Prediction of milk/plasma concentration ratio of drugs

Machine Learning Models for Prediction of Xenobiotic Chemicals with High Propensity to Transfer into Human Milk

Breast milk serves as a vital source of essential nutrients for infants. However, human milk contamination via the transfer of environmental chemicals from maternal exposome is a significant concern for infant health. The milk to plasma concentration (M/P) ratio is a critical metric that quantifies the extent to which these chemicals transfer from maternal plasma into breast milk, impacting infant exposure. Machine learning-based predictive toxicology models can be valuable in predicting chemicals with a high propensity to transfer into human milk. To this end, we build such classification- and regression-based models by employing multiple machine learning algorithms and leveraging the largest curated data set, to date, of 375 chemicals with known milk-to-plasma concentration (M/P) ratios. Our support vector machine (SVM)-based classifier outperforms other models in terms of different performance metrics, when evaluated on both (internal) test data and an external test data set. Specifically, the SVM-based classifier on (internal) test data achieved a classification accuracy of 77.33%, a specificity of 84%, a sensitivity of 64%, and an F-score of 65.31%. When evaluated on an external test data set, our SVM-based classifier is found to be generalizable with a sensitivity of 77.78%. While we were able to build highly predictive classification models, our best regression models for predicting the M/P ratio of chemicals could achieve only moderate R2 values on the (internal) test data. As noted in the earlier literature, our study also highlights the challenges in developing accurate regression models for predicting the M/P ratio of xenobiotic chemicals. Overall, this study attests to the immense potential of predictive computational toxicology models in characterizing the myriad of chemicals in the human exposome.

Predicting Maternal and Infant Tetrahydrocannabinol Exposure in Lactating Cannabis Users: A Physiologically Based Pharmacokinetic Modeling Approach

A knowledge gap exists in infant tetrahydrocannabinol (THC) data to guide breastfeeding recommendations for mothers who use cannabis. In the present study, a paired lactation and infant physiologically based pharmacokinetic (PBPK) model was developed and verified. The verified model was used to simulate one hundred virtual lactating mothers (mean age: 28 years, body weight: 78 kg) who smoked 0.32 g of cannabis containing 14.14% THC, either once or multiple times. The simulated breastfeeding conditions included one-hour post smoking and subsequently every three hours. The mean peak concentration (Cmax) and area under the concentration-time curve (AUC(0-24 h)) for breastmilk were higher than in plasma (Cmax: 155 vs. 69.9 ng/mL; AUC(0-24 h): 924.9 vs. 273.4 ng·hr/mL) with a milk-to-plasma AUC ratio of 3.3. The predicted relative infant dose ranged from 0.34% to 0.88% for infants consuming THC-containing breastmilk between birth and 12 months. However, the mother-to-infant plasma AUC(0-24 h) ratio increased up to three-fold (3.4-3.6) with increased maternal cannabis smoking up to six times. Our study demonstrated the successful development and application of a lactation and infant PBPK model for exploring THC exposure in infants, and the results can potentially inform breastfeeding recommendations.

Potential neonatal toxicity of new psychoactive substances

Cannabis, cocaine, 3,4-methylenedioxymethamphetamine, and lysergic acid diethylamide are psychoactive substances with a significant increase in consumption during the 21st century due to their popularity in medicinal and recreational use. New psychoactive substances (NPSs) mimic established psychoactive substances. NPSs are known as being natural and safe to consumers; however, they are neither natural nor safe, causing severe adverse reactions, including seizures, nephrotoxicity, and sometimes death. Synthetic cannabinoids, synthetic cathinones, phenethylamines, and piperazines are all examples of NPSs. As of January 2020, nearly 1000 NPSs have become documented. Due to their low cost, ease of availability, and difficulty of detection, misuse of NPSs has become a familiar and growing problem, especially in adolescents and young adults in the past decade. The use of NPSs is associated with higher risks of unplanned sexual intercourse and pregnancy. As many as 4 in 100 women seeking treatment for substance abuse are pregnant or nursing. Animal studies and human clinical case reports have shown that exposure to certain NPSs during lactation periods has toxic effects on neonates, increasing various risks, including brain damage. Nevertheless, neonatal toxicity effects of NPSs are usually unrecognized and overlooked by healthcare professionals. In this review article, we introduce and discuss the potential neonatal toxicity of NPSs, emphasizing synthetic cannabinoids. Utilizing the established prediction models, we identify synthetic cannabinoids and their highly accumulative metabolites in breast milk.

A systematic review on maternal-to-infant transfer of drugs through breast milk during the treatment of malaria, tuberculosis, and neglected tropical diseases

BACKGROUND

Exclusive breastfeeding of infants under 6 months of age is recommended by the World Health Organization. In 2021, over 300 million combined incident cases of malaria, tuberculosis, and neglected tropical diseases (NTDs) were reported, predominantly in low-income countries. For many of the drugs used as first-line treatments for these conditions, there is limited knowledge on infant exposure through breastfeeding with poorly understood consequences. This review summarized available knowledge on mother-to-infant transfer of these drugs to inform future lactation pharmacokinetic studies.

