Introduction Ophthalmic drug product development and dosing regimen selection depend on animal eye drug concentration-effect relationships since human eye tissues cannot be sampled for drug quantification. This study hypothesized that a pharmacokinetic-pharmacodynamic (PK-PD) mathematical model developed based on dog studies can be applied to the human eye of different ages, based on physiological parameter adjustment, to predict drug concentrations and effects in response to a new 6-month slow-release, intracameral, intraocular pressure (IOP) lowering, anti-glaucoma bimatoprost implant. Methods Using previously reported dog concentration-effect relationship data at various doses, and the physiological parameters of dog eye, a PK-PD model was designed to predict dog aqueous humor drug concentrations and IOP lowering effects simultaneously for a given dose. After validating the model using the dog IOP data, it was applied to the human eye. Results Using a drug release rate constant of 0.0002 h−1, the model predicted the dog IOP lowering effect with an error less than 6% or less at various doses (Observed = 0.91*Predicted + 2.35; R2 = 0.98). Considering literature reported aqueous humor volumes and flow rates in old (over 60 years) and young (20 to 30 years) humans, aqueous humor elimination rate constant was estimated to be 0.9 and 0.68 h−1, respectively. The model when modified using the older human eye parameters, predicted the IOP lowering effects reported in a clinical trial with 63-year-old adults, with an error of 6.2% or less. The model, when used for young adult eye not previously tested in clinical trials, predicted lower drug concentrations and effects, possibly due to 54% higher aqueous humor volume relative to older adults. The model predicted an IOP reduction of 26.3 and 30.6%, at 10 and 15 microgram doses, respectively, in young adults. Conclusions The PK-PD model developed is useful for product design and patient dosing by predicting eye drug concentration and effect time-courses in response to implant administration at various doses, frequencies, and release rates.
Purpose Monoclonal antibodies target a single epitope or region in an antigen for therapeutic purposes. Given the highly mutant nature of SARS-COV-2 or coronavirus, it is likely that a cocktail of antibodies or a polyclonal antibody targeting multiple regions of the virus might be more beneficial in treating COVID-19. The purpose of this project, based on the reported clinical evaluation of XAV-19 polyclonal antibody in pneumonia patients, is to develop a pharmacokinetic-pharmacodynamic (PK-PD) model to explain the relationship between drug concentrations and reduction in the nasopharyngeal viral load. Methods: The concentration of the drug in a time course was related to the effect at each time point to determine the PK-PD relationship. Using Berkeley-Madonna, a PK-PD mathematical model including a central serum compartment, a peripheral effect compartment, and an Emax model for drug effects was developed to explain the observed drug concentrations and effects. Using published EC50 concentrations for XAV-19 and various variants of SARS-CoV-2, the time course of drug effect was predicted for the virus variants including D614G, alpha, beta, gamma, and delta. Results: The results indicated a counterclockwise hysteresis loop for the PK-PD relationship, suggesting lower effects at the same concentration initially, followed by greater effects at the same concentration later. This is consistent with separation of the effect compartment from the serum compartment, where concentrations are measured. The model explained the observed data well. Conclusion: The PK-PD model is useful in predicting dose-response relationships for the new polyclonal antibody. Further, it can be extended to other emerging variants of the coronavirus.
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