Physiologically Based Pharmacokinetic Modeling of Transdermal Selegiline and Its Metabolites for the Evaluation of Disposition Differences between Healthy and Special Populations

Abstract

A physiologically based pharmacokinetic (PBPK) model of selegiline (SEL), and its metabolites, was developed in silico to evaluate the disposition differences between healthy and special populations. SEL is metabolized to methamphetamine (MAP) and desmethyl selegiline (DMS) by several CYP enzymes. CYP2D6 metabolizes the conversion of MAP to amphetamine (AMP), while CYP2B6 and CYP3A4 predominantly mediate the conversion of DMS to AMP. The overall prediction error in simulated PK, using the developed PBPK model, was within 0.5–1.5-fold after intravenous and transdermal dosing in healthy and elderly populations. Simulation results generated in the special populations demonstrated that a decrease in cardiac output is a potential covariate that affects the SEL exposure in renally impaired (RI) and hepatic impaired (HI) subjects. A decrease in CYP2D6 levels increased the systemic exposure of MAP. DMS exposure increased due to a reduction in the abundance of CYP2B6 and CYP3A4 in RI and HI subjects. In addition, an increase in the exposure of the primary metabolites decreased the exposure of AMP. No significant difference between the adult and adolescent populations, in terms of PK, were observed. The current PBPK model predictions indicate that subjects with HI or RI may require closer clinical monitoring to identify any untoward effects associated with the administration of transdermal SEL patch.

Physiologically‐based pharmacokinetic modeling to support bioequivalence and approval of generic products: A case for diclofenac sodium topical gel, 1%

“…The "2-fold" criterion on mC max and AUC was referenced in this case for performance assessment of the dermal PBPK models developed for diclofenac sodium topical drug products and of dermal PBPK models developed for drug products supporting platform performance assessment. 24,[40][41][42][43] Overall, a good agreement between the predicted and observed PK profiles was observed (i.e., the overall shape of the PK profile, model-predicted absorption phase, and prediction of the time at C max [T max ] value were deemed satisfactory). Additional considerations on the acceptance criteria included the quality of the data used for building and assessing the performance of the model, the credibility of the model assumptions, the regulatory impact of the decision associated with the model, and the level of confidence on the overall modeling approach.…”

“…Currently, there are no established or formally recognized acceptance criteria for adequate model performance by the Agency. The “2‐fold” criterion on mC max and AUC was referenced in this case for performance assessment of the dermal PBPK models developed for diclofenac sodium topical drug products and of dermal PBPK models developed for drug products supporting platform performance assessment 24,40–43 . Overall, a good agreement between the predicted and observed PK profiles was observed (i.e., the overall shape of the PK profile, model‐predicted absorption phase, and prediction of the time at C max [T max ] value were deemed satisfactory).…”

“…Therefore, for these products, PBPK models can be leveraged to predict local drug exposure by integrating knowledge on the characterization of a drug product, the physiology or pathophysiology at or near the site of action, and the population information of healthy volunteers or patients receiving the drug product and to establish a link with systemic exposure if measurable. 20,21,23,24 This report summarizes the approval of an Abbreviated New Drug Application (ANDA) for a generic diclofenac sodium topical gel, 1% (referencing Voltaren topical gel, 1%), where for the first time a VBE assessment leveraging dermal PBPK modeling and simulation supported by a totality of evidence approach resulted in approval of the ANDA and discusses the lessons learned from this submission.…”

“…For locally acting drug products, including those applied on the skin, although administered at or close to the site of action, quantification of active ingredient amounts at the site of action for BE assessments is often not feasible. Therefore, for these products, PBPK models can be leveraged to predict local drug exposure by integrating knowledge on the characterization of a drug product, the physiology or pathophysiology at or near the site of action, and the population information of healthy volunteers or patients receiving the drug product and to establish a link with systemic exposure if measurable 20,21,23,24 …”

Skin-on-a-Chip Technology for Testing Transdermal Drug Delivery—Starting Points and Recent Developments

“…On the other hand, the in silico methods are often supported by strong in vitro data and can provide timely results, bringing down costs and the need for extensive biological studies. The in vivo testing can be limited and a large proportion of the required criteria can be planned and met in silico [66,67].…”