METHODOLOGY

A list of first-line drugs was generated from the latest WHO treatment guidelines. Using standard online databases, 2 independent reviewers searched for eligible articles reporting lactation pharmacokinetics studies and extracted information on study design, participant characteristics, and the mathematical approach used for parameter estimation. A third reviewer settled any disagreements between the 2 reviewers. All studies were scored against the standardized "ClinPK" checklist for conformity to best practices for reporting clinical pharmacokinetic studies. Simple proportions were used to summarize different study characteristics.

FINDINGS

The most remarkable finding was the scarcity of lactation pharmacokinetic data. Only 15 of the 69 drugs we listed had lactation pharmacokinetics fully characterized. Most studies enrolled few mothers, and only one evaluated infant drug concentrations. Up to 66% of the studies used non-compartmental analysis to estimate pharmacokinetic parameters rather than model-based compartmental analysis. Unlike non-compartmental approaches, model-based compartmental analysis provides for dynamic characterization of individual plasma and breast milk concentration-time profiles and adequately characterizes variability within and between individuals, using sparsely sampled data. The "ClinPK" checklist inadequately appraised the studies with variability in the number of relevant criteria across different studies.

CONCLUSIONS/SIGNIFICANCE

A consensus is required on best practices for conducting and reporting lactation pharmacokinetic studies, especially in neglected diseases such as malaria, tuberculosis, and NTDs, to optimize treatment of mother-infant pairs.

Maternal drugs and breastfeeding: Risk assessment from pharmacokinetics to safety evidence - A contribution from the ConcePTION project

Human milk is the most appropriate form of nutrition for infants while taking medication during the postpartum period is common. Discontinuation of breastfeeding is sometimes wrongly recommended for fear of adverse effects in the breastfed infant whereas only a few drugs are strictly contraindicated while breastfeeding. Most drugs are transferred from the mother's blood to the milk, but the breastfed infant usually ingests a small drug amount through human milk. As population-based evidence is still scarce on safety of drugs during breastfeeding, risk assessment relies on the little clinical evidence available and on pharmacokinetic principles, as well as on specialized sources of information that are essential for clinical decision-making. Risk assessment should not only be based on the drug's potential risk for the breastfed infant but should always take into account the benefits associated to breastfeeding, the risks of untreated maternal disease and the maternal willingness to breastfeed. Identifying situations with potential for drug accumulation in the breastfed infant is decisive while assessing the risk. Health care providers should always assume that mothers will be concerned and use risk communication as a key to ensure medication adherence and prevent unnecessary interruption of breastfeeding. When a mother still expresses concerns, decision support algorithms may facilitate communication and some strategies can be offered to minimize the drug exposure in the breastfed infant even when clinically not justified.

Are active efflux transporters contributing to infant drug exposure via breastmilk? A longitudinal study

Although most drugs are considered safe and compatible with breastfeeding, cases of toxic drug exposure have been reported. Active efflux transporters have been implicated as a mechanism in the transfer of drugs from mother to baby via breastmilk. Using breastmilk as a source of human mammary epithelial cells, this novel longitudinal study investigated the expression of four active transporters, namely, MDR1, MRP1, MRP2 and BCRP in the lactating human breast. BCRP gene was found to be strongly overexpressed with levels peaking at 5 months postpartum, potentially indicating a time where a breastfed infant may be at risk of inadvertent exposure to BCRP substrates. Serum albumin, a major component of human breastmilk was increasingly downregulated as lactation progresses. Xanthine oxidase/dehydrogenase, an enzyme in breastmilk attributed to a reduced risk of gastroenteritis caused by Escherichia coli and Salmonella enteritides, was downregulated. Lysozyme and fatty acid synthase are progressively upregulated. This study also shows that breastmilk-derived epithelial cells, when propagated in culture, exhibit characteristics significantly different to those derived directly from breastmilk. This serves to warn that in vitro studies are not a true representation of in vivo processes in the lactating breast; hence, application of in vitro data should be conducted with caution.

Physiologically based pharmacokinetic model to predict drug concentrations of breast cancer resistance protein substrates in milk

