A limited sampling method for the estimation of AUC and Cmax of carbamazepine and carbamazepine epoxide following a single and multiple dose of a sustained-release product

Safety of drug use in patients with a primary mitochondrial disease: An international Delphi-based consensus

Clinical guidance is often sought when prescribing drugs for patients with primary mitochondrial disease. Theoretical considerations concerning drug safety in patients with mitochondrial disease may lead to unnecessary withholding of a drug in a situation of clinical need. The aim of this study was to develop consensus on safe medication use in patients with a primary mitochondrial disease. A panel of 16 experts in mitochondrial medicine, pharmacology, and basic science from six different countries was established. A modified Delphi technique was used to allow the panellists to consider draft recommendations anonymously in two Delphi rounds with predetermined levels of agreement. This process was supported by a review of the available literature and a consensus conference that included the panellists and representatives of patient advocacy groups. A high level of consensus was reached regarding the safety of all 46 reviewed drugs, with the knowledge that the risk of adverse events is influenced both by individual patient risk factors and choice of drug or drug class. This paper details the consensus guidelines of an expert panel and provides an important update of previously established guidelines in safe medication use in patients with primary mitochondrial disease. Specific drugs, drug groups, and clinical or genetic conditions are described separately as they require special attention. It is important to emphasise that consensus-based information is useful to provide guidance, but that decisions related to drug prescribing should always be tailored to the specific needs and risks of each individual patient. We aim to present what is current knowledge and plan to update this regularly both to include new drugs and to review those currently included.

Model-Based Evaluation of Linear Limited and Bayesian Sparse Sampling for Therapeutic Monitoring of Recombinant Coagulation Factor IX

Dosing of coagulation factor products is mainly determined based on a patient's body weight; however, several studies have reported high interindividual variability in their pharmacokinetics (PK). The objective of this study was to develop and evaluate 2 sparse sampling methods for the estimation of AUC of recombinant factor IX (BeneFIX) as proof of concept for dose individualization. A population pharmacokinetic model was used to generate the plasma factor IX activity-versus-time data. The linear limited sampling model (LLSM) was developed based on the correlation of factor IX activity versus AUC_0-72 hours following screening of several blood sampling times in adolescent and adult subjects (n = 90 subjects). Factor IX trough concentrations were predicted from a relationship established from AUC versus factor IX activity measured 72 hours postdosing. Using the best selected sampling time, the LLSM and Bayesian model were validated in separate data sets (n = 75 subjects). Using the LLSM and Bayesian analysis, a blood sample at 24 hours predicted AUC with bias and root mean square error < 5% and < 15%, respectively. The predicted trough concentrations were ≥1 IU/dL in 99% and 100% of subjects by the LLSM and Bayesian model, respectively. The average factor IX dose for a target AUC of 800 IU·h/dL was 61, 60, and 63 IU/kg using the extensive (reference), LLSM and Bayesian model, respectively. Overall, the AUC, trough concentrations and individualized dosing of recombinant factor IX could be reasonably predicted using the LLSM and Bayesian model.

Establishment and assessment of a new human embryonic stem cell-based biomarker assay for developmental toxicity screening

A metabolic biomarker-based in vitro assay utilizing human embryonic stem (hES) cells was developed to identify the concentration of test compounds that perturbs cellular metabolism in a manner indicative of teratogenicity. This assay is designed to aid the early discovery-phase detection of potential human developmental toxicants. In this study, metabolomic data from hES cell culture media were used to assess potential biomarkers for development of a rapid in vitro teratogenicity assay. hES cells were treated with pharmaceuticals of known human teratogenicity at a concentration equivalent to their published human peak therapeutic plasma concentration. Two metabolite biomarkers (ornithine and cystine) were identified as indicators of developmental toxicity. A targeted exposure-based biomarker assay using these metabolites, along with a cytotoxicity endpoint, was then developed using a 9-point dose-response curve. The predictivity of the new assay was evaluated using a separate set of test compounds. To illustrate how the assay could be applied to compounds of unknown potential for developmental toxicity, an additional 10 compounds were evaluated that do not have data on human exposure during pregnancy, but have shown positive results in animal developmental toxicity studies. The new assay identified the potential developmental toxicants in the test set with 77% accuracy (57% sensitivity, 100% specificity). The assay had a high concordance (≥75%) with existing in vivo models, demonstrating that the new assay can predict the developmental toxicity potential of new compounds as part of discovery phase testing and provide a signal as to the likely outcome of required in vivo tests.

Induction of hepatic cytochrome P450 enzymes: methods, mechanisms, recommendations, and in vitro-in vivo correlations

Induction of drug-clearance pathways (Phase 1 and 2 enzymes and transporters) can have important clinical consequences. Inducers can (1) increase the clearance of other drugs, resulting in a decreased therapeutic effect, (2) increase the activation of pro-drugs, causing an alteration in their efficacy and pharmacokinetics, and (3) increase the bioactivation of drugs that contribute to hepatotoxicity via reactive intermediates. Nuclear receptors are key mediators of drug-induced changes in the expression of drug-clearance pathways. However, species differences in nuclear receptor activation make the prediction of cytochrome P450 (CYP) induction in humans from data derived from animal models problematic. Thus, in vitro human-relevant model systems are increasingly used to evaluate enzyme induction. In this review, the authors' current understanding of the mechanisms of enzyme induction and the in vitro methods for assessing the induction potential of new drugs will be discussed. Relevant issues and considerations surrounding proper study design and the interpretation of in vitro results will be discussed in light of the current US Food and Drug Administration (FDA) recommendations.

A Bayesian approach for the estimation of pharmacokinetic parameters in children

A Bayesian method is proposed for the first-time assessment of pharmacokinetic parameters (area under the curve [AUC], maximum concentration [C(max)], half-life [T(1/2)]) in children after a single oral dose. Pharmacokinetic parameters were compared using sparse sampling (three blood samples) with extensive sampling (nine blood samples). Two different therapeutic classes of drugs were evaluated in this study. The population pharmacokinetic parameters and the blood sampling time points were obtained from adult data. The results indicate that the Bayesian approach can be used to estimate pharmacokinetic parameters in children with fair degree of accuracy. The Bayesian method described here can be used to assess pharmacokinetic parameters in children, provided there is a prior knowledge of the pharmacokinetics of a drug in adult population.

Limited sampling model for the estimation of pharmacokinetic parameters in children

A limited sampling model (LSM) is proposed for the first-time assessment of pharmacokinetic parameters (area under the concentration-time curve (AUC), Cmax, and T1/2) in children after a single oral dose of drug. Three drugs were evaluated in this study. The LSM was developed for each drug from the data of 10 healthy adult volunteers. The relationship at selected time points between plasma concentration and the AUC or Cmax was evaluated by multiple linear regression. The multiple linear regression that gave the best correlation coefficient (r) for 3 sampling times versus AUC or Cmax was chosen as the LSM. Pharmacokinetic parameters generated using sparse sampling (3 blood samples) were compared with pharmacokinetic parameters generated using extensive sampling (>7 blood samples). The results indicated that a limited sampling model can be developed from adult data to estimate pharmacokinetic parameters in children with fair degree of accuracy.