Carrie German

Topical drug administration is a common method of delivering medications to the eye to treat various ocular conditions, including glaucoma, dry eye, and inflammation. Drug efficacy following topical administration, including the drug’s distribution within the eye, absorption and elimination rates, and physiological responses can be predicted using physiologically based pharmacokinetic (PBPK) modeling. High-resolution computational models of the eye are desirable to improve simulations of drug delivery; however, these approaches can have long run times. In this study, a fast-running computational quasi-3D (Q3D) model of the human tear film was developed to account for absorption, blinking, drainage, and evaporation. Visualization of blinking mechanics and flow distributions throughout the tear film were enabled using this Q3D approach. Average drug absorption throughout the tear film subregions was quantified using a high-resolution compartment model based on a system of ordinary differential equations (ODEs). Simulations were validated by comparing them with experimental data from topical administration of 0.1% dexamethasone suspension in the tear film (R² = 0.76, RMSE = 8.7, AARD = 28.8%). Overall, the Q3D tear film model accounts for critical mechanistic factors (e.g., blinking and drainage) not previously included in fast-running models. Further, this work demonstrated methods toward improved computational efficiency, where central processing unit (CPU) time was decreased while maintaining accuracy. Building upon this work, this Q3D approach applied to the tear film will allow for more seamless integration into full-body models, which will be an extremely valuable tool in the development of treatments for ocular conditions.

The administration of therapeutic drugs through dermal routes, such as creams and ointments, has emerged as an increasingly popular alternative to traditional delivery methods, such as tablets and injections. In the context of drug development, it is crucial to identify the optimal doses and delivery routes that ensure successful outcomes. Physiologically based pharmacokinetic (PBPK) models have been proposed to simulate drug delivery and optimize drug formulations, but the calibration of these models is challenging due to the multitude of variables involved and limited experimental data. One significant research gap that this article addresses is the need for more efficient and accurate methods for calibrating PBPK models for dermal drug delivery. This manuscript presents a novel approach and an integrated dermal drug delivery model to address this gap that leverages virtual in vitro release (IVRT) and permeation (IVPT) testing data to optimize mechanistic models. The proposed approach was demonstrated through a study involving Desoximetasone cream and ointment formulations, where the release kinetics and permeation profiles of Desoximetasone were determined experimentally, and a computational model was created to simulate the results. The experimental studies showed that, even though the cumulative permeation of Desoximetasone at the end of the permeation study was comparable, there was a significant difference seen in the lag time in the permeation of Desoximetasone between the cream and ointment. Additionally, there was a significant difference seen in the amount of Desoximetasone permeated through human cadaver skin at early time points when the cream and ointment were compared. The computational model was optimized and validated, suggesting that this approach has the potential to bridge the existing research gap by improving the accuracy and efficiency of drug development processes. The model results show a good fit between the experimental data and model predictions. During the model optimization process, it became evident that there was variability in both the permeability and the partition coefficient within the stratum corneum. This variability had a significant and noteworthy influence on the overall performance of the model, especially when it came to its capacity to differentiate between cream and ointment formulations. Leveraging virtual models significantly aids the comprehension of drug release and permeation, mitigating the demanding data requirements. The use of virtual IVRT and IVPT data can accelerate the calibration of PBPK models, streamline the selection of the appropriate doses, and optimize drug delivery. Moreover, this novel approach could potentially reduce the time and resources involved in drug development, thus making it more cost-effective and efficient.

Quercetin is a polyphenol of the flavonoid class of secondary metabolites that is widely distributed in the plant kingdom. Quercetin has been found to exhibit potent bioactivity in the areas of wound healing, neuroprotection, and anti-aging research. Naturally found in highly glycosylated forms, aglycone quercetin has low solubility in aqueous environments, which has heavily limited its clinical applications. To improve the stability and bioavailability of quercetin, efforts have been made to chemically modify quercetin and related flavonoids so as to improve aqueous solubility while retaining bioactivity. In this review, we provide an updated overview of the biological properties of quercetin and proposed mechanisms of actions in the context of wound healing and aging. We also provide a description of recent developments in synthetic approaches to improve the solubility and stability of quercetin and related analogs for therapeutic applications. Further research in these areas is expected to enable translational applications to improve ocular wound healing and tissue repair.

Introduction Although the eye is directly accessible on the surface of the human body, drug delivery can be extremely challenging due to the presence of multiple protective barriers in eye tissues. Researchers have developed complex formulation strategies to overcome these barriers to ophthalmic drug delivery. Current development strategies rely heavily on in vitro experiments and animal testing to predict human pharmacokinetics (PK) and pharmacodynamics (PD). Objective The primary objective of the study was to develop a high-fidelity PK/PD model of the anterior eye for topical application of ophthalmic drug products. Methods Here, we present a physiologically-based in silico approach to predicting PK and PD in rabbits after topical administration of ophthalmic products. A first-principles based approach was used to describe timolol dissolution, transport, and distribution, including consideration of ionized transport, following topical instillation of a timolol suspension. Results Using literature transport and response parameters, the computational model described well the concentration–time and response-time profiles in rabbit. Comparison of validated rabbit model results and extrapolated human model results demonstrate observable differences in the distribution of timolol at multiple time points. Conclusion This modeling framework provides a tool for model-based prediction of PK in eye tissues and PD after topical ophthalmic drug administration to the eyes.

The primary goal of this work was to develop a computational tool to enable personalized prediction of pharmacological disposition and associated responses for opioids and antidotes. Here we present a computational framework for physiologically-based pharmacokinetic (PBPK) modeling of an opioid (morphine) and an antidote (naloxone). At present, the model is solely personalized according to an individual’s mass. These PK models are integrated with a minimal pharmacodynamic model of respiratory depression induction (associated with opioid administration) and reversal (associated with antidote administration). The model was developed and validated on human data for IV administration of morphine and naloxone. The model can be further extended to consider different routes of administration, as well as to study different combinations of opioid receptor agonists and antagonists. This work provides the framework for a tool that could be used in model-based management of pain, pharmacological treatment of opioid addiction, appropriate use of antidotes for opioid overdose and evaluation of abuse deterrent formulations.