Many mothers need to take some medications during breastfeeding, which may carry a risk to breastfed infants. Thus, determining the amount of a drug transferred into breast milk is critical for risk-benefit analysis of breastfeeding. Breast cancer resistance protein (BCRP), an efflux transporter which usually protects the body from environmental and dietary toxins, was reported to be highly expressed in lactating mammary glands. In this study, we developed a mechanistic lactation physiologically based pharmacokinetic (PBPK) modeling approach incorporating BCRP mediated transport kinetics to simulate the concentration-time profiles of five BCRP drug substrates (acyclovir, bupropion, cimetidine, ciprofloxacin, and nitrofurantoin) in nursing women's plasma and milk. Due to the lack of certain physiological parameters and scaling factors in nursing women, we combine the bottom up and top down PBPK modeling approaches together with literature reported data to optimize and determine a set of parameters that are applicable for all five drugs. The predictive performance of the PBPK models was assessed by comparing predicted pharmacokinetic profiles and the milk-to-plasma (M/P) ratio with clinically reported data. The predicted M/P ratios for acyclovir, bupropion, cimetidine, ciprofloxacin, and nitrofurantoin were 2.48, 3.70, 3.55, 1.21, and 5.78, which were all within 1.5-fold of the observed values. These PBPK models are useful to predict the PK profiles of those five drugs in the milk for different dosing regimens. Furthermore, the approach proposed in this study will be applicable to predict pharmacokinetics of other transporter substrates in the milk.

Developing an In Vitro to In Vivo Extrapolation (IVIVE) Model to Predict Human Milk-to-Plasma Drug Concentration Ratios

Determining the amount of drug transferred into human milk is critical for benefit-risk analysis of taking medication while breastfeeding. In this study, we developed an in vitro and in vivo extrapolation (IVIVE) model to predict human milk/plasma (M/P) drug concentration ratios. Drug unionized fractions at pH 7.0 (F_ni,7.0) and 7.4 (F_ni,7.4), drug fractions unbound in human plasma (f_up) and milk (f_um), and in vitro cell permeability in both directions (efflux ratio, ER) were incorporated into the IVIVE model. A multiple regression E_max model was chosen to predict f_um from f_up and polar surface area (PSA). A total of 97 drugs with experimental ER from Caco-2 cells were used to test the IVIVE model. The M/P ratios predicted by the IVIVE model had a 1.93-fold geometric mean fold error (GMFE) and 72% of predictions were within two-fold error (Pw2FE), which were superior to the performance of previously reported five models. The IVIVE model showed a reasonable prediction accuracy for passive diffusion drugs (GMFE = 1.71-fold, Pw2FE = 82%, N = 50), BCRP substrates (BCRP: GMFE = 1.91-fold, Pw2FE = 60%, N = 5), and substrates of P-gp and BCRP (GMFE = 1.74-fold, Pw2FE = 75%, N = 8) and a lower prediction performance for P-gp substrates (GMFE = 2.51-fold, Pw2FE = 55%, N = 22). By fitting the observed M/P ratios of 39 P-gp substrates, an optimized ER (1.61) was generated to predict the M/P ratio of P-gp substrates using the developed IVIVE model. Compared with currently available in vitro models, the developed IVIVE model provides a more accurate prediction of the drug M/P ratio, especially for passive diffusion drugs. The model performance is expected to be further improved when more experimental f_um and ER data are available.

Development of a Generic Physiologically-Based Pharmacokinetic Model for Lactation and Prediction of Maternal and Infant Exposure to Ondansetron via Breast Milk

Ondansetron is commonly used in breastfeeding mothers to treat nausea and vomiting. There is limited information in humans regarding safety of ondansetron exposure to nursing infants and no adequate study looking at ondansetron pharmacokinetics during lactation. We developed a generic physiologically-based pharmacokinetic lactation model for small molecule drugs and applied this model to predict ondansetron transfer into breast milk and characterize infant exposure. Drug-specific model inputs were parameterized using data from the literature. Population-specific inputs were derived from a previously conducted systematic literature review of anatomic and physiologic changes in postpartum women. Model predictions were evaluated using ondansetron plasma and breast milk concentration data collected prospectively from 78 women in the Commonly Used Drugs During Lactation and infant Exposure (CUDDLE) study. The final model predicted breast milk and plasma exposures following a single 4 mg dose of intravenous ondansetron in 1,000 simulated women who were 2 days postpartum. Model predictions showed good agreement with observed data. Breast milk median prediction error (MPE) was 18.4% and median absolute prediction error (MAPE) was 53.0%. Plasma MPE was 32.5% and MAPE was 43.2%. The model-predicted daily and relative infant doses were 0.005 mg/kg/day and 3.0%, respectively. This model adequately predicted ondansetron passage into breast milk. The calculated low relative infant dose indicates that mothers receiving ondansetron can safely breastfeed. The model building blocks and population database are open-source and can be adapted to other drugs.

