Hyo-Jeong Ryu

Botulinum neurotoxins (BoNTs) are commonly used in therapeutic and cosmetic applications. One such neurotoxin, BoNT type A (BoNT/A), has been studied widely for its effects on muscle function and contraction. Despite the importance of BoNT/A products, determining the blood concentrations of these toxins can be challenging. To address this, researchers have focused on pharmacodynamic (PD) markers, including compound muscle action potential (CMAP) and digit abduction scoring (DAS). In this study, we aimed to develop a probabilistic kinetic‐pharmacodynamic (K‐PD) model to interpret CMAP and DAS data obtained from mice and rats during the development of BoNT/A products. The researchers also wanted to gain a better understanding of how the estimated parameters from the model relate to the bridging of animal models to human responses. We used female Institute of Cancer Research mice and Sprague‐Dawley (SD) rats to measure CMAP and DAS levels over 32 weeks after administering BoNT/A. We developed a muscle‐contraction inhibition model using a virtual pharmacokinetic (PK) compartment combined with an indirect response model and performed model diagnostics using goodness‐of‐fit analysis, visual predictive checks (VPC), and bootstrap analysis. The CMAP and DAS profiles were dose‐dependent, with recovery times varying depending on the administered dose. The final K‐PD model effectively characterized the data and provided insights into species‐specific differences in the PK and PD parameters. Overall, this study demonstrated the utility of PK‐PD modeling in understanding the effects of BoNT/A and provides a foundation for future research on other BoNT/A products.

Compartment modeling is a widely accepted technique in the field of pharmacokinetic analysis. However, conventional compartment modeling is performed under a homogeneity assumption that is not a naturally occurring condition. Since the assumption lacks physiological considerations, the respective modeling approach has been questioned, as novel drugs are increasingly characterized by physiological or physical features. Alternative approaches have focused on fractal kinetics, but evaluations of their application are lacking. Thus, in this study, a simulation was performed to identify desirable fractal-kinetics applications in conventional modeling. Visible changes in the profiles were then investigated. Five cases of finalized population models were collected for implementation. For model diagnosis, the objective function value (OFV), Akaike’s information criterion (AIC), and corrected Akaike’s information criterion (AICc) were used as performance metrics, and the goodness of fit (GOF), visual predictive check (VPC), and normalized prediction distribution error (NPDE) were used as visual diagnostics. In most cases, model performance was enhanced by the fractal rate, as shown in a simulation study. The necessary parameters of the fractal rate in the model varied and were successfully estimated between 0 and 1. GOF, VPC, and NPDE diagnostics show that models with the fractal rate described the data well and were robust. In the simulation study, the fractal absorption process was, therefore, chosen for testing. In the estimation study, the rate application yielded improved performance and good prediction–observation agreement in early sampling points, and did not cause a large shift in the original estimation results. Thus, the fractal rate yielded explainable parameters by setting only the heterogeneity exponent, which reflects true physiological behavior well. This approach can be expected to provide useful insights in pharmacological decision making.

MT921 is a new injectable drug developed by Medytox Inc. to reduce submental fat. Cholic acid is the active pharmaceutical ingredient, a primary bile acid biosynthesized from cholesterol, endogenously produced by liver in humans and other mammals. Although individuals treated with MT921 could be administered with multiple medications, such as those for hypertension, diabetes, and hyperlipidemia, the pharmacokinetic drug–drug interaction (DDI) has not been investigated yet. Therefore, we studied in vitro against drug-metabolizing enzymes and transporters. Moreover, we predicted the potential DDI between MT921 and drugs for chronic diseases using physiologically-based pharmacokinetic (PBPK) modeling and simulation. The magnitude of DDI was found to be negligible in in vitro inhibition and induction of cytochrome P450s and UDP-glucuronosyltransferases. Organic anion transporting polypeptide (OATP)1B3, organic anion transporter (OAT)3, Na⁺-taurocholate cotransporting polypeptide (NTCP), and apical sodium-dependent bile acid transporter (ASBT) are mainly involved in MT921 transport. Based on the result of in vitro experiments, the PBPK model of MT921 was developed and evaluated by clinical data. Furthermore, the PBPK model of amlodipine was developed and evaluated. PBPK DDI simulation results indicated that the pharmacokinetics of MT921 was not affected by the perpetrator drugs. In conclusion, MT921 could be administered without a DDI risk based on in vitro study and related in silico simulation. Further clinical studies are needed to validate this finding.

Dermal fillers are gel-type substances for nonsurgical medical-device use to achieve facial rejuvenation. Currently, the most widely used skin fillers are hyaluronic-acid-based dermal fillers. This study aimed to explain the change in the volume of injected dermal fillers by developing a mathematical kinetic model for various dermal fillers. The kinetics of the injected fillers were separated by a biphasic phenomenon. We attributed an increase in filler volume to the hydration of hyaluronic acid molecules and injection-site reaction and a decrease in volume to enzyme-mediated degradation. To explain these in vivo characteristics of dermal fillers, we proposed a two-compartment model, divided into a depot compartment (where the filler was injected) and a subcutaneous compartment (an observation compartment where the fillers swell and degrade), assuming that the swelling and degradation occurred in accordance with the swelling and degradation rate constants, respectively. The model was developed using five hyaluronic-acid-based dermal fillers and NONMEM. We determined that the rate-limiting step for the complete degradation of the dermal fillers in vivo was the swelling phase, as described by the swelling rate constant (K_swell). This study could enable scientists developing novel dermal fillers to predict the in vivo behavior of fillers.