, other factors, such as anthropometric characteristics and menopausal status, should also be addressed when accounting for this variability. All these studies should be externally evaluated to assess their applicability in different populations and to use model-informed dosing in the clinical setting.

Application of Physiologically Based Pharmacokinetic Modeling of Lamotrigine Using PK-Sim in Predicting the Impact of Drug Interactions and Dosage Adjustment

Background

Physiologically based pharmacokinetic (PBPK) models are helpful as mechanistic representations of pharmacokinetic parameters. There were no reports of lamotrigine (LTG) PBPK models developed in open source platforms like PK-Sim.

Objectives

The present work was aimed to build a LTG PBPK model and compare it to the clinical data from South Asian Indian patients and use this model to understand the drug interactions of LTG and explore the optimal doses.

Methods and Material

The PBPK model was developed using the PK-Sim software platform and qualified with LTG plasma concentration data from an Indian study. The European population database was chosen as the patient setting in the software. Physicochemical data of LTG and enzyme kinetic data were incorporated from the literature. Dosing protocols were as per the previous study. Interaction models for drug interactions with carbamazepine and valproate were also simulated.

Results

Most of the model predicted concentration-time profiles of LTG at steady-state were well within the observed concentrations. The developed models were suitably qualified. The drug interaction model was used to assess the impact of induction and inhibition of the pharmacokinetic profile of LTG.

Conclusions

The predicted plasma concentrations of the developed PBPK models using the European population database were very similar to the data from Indian patients. The developed LTG PBPK models are applicable in predicting the impact of drug interactions and can yield appropriate LTG doses to be administered.

Population Pharmacokinetics of Hydroxychloroquine Sulfate in Healthcare Workers, Given for Prophylaxis Against Coronavirus Disease 2019 (COVID-19) in India

Healthcare workers (HCWs) and frontline workers were recommended hydroxychloroquine (HCQ) 400 mg twice a day on day 1, followed by 400 mg once weekly for the next 7 weeks, as prophylaxis against COVID-19. There was limited information on the population pharmacokinetics (popPK) of HCQ in an Indian setting when administered for prophylaxis against COVID-19, and hence this study was proposed. It was a multicentric prospective study conducted at 3 sites in India wherein HCWs who were already on HCQ prophylaxis, who were about to start prophylaxis or who had stopped the prophylaxis for any reason were enrolled. Each participant gave 2 to 6 blood samples at different time points and whole-blood HCQ concentrations were assayed using liquid chromatography with tandem mass spectrometry (LC MS/MS). popPK analysis was performed using PUMAS 1.1.0. A total of N = 338 blood samples from N = 121 participants were included in the popPK analysis. A 2-compartment structural model with linear elimination was able to explain the observed data. Body weight was found to be a significant covariate influencing drug clearance. The final model was assessed using goodness-of-fit plots, a visual predictive check and a bootstrap, all of which confirmed that the model was appropriate. Simulations based on the current regimen showed that trough values were below the half-maximal effective concentration (EC50) of 0.7 μmol against COVID-19. A new weight-based dosage regimen was proposed to maintain the trough concentration above the EC50 threshold.

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.

Validation of an HPLC method for estimation of cefotaxime from dried blood spot: alternative to plasma-based PK evaluation in neonates

Aim: Pharmacokinetic evaluation of cefotaxime in neonates is currently a challenge due to the large volume requirement of blood for its analysis by existing methods. A dried blood spot (DBS) based method is the best alternative. Materials & methods: We validated an HPLC method for estimation of cefotaxime from DBS and plasma. Extraction employed a simple procedure using acetonitrile and buffer. Selective separation of cefotaxime was achieved on a C8 column using gradient programming. Results & conclusion: The linearity of the method ranged from 2 to 200 μg/ml with acceptable precision and accuracy for both plasma and DBS. Hematocrit was not affecting the assay accuracy. A strong correlation and interchangeability observed with the plasma method proves its clinical validity for application to PK evaluations.

Assessment of Demographic and Socio-Behavioral Factors on Adherence to HIV Pre-Exposure Prophylaxis Using a Markov Modeling Approach

Purpose: Adherence is important for the effectiveness of human immunodeficiency virus (HIV) preexposure prophylaxis (PrEP). The objective of the current work is to assess the impact of multiple demographic and socio-behavioral factors on the adherence to tenofovir-based PrEP among HIV serodiscordant couples in East Africa using Markov mixed-effects modeling approach.

Methods: The Partners Demonstration Project was a prospective, open-label, implementation science-driven study of HIV PrEP among heterosexual HIV serodiscordant couples in Kenya and Uganda. The uninfected partner received oral PrEP according to the “bridge to antiretroviral therapy [ART]” strategy (i.e., until the infected partner had been on ART for ≥6 months). Adherence was monitored electronically; demographic and socio-behavioral data were collected during study visits. Analyzed data reflect 12 months of follow-up per participant. A two-state, first-order, discrete time Markov model was developed with longitudinal adherence data characterized by “dose taking (1)” and “dose missing (0).” Covariate effects were linearly added in the logit domain of transition probability parameters (P01 and P10) in the model. The full covariate model was initially developed, followed by backward elimination process to reduce the model. All significant covariates reported by a prior primary statistical analysis of the same data were included in the full covariate model.