Prediction of drug concentrations in milk during breastfeeding, integrating predictive algorithms within a physiologically-based pharmacokinetic model

There is a risk of exposure to drugs in neonates during the lactation period due to maternal drug intake. The ability to predict drugs of potential hazards to the neonates would be useful in a clinical setting. This work aimed to evaluate the possibility of integrating milk-to-plasma (M/P) ratio predictive algorithms within the physiologically-based pharmacokinetic (PBPK) approach and to predict milk exposure for compounds with different physicochemical properties. Drug and physiological milk properties were integrated to develop a lactation PBPK model that takes into account the drug ionization, partitioning between the maternal plasma and milk matrices, and drug partitioning between the milk constituents. Infant dose calculations that take into account maternal and milk physiological variability were incorporated in the model. Predicted M/P ratio for acetaminophen, alprazolam, caffeine, and digoxin were 0.83 ± 0.01, 0.45 ± 0.05, 0.70 ± 0.04, and 0.76 ± 0.02, respectively. These ratios were within 1.26-fold of the observed ratios. Assuming a daily milk intake of 150 ml, the predicted relative infant dose (%) for these compounds were 4.0, 6.7, 9.9, and 86, respectively, which correspond to a daily ingestion of 2.0 ± 0.5 mg, 3.7 ± 1.2 µg, 2.1 ± 1.0 mg, and 32 ± 4.0 µg by an infant of 5 kg bodyweight. Integration of the lactation model within the PBPK approach will facilitate and extend the application of PBPK models during drug development in high-throughput screening and in different clinical settings. The model can also be used in designing lactation trials and in the risk assessment of both environmental chemicals and maternally administered drugs.

Antiepileptic Drug Exposure in Infants of Breastfeeding Mothers With Epilepsy

Importance

There is limited information on infant drug exposure via breastfeeding by mothers who are receiving antiepileptic drug therapy.

Objective

To provide direct, objective information on antiepileptic drug exposure through breast milk.

Design, Setting, and Participants

This prospective cohort study was conducted between December 2012 to October 2016, with follow-up in children until 6 years of age at 20 sites across the United States. Data were collected via an observational multicenter investigation (Maternal Outcomes and Neurodevelopmental Effects of Antiepileptic Drugs [MONEAD]) of outcomes in pregnant mothers with epilepsy and their children. Pregnant women with epilepsy who were aged 14 to 45 years, had pregnancies that had progressed to less than 20 weeks' gestational age, and had measured IQ scores of more than 70 points were enrolled and followed up through pregnancy and 9 postpartum months. Their infants were enrolled at birth. Data were analyzed from May 2014 to August 2019.

Exposures

Antiepileptic drug exposure in infants who were breastfed.

Main Outcomes and Measures

The percentage of infant-to-mother concentration of antiepileptic drugs. Antiepileptic drug concentrations were quantified from blood samples collected from infants and mothers at the same visit, 5 to 20 weeks after birth. Concentrations of antiepileptic drugs in infants at less than the lower limit of quantification were assessed as half of the lower limit. Additional measures collected were the total duration of all daily breastfeeding sessions and/or the volume of pumped breast milk ingested from a bottle.

Results

A total of 351 women (of 865 screened and 503 eligible individuals) were enrolled, along with their 345 infants (179 female children [51.9%]; median [range] age, 13 [5-20] weeks). Of the 345 infants, 222 (64.3%) were breastfed; the data collection yielded 164 matching infant-mother concentration pairs from 138 infants. Approximately 49% of all antiepileptic drug concentrations in nursing infants were less than the lower limit of quantification. The median percentage of infant-to-mother concentration for all 7 antiepileptic drugs and 1 metabolite (carbamazepine, carbamazepine-10,11-epoxide, levetiracetam, lamotrigine, oxcarbazepine, topiramate, valproate, and zonisamide) ranged from 0.3% (range, 0.2%-0.9%) to 44.2% (range, 35.2%-125.3%). In multiple linear regression models, maternal concentration was a significant factor associated with lamotrigine concentration in infants (Pearson correlation coefficient, 0.58; P < .001) but not levetiracetam concentration in infants.

Conclusions and Relevance

Overall, antiepileptic drug concentrations in blood samples of infants who were breastfed were substantially lower than maternal blood concentrations. Given the well-known benefits of breastfeeding and the prior studies demonstrating no ill effects when the mother was receiving antiepileptic drugs, these findings support the breastfeeding of infants by mothers with epilepsy who are taking antiepileptic drug therapy.

Lactational Transfer of Long-Chain Perfluorinated Carboxylic Acids in Mice: A Method to Directly Collect Milk and Evaluate Chemical Transferability

Perfluoroalkyl carboxylic acids (PFCAs), such as perfluorooctanoic acid (PFOA, C8), are a group of industrial chemicals that are detected in the serum of people throughout the world. Long-chain PFCAs (C9 to C13) have high lipophilicity, therefore they may have a high transfer rate to breast milk. This study investigated the lactational transfer of PFCAs with carbon chain lengths of 8 to 13 in mice. Lactating dams were given a single intravenous administration of PFCAs (C8 to C13) during the postnatal period (8–13 days after delivery). Milk was collected from the dam 24 h after administration using a milking device built in-house. Plasma was obtained from the dam at the same time as milk collection. The observed milk/plasma (M/P) concentration ratios were 0.32 for C8, 0.30 for C9, 0.17 for C10, 0.21 for C11, 0.32 for C12, and 0.49 for C13. These results indicate that the M/P concentration ratio is not related to the lipophilicity of PFCAs. However, estimated relative daily intake, an indicator of how much PFCA is transferred from dams to pups per body weight, increased with chain length: 4.16 for C8, 8.98 for C9, 9.35 for C10, 9.51 for C11, 10.20 for C12, and 10.49 for C13, which may be related to the lower clearance of long-chain PFCAs. These results indicate the importance of future risk assessment of long-chain PFCAs.

Cannabis use in pregnancy and breastfeeding: The pharmacist's role

Background

The recent legalization of cannabis use in Canada requires pharmacists to be able to support their patients with accurate knowledge of its known risks and benefits. Certain populations, such as pregnant and breastfeeding women and their developing children, may be at higher risk than other populations.

Methods

The authors independently searched the literature for clinical reports or reviews of the literature regarding the safety of cannabis use in pregnancy and breastfeeding using search terms such as cannabis, marijuana, pregnancy and breastfeeding.

Results

This review combines the relevant pharmacological, pharmacokinetic and clinical evidence for the effects of cannabis in this special patient population. The literature demonstrates that some of the constituents of cannabis can reach children in utero and through breastmilk. Given that Δ⁹-tetrahydrocannabinol can be present in breastmilk as quickly as 1 hour after consumption and last up to 6 days, it may not be possible to use cannabis and avoid infant exposure. There is evidence that this exposure may result in cognitive, social and motor defects. Some of these effects may be long term, lasting years. The pharmacist must be able to educate and screen patients regarding marijuana use in pregnancy and breastfeeding, with the ultimate aim of harm reduction.

Selenium status in lactating mothers-infants and its potential protective role against the neurotoxicity of methylmercury, lead, manganese, and DDT

A total of 206 lactating mothers and their infants (3-12 months) were included in this study to evaluate postnatal exposure to neurotoxic pollutants such as methylmercury (MeHg), lead (Pb), manganese (Mn), dichlorodiphenyltrichloroethane (DDT) and its metabolites [dichlorodiphenyldichloroethane (DDD), and dichlorodiphenyldichloroethylene (DDE)] and their association with delayed neurological development and to explore the protective role of selenium (Se) against chemical neurotoxicity. Neurodevelopmental performance was evaluated using Denver Developmental Screening Test II and Parents' Evaluation of Developmental Status (PEDS). Multivariate log-binomial regression modeling was applied for both single and multiple exposures to chemicals using a principal component analysis that generated six principal components. Both mothers and their infants had been exposed to metals and DDT metabolites, with some exceeding the accepted permissible limits. The geometric means of MeHg, Pb, Mn, DDD, DDE and DDT levels in breast milk were 1.333, 45.327, 15.576, 0.069, 0.542 and 1.08 μg/l, respectively. A single-exposure model identified a high risk of reduced PEDS performance significantly associated with DDD in breast milk [relative risk (RR) = 1.484; 95% confidence interval (95%CI) = 1.091-2.019] and marginally significantly associated with Pb in the mothers' blood (RR = 2.164; 95%CI = 0.87-5.382). We did not find a protective role of Se in neurodevelopment due to its high levels in the mothers. Models of multi-chemical exposure indicated that Mn in blood and breast milk, Se in blood and Pb in the mothers' urine were marginally significantly associated with a high risk of reduced PEDS performance (RR = 0.424; 95%CI = 0.176-1.022). The use of multi-chemical exposure approach in early life risk assessments is important because it indicates real-world exposure. Our results were not conclusive because the sample size was small, so future studies examining the implications to health of the impact of prenatal/postnatal exposure to a mixture of chemicals in the Saudi population are merited.

Risk-Benefit assessment of infant exposure to lithium through breast milk: a systematic review of the literature

The continuation of lithium while breastfeeding is a controversial topic, and clinical recommendations vary. A systematic review was completed of available data on lithium and breastfeeding to determine the degree of lithium exposure through breast milk and assess the potential risk to the infant. Databases, including PubMed MEDLINE, Embase, PsycINFO, Web of Science, Scopus, and Cochrane CENTRAL Register of Controlled Trials databases, were searched for articles on lithium and breastfeeding from the start dates of the databases through December 2018. Articles were included if the report included at least one maternal serum/plasma and/or breast milk lithium concentration and one infant serum/plasma lithium concentration. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Twelve articles, all case reports, were selected for inclusion out of 441 articles that were found and 230 that were reviewed from the search. Data are limited on the safety of lithium continuation while breastfeeding. Among the adverse effects reported, it is difficult to differentiate poor outcomes from factors affecting infant health, concomitant medications, and gestational lithium exposure. Recommendations on whether to continue lithium while breastfeeding must be personalized to the individual woman and her infant.