Results: The model included data from 920 participants, who were predominantly male (65%). Significant covariates associated with higher adherence were 25 years or older [odds ratio (OR) for P10, 0.61], female sex (OR for P10, 0.67), participant wanting the relationship with the partner to succeed (OR for P10, 0.79; OR for P01, 1.45), and sex with partner either with 100% or <100% condom use compared to those reported no sex (OR for P10, 0.84; OR for P01, 1.21). Significant covariates associated with lower adherence were partner on ART >6 months (OR for P01, 0.86; OR for P10, 1.34), subject in the study for >6 months (OR for P01, 0.8; OR for P10, 1.25), and problematic alcohol use (OR for P01, 0.63; OR for P10, 1.16).

Conclusion: The developed Markov model provides a mechanistic understanding of relationship between demographic, socio-behavioral covariates, and PrEP adherence, by indicating the pattern of adherence influenced by each factor over time. Such data can be used for further intervention development to promote PrEP adherence.

Population pharmacokinetics of primaquine and the effect of hepatic and renal dysfunction: An exploratory approach

OBJECTIVES

We attempted to develop a population pharmacokinetic model for primaquine (PQ) and evaluate the effect of renal and hepatic dysfunction on PQ pharmacokinetics.

MATERIALS AND METHODS

The data were collected from a prospective, nonrandomized clinical study in healthy volunteers and patients with mild-moderate hepatic dysfunction and renal dysfunction. Model development was conducted using NONMEM^® software, and parameter estimation was conducted using first-order conditional estimation with interaction method.

RESULTS

Final data included a total of 53 study participants (13 healthy individuals, 12 with mild hepatic dysfunction, 6 with moderate hepatic dysfunction, and 22 with renal dysfunction) with 458 concentrations records. Absorption rate constant (Ka) was constrained to be higher than elimination rate constant to avoid flip-flop situation. Mild hepatic dysfunction was a significant covariate on volume of distribution, and it is approximately three folds higher compared to other subjects. Fixed effects parameter estimates of the final model - absorption rate constant (Ka), volume of distribution (V), and clearance (CL) - were 0.95/h, 498 L, and 39 L/h, respectively. Between-subject variability estimates (% CV) on Ka, V, and CL were 77, 66, and 65, respectively. Residual error was modeled as combination error model with the parameter estimates for proportion error 12% CV and additive error (standard deviation) 1.5 ng/ml.

CONCLUSION

Population pharmacokinetic modeling showed that the volume of distribution of PQ in subjects with moderate hepatic dysfunction increases approximately three folds resulting in a significantly lower plasma concentration.

A Systematic Evaluation of Effect of Adherence Patterns on the Sample Size and Power of a Clinical Study

The objective of our study was to evaluate the effect of adherence patterns on the sample size and power of a clinical trial. Simulations from a population pharmacokinetic/pharmacodynamic (PK/PD) model linked to an adherence model were used. Four types of drug characteristics, such as long (~35 hours) and short (~12 hours) half-life in combination with earlier or delayed time to reach steady-state PD end points were studied. Adherence patterns were simulated using Markov chains. Our results clearly demonstrate the significant impact of varying levels and patterns of nonadherence on the sample size and power of a study. For drugs with short half-lives the evidence to support efficacy could be diluted by various patterns of nonadherence that would make its efficacy indistinguishable from the response to placebo. Prospectively utilizing clinical trial simulations with thorough incorporation of various adherence patterns would provide valuable information when designing a trial.

Factors that Correlate with Poor Glycemic Control in Type 2 Diabetes Mellitus Patients with Complications

Objectives

Inadequate glycemic control amongst patients with Type 2 diabetes mellitus (T2DM) indicates a major public health problem and a significant risk factor for the progression and complications caused by diabetes. Glycemic control is the main therapeutic objective for the prevention of organ damage and other complications arising from diabetes.

Methods

This was a retrospective observational study of T2DM patients with complications, who were aged 40 years and older. The study was conducted retrospectively on medical records (in-patient and out-patient) obtained from a South Indian teaching hospital, Manipal, India. The patients included in the study had fasting blood sugar, postprandial blood sugar and HbA1c measured at least twice during follow-ups the previous year. Patients' HbA1c levels were categorized into good control ≤7% (≤53mmol/mol), and poor control >7% (>53mmol/mol), and patients' characteristics were analyzed.

Results

A total of 657 patients were included in the study. The mean age was 59.67 (SD = 9.617) years, with 152 (23.1%) females and 505 (76.9%) males, and 514 (78.2%) patients had poor glycemic control. Most of the patients were on insulin mono-therapy [n = 271 (42.1%)], about a third of the patients were on combination therapy that included an oral hypoglycemic agent and insulin [n = 236 (36.6%)]. Patients with a history of more than 10 years of diabetes [n = 293 (44.6%)], had a family history of diabetes [n = 256 (39%)] and obesity [n = 95 (14.5%)], all had poor glycemic control.