[Which medications are safe while breastfeeding? : A synopsis for the anesthetist, obstetrician and pediatrician]

Pharmacokinetic data on drug administration during lactation are often inconsistent or missing. For legal reasons medicinal drug product information generally advises to interrupt breastfeeding for 24 h after medication intake. However this is not standard of care in clinical practice as the mother should be instructed to initiate breastfeeding as soon as possible after giving birth. At the same time the medication exposure over the breast milk for the newborn should be minimized. Aim of this article is to summarize pharmacokinetic data and to give important clinical information on medications frequently administered during the lactation period. As a general rule a mother can start breastfeeding following anesthesia as soon as she is able to get her baby latched on her breast.

Modeling drug passage into human milk

Breastfeeding has positive health consequences for both the breastfed infant and the nursing mother.(1,2) Although information on drug use during lactation is available through sites such as LactMed,(3) available information is often incomplete. Unlike pregnancy, in which large numbers of pregnant women need to be studied to assure safety, measurement of drug concentrations in breastmilk in a relatively few subjects can provide valuable information to assess drug safety. This article reviews methods of measuring and predicting drug passage into breastmilk.

Recommendations for the treatment of migraine attacks - a Brazilian consensus

ABSTRACT In this article, a group of experts in headache management of the Brazilian Headache Society developed through a consensus strategic measurements to treat a migraine attack in both the child and the adult. Particular emphasis was laid on the treatment of migraine in women, including at pregnancy, lactation and perimenstrual period.

Maternal blood, plasma, and breast milk lead: lactational transfer and contribution to infant exposure

BACKGROUND

Human milk is a potential source of lead exposure. Yet lactational transfer of lead from maternal blood into breast milk and its contribution to infant lead burden remains poorly understood.

OBJECTIVES

We explored the dose-response relationships between maternal blood, plasma, and breast milk to better understand lactational transfer of lead from blood and plasma into milk and, ultimately, to the breastfeeding infant.

METHODS

We measured lead in 81 maternal blood, plasma, and breast milk samples at 1 month postpartum and in 60 infant blood samples at 3 months of age. Milk-to-plasma (M/P) lead ratios were calculated. Multivariate linear, piecewise, and generalized additive models were used to examine dose-response relationships between blood, plasma, and milk lead levels.

RESULTS

Maternal lead levels (mean±SD) were as follows: blood: 7.7±4.0 μg/dL; plasma: 0.1±0.1 μg/L; milk: 0.8±0.7 μg/L. The average M/P lead ratio was 7.7 (range, 0.6-39.8) with 97% of the ratios being >1. The dose-response relationship between plasma lead and M/P ratio was nonlinear (empirical distribution function=6.5, p=0.0006) with the M/P ratio decreasing by 16.6 and 0.6 per 0.1 μg/L of plasma lead, respectively, below and above 0.1 μg/L plasma lead. Infant blood lead level (3.4±2.2 μg/dL) increased by 1.8 μg/dL per 1 μg/L milk lead (p<0.0001, R2=0.3).

CONCLUSIONS

The M/P ratio for lead in humans is substantially higher than previously reported, and transfer of lead from plasma to milk may be higher at lower levels of plasma lead. Breast milk is an important determinant of lead burden among breastfeeding infants.

Prediction of drug disposition on the basis of its chemical structure

The chemical structure of any drug determines its pharmacokinetics and pharmacodynamics. Detailed understanding of relationships between the drug chemical structure and individual disposition pathways (i.e., distribution and elimination) is required for efficient use of existing drugs and effective development of new drugs. Different approaches have been developed for this purpose, ranging from statistics-based quantitative structure-property (or structure-pharmacokinetic) relationships (QSPR) analysis to physiologically based pharmacokinetic (PBPK) models. This review critically analyzes currently available approaches for analysis and prediction of drug disposition on the basis of chemical structure. Models that can be used to predict different aspects of disposition are presented, including: (a) value of the individual pharmacokinetic parameter (e.g., clearance or volume of distribution), (b) efficiency of the specific disposition pathway (e.g., biliary drug excretion or cytochrome P450 3A4 metabolism), (c) accumulation in a specific organ or tissue (e.g., permeability of the placenta or accumulation in the brain), and (d) the whole-body disposition in the individual patients. Examples of presented pharmacological agents include "classical" low-molecular-weight compounds, biopharmaceuticals, and drugs encapsulated in specialized drug-delivery systems. The clinical efficiency of agents from all these groups can be suboptimal, because of inefficient permeability of the drug to the site of action and/or excessive accumulation in other organs and tissues. Therefore, robust and reliable approaches for chemical structure-based prediction of drug disposition are required to overcome these limitations. PBPK models are increasingly being used for prediction of drug disposition. These models can reflect the complex interplay of factors that determine drug disposition in a mechanistically correct fashion and can be combined with other approaches, for example QSPR-based prediction of drug permeability and metabolism, pharmacogenomic data and tools, pharmacokinetic-pharmacodynamic modeling approaches, etc. Moreover, the PBPK models enable detailed analysis of clinically relevant scenarios, for example the effect of the specific conditions on the time course of the analyzed drug in the individual organs and tissues, including the site of action. It is expected that further development of such combined approaches will increase their precision, enhance the effectiveness of drugs, and lead to individualized drug therapy for different patient populations (geriatric, pediatric, specific diseases, etc.).