Conclusion

This present study indicated a significant association of gender (female), age, high-density lipoprotein level, duration of diabetes and type of medication, with poor glycemic control in T2DM patients that had secondary medical complications.

High performance liquid chromatographic fluorescence detection method for the quantification of rivastigmine in rat plasma and brain: application to preclinical pharmacokinetic studies in rats

A highly sensitive and selective high performance liquid chromatographic fluorescence detection method has been developed and validated for the quantification of rivastigmine in rat plasma and brain. Protein precipitation and one-step liquid–liquid extraction techniques were utilized for the extraction of RSM from brain and plasma, respectively, along with an internal standard. The chromatographic separation was achieved with a column inertsil ODS-3V and a mobile phase consisting of ammonium acetate buffer (20 mM, pH 4.5) and acetonitrile (76:24, v/v) delivered at a flow rate of 1 ml/min. The lower limit of quantitation for the developed method was 10 ng/mL for both matrices. The method was found to be accurate and reproducible and was successfully used to quantify levels of RSM in plasma and brain following intravenous administration of RSM in rats.

Predictors of warfarin-induced bleeding in a South Indian cardiology unit

Objectives:

Warfarin-induced bleedingresults in increased morbidity and mortality and higher cost of healthcare. The objective of the study is to identify the predictors of warfarin-induced bleeding in the Cardiology Unit of a teaching hospital.

Materials and Methods:

A cross-sectional study was carried out for a period of six months in a tertiary care teaching hospital. A total of 235 patients were enrolled in the study, to identify the predictors of warfarin-induced bleeding. Only prescriptions with warfarin were selected for the study. The chi square test was used to find the association between demography and risk factors.

Results:

Out of 235 patients, 61 (25.95%) had developed warfarin-induced bleeding and the majority were in the age group of 41 – 61 years (60.65%), and it was also found to be higher in women (62.29%). The length of stay was > 14 days (65.57%) and the number of drugs prescribed was in the range of 6 – 12 (52.45%). Aspirin (40.98%), Heparin (36.06%), Clopidogrel (22.95%), and Streptokinase (14.75%) were the most common drugs involved, and other comorbid conditions like diabetes (37.70%), hypertension (32.78%), smoking (57.37%), and alcohol (32.78%) were found to be major predictors of warfarin-induced bleeding in this study. The severity of warfarin-induced most of the bleeding reactions were moderate (44.26%) and the most common site of bleeding was gastrointestinal system (34.42%).

Conclusion:

Predictors of warfarin-induced bleeding were found to be female gender, length of stay, number of medications, drugs like aspirin, heparin, and clopidogrel, and other comorbidities like smoking, alcohol, and hypertension.

Pattern of Angiotensin-converting enzyme inhibitors induced adverse drug reactions in South Indian teaching hospital

BACKGROUND

Adverse drug reactions (ADRs) occur frequently with cardiovascular drugs leading to change in therapy, increasing morbidity, and mortality.

AIM

The study was conducted to evaluate the incidence of ADRs due to angiotensin-converting enzyme Inhibitors in cardiology department.

MATERIALS AND METHODS

A cross-sectional observational study was carried out for a period of 6 months. The data were assessed for the pattern of the ADRs with respect to patient demographics, nature of the reaction, outcome of the reactions, causality, severity, and preventability.

RESULTS

Among 692 patients, 51 (7.36%) had developed 60 ADRs, and majority of cases (56.66%) were in the age group of >61 years and most of them were developed in female (80%). The common ADRs observed were cough, hypotension, hyperkalemia, and acute renal failure. In 21.66% cases the dose of the suspected drug was altered and in 78.33% cases the drug was withdrawn. Considering the outcome, 93.33% of cases recovered from ADRs, whereas in 6.66% cases were continuing. Causality assessment showed that majority of ADRs was probable and were found to be moderately severe.

CONCLUSION

Our study concludes geriatrics and female patients have higher incidence of ADRs. So early identification and management of ADRs are essential for this population.

Cost of adverse drug reactions in a South Indian tertiary care teaching hospital

In India, very few reports on the cost of adverse drug reactions (ADRs) are available. There is a need to study this aspect of health care in order to understand the economic burden imposed by ADRs. The aim of the current work was to study the costs associated with documented ADRs in a tertiary care teaching hospital. This study was conducted in medical wards of a south Indian tertiary care teaching hospital over a 6-month period. The study protocol was assessed and approved by the institutional ethics committee. A total of 317 ADRs from 246 patients were identified during the study period. The present study used an intensive monitoring method to detect ADRs and assessed an incidence of 32.7% adverse reactions in the monitored group. The causality, severity, predictability, and preventability of the documented ADRs were assessed. The total cost to the hospital due to ADRs was found to be Rs. 1,567,397 (US$36 451). The average cost per patient hospitalized with an ADR was Rs. 4,945 (US$115). The cost per reaction was found to be higher in the Indian context, as the per capita annual expenditure on health in this country is around US$109.