Absence of infliximab in infants and breast milk from nursing mothers receiving therapy for Crohn's disease before and after delivery

GOALS

The objective of this study was to determine whether infliximab, an antitumor necrosis factor monoclonal antibody, is transferred in utero or through breast milk from nursing Crohn's disease patients to their newborns.

BACKGROUND

Crohn's disease most often occurs in women of childbearing age. Many of these women receive treatment for their disease, but are advised to terminate therapy while pregnant or nursing.

STUDY

Three patients diagnosed with Crohn's disease who had a history of infliximab use during and after pregnancy were followed prospectively. Patients received 5-mg/kg infliximab at regular intervals until approximately gestational week 30, and resumed infliximab treatment within 3 to 14 days after giving birth. Serum samples from patients and children and breast milk samples were collected postpartum. The concentration of infliximab in the serum and milk samples was measured using an enzyme-linked immmunosorbent assay.

RESULTS

The levels of infliximab detected in the mothers' serum samples postpartum were 74.27, 62.62, and 59.97 microg/mL, respectively. However, infliximab was undetectable (<0.10 microg/mL) in the sera of the newborn children. Likewise, infliximab was undetectable in the breast milk of the nursing mothers.

CONCLUSIONS

Infliximab was detected in the mothers' sera, but not in the breast milk of nursing mothers or in the sera of the breast-fed newborns. Data from this small series of patients suggest that infliximab was not transferred from mother to child, either in utero or through breast milk. These data suggest that mothers receiving infliximab should not be discouraged from nursing their children.

Absence of infliximab in infants and breast milk from nursing mothers receiving therapy for Crohn's disease before and after delivery

GOALS

The objective of this study was to determine whether infliximab, an antitumor necrosis factor monoclonal antibody, is transferred in utero or through breast milk from nursing Crohn's disease patients to their newborns.

BACKGROUND

Crohn's disease most often occurs in women of childbearing age. Many of these women receive treatment for their disease, but are advised to terminate therapy while pregnant or nursing.

STUDY

Three patients diagnosed with Crohn's disease who had a history of infliximab use during and after pregnancy were followed prospectively. Patients received 5-mg/kg infliximab at regular intervals until approximately gestational week 30, and resumed infliximab treatment within 3 to 14 days after giving birth. Serum samples from patients and children and breast milk samples were collected postpartum. The concentration of infliximab in the serum and milk samples was measured using an enzyme-linked immmunosorbent assay.

RESULTS

The levels of infliximab detected in the mothers' serum samples postpartum were 74.27, 62.62, and 59.97 microg/mL, respectively. However, infliximab was undetectable (<0.10 microg/mL) in the sera of the newborn children. Likewise, infliximab was undetectable in the breast milk of the nursing mothers.

CONCLUSIONS

Infliximab was detected in the mothers' sera, but not in the breast milk of nursing mothers or in the sera of the breast-fed newborns. Data from this small series of patients suggest that infliximab was not transferred from mother to child, either in utero or through breast milk. These data suggest that mothers receiving infliximab should not be discouraged from nursing their children.

Computational chemistry development of a unified free energy Markov model for the distribution of 1300 chemicals to 38 different environmental or biological systems

Predicting tissue and environmental distribution of chemicals is of major importance for environmental and life sciences. Most of the molecular descriptors used in computational prediction of chemicals partition behavior consider molecular structure but ignore the nature of the partition system. Consequently, computational models derived up-to-date are restricted to the specific system under study. Here, a free energy-based descriptor (DeltaG(k)) is introduced, which circumvent this problem. Based on DeltaG(k), we developed for the first time a single linear classification model to predict the partition behavior of a broad number of structurally diverse drugs and other chemicals (1300) for 38 different partition systems of biological and environmental significance. The model presented training/predicting set accuracies of 91.79/88.92%. Parametrical assumptions were checked. Desirability analysis was used to explore the levels of the predictors that produce the most desirable partition properties. Finally, inversion of the partition direction for each one of the 38 partition systems evidences that our models correctly classified 89.08% of compounds with an uncertainty of only +/-0.17% independently of the direction of the partition process used to seek the model. Other 10 different classification models (linear, neural networks, and genetic algorithms) were also tested for the same purposes. None of these computational models favorably compare with respect to the linear model indicating that our approach capture the main aspects that govern chemicals partition in different systems.

SSRIs during breastfeeding: spotlight on milk-to-plasma ratio

OBJECTIVE

To investigate the usefulness of the milk-to-plasma (M/P) ratio for assessing the risks for the breastfed infant associated with the maternal use of SSRIs.

DATA SOURCES

Medline, Toxnet, Embase, Current Contents, and PsycInfo indexed articles from 1980 to September 2006.

STUDY SELECTION AND DATA EXTRACTION

All studies reporting the M/P ratio in mothers taking SSRIs while breastfeeding or studies which such an information could be calculated from data reported in the article.

DATA SYNTHESIS

Higher M/P ratios were rarely associated with a clinically significant impact on the babies during the early phases of breastfeeding.

CONCLUSIONS

So far no evidence-based information seems to support the hypothesis that SSRIs characterized by a M/P ratio <1.0 should be preferred. Hence, physicians should consider different parameters when attempting to choose the safest SSRI for the breastfeeding woman. These parameters might be represented by the number of well-documented published adverse event reports and the tendency of each SSRI of inducing in the infants serum concentrations that are elevated above 10% of average maternal serum levels. In any case, if the mother wishes to breastfeed her infant while taking a SSRI, the baby should be closely monitored in order to promptly detect any iatrogenic event.

Using pharmacokinetics to predict the effects of pregnancy and maternal-infant transfer of drugs during lactation

Knowledge of pharmacokinetics and the use of a mechanistic-based approach can improve our ability to predict the effects of pregnancy for medications when data are limited. Despite the many physiological changes that occur during pregnancy that could theoretically affect absorption, bioavailability does not appear to be altered. Decreased albumin and alpha(1)-acid glycoprotein concentrations during pregnancy will result in decreased protein binding for highly bound drugs. For drugs metabolised by the liver, this can result in misinterpretation of total plasma concentrations of low extraction ratio drugs and overdosing of high extraction ratio drugs administered by non-oral routes. Renal clearance and the activity of the CYP isozymes, CYP3A4, 2D6 and 2C9, and uridine 5'-diphosphate glucuronosyltransferase are increased during pregnancy. In contrast, CYP1A2 and 2C19 activity is decreased. The dose of a drug an infant receives during breastfeeding is dependent on the amount excreted into the breast milk, the daily volume of milk ingested and the average plasma concentration of the mother. The lipophilicity, protein binding and ionisation properties of a drug will determine how much is excreted into the breast milk. The milk to plasma concentration ratio has large inter- and intrasubject variability and is often not known. In contrast, protein binding is usually known. An extensive literature review was done to identify case reports including infant concentrations from breast-fed infants exposed to maternal drugs. For drugs that were at least 85% protein bound, measurable concentrations of drug in the infant did not occur if there was no placental exposure immediately prior to or during delivery. Knowledge of the protein binding properties of a drug can provide a quick and easy tool to estimate exposure of an infant to medication from breastfeeding.

Toxicology: Then and now

Toxicology is "the science of poisons"; more specifically the chemical and physical properties of poisons, their physiological or behavioral effects on living organisms, qualitative, and quantitative methods for their analysis and the development of procedures for the treatment of poisoning. Although the history of poisons dates to the earliest times, the study and the science of toxicology can be traced to Paracelsus (1493-1541) and Orfila (1757-1853). Modern toxicology is characterized by sophisticated scientific investigation and evaluation of toxic exposures. The 20th century is marked by an advanced level of understanding of toxicology. DNA and various biochemicals that maintain cellular functions were discovered. Our level of knowledge of toxic effects on organs and cells is now being revealed at the molecular level. This paper will review the historical progress of clinical and forensic toxicology by exploring analytical techniques in drug analysis, differing biological matrices, clinical toxicology, therapeutic drug management, workplace drug testing, and pharmacodynamic monitoring and pharmacogenetics.

Individualized drug and dose: The clinical pharmacologist's calling or curse?

1. The role of the clinical pharmacologist is to promote the rational, safe and effective use of medicines. This revolves around the notion of variability, between and within patients and between and within drugs, in terms of both pharmacokinetics and pharmacodynamics. Ideal therapeutics involves tailoring the drug and its dosing to the individual patient, taking into account this variability. 2. In the 25 years of my membership of the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists, three themes have dominated my research: (i) drugs and breast feeding; (ii) aminoglycoside dosing; and (iii) pharmacogenetics. In all these, the research has been orientated towards identifying factors involved in variability and working towards dose individualization based on the understanding of these factors. 3. Our model for predicting drug concentrations in milk has assisted not only in estimating the safety of drug ingestion via breast milk, but also in the understanding of the processes involved in drug transfer. 4. The aminoglycoside studies have assisted in the understanding of the basis behind extended interval dosing, leading to a model for dose prediction that is widely used, especially in Australasia. 5. Pharmacogenetics is a field widely acclaimed as having a huge future in terms of individualization of drug therapy. Our early studies in this area lend only cautious support to this optimism.

Pharmacokinetics of tenofovir in breast milk of lactating rhesus macaques

To study tenofovir transfer into milk, two lactating macaques were given a subcutaneous dose of tenofovir (30 mg/kg of body weight). Peak concentrations and area under the curve values of tenofovir in milk were approximately 3 and approximately 20% of those detected in serum, respectively.