Plasma Concentration-time Profiles Research Articles

A pharmacokinetic-pharmacodynamic (PKPD) model-based analysis of tedizolid against enterococci using the hollow-fibre infection model

Tedizolid is a novel oxazolidinone antibiotic. Considering the higher antibacterial effect in immunocompetent compared with immunosuppressed animals, it is not recommended in immunocompromised patients. In this study, we assessed the 'pure' pharmacokinetic-pharmacodynamic (PKPD) relationship for tedizolid against Enterococcus in the hollow-fibre infection model (HFIM). Unbound plasma concentration time profiles (200-5000 mg/day IV) were simulated in the HFIM over 120 h against an Enterococcus faecalis strain and two clinical isolates of Enterococcus faecium (VRE-vanB and VRE-vanA). Next, a PKPD model describing tedizolid efficacy against bacterial isolates was developed. A population PK model was linked to the developed PKPD model and utilized to predict the bacterial kinetics in plasma and in target tissues [adipose, muscle, epithelial lining fluid (ELF) and sputum] over 120 h of therapy. The PKPD model adequately described the bacterial kill kinetics for all bacterial populations. At the human recommended dose of 200 mg/day, bacterial growth was predicted in plasma and all tissues, except for ELF. Bacteriostasis was observed only at a higher dose of 1200 mg/day over 120 h. An fAUC/MIC of 80 related to stasis over 120 h. Subpopulations resistant to 3 × MIC were amplified in plasma and target tissues, except for ELF, at doses of 200-800 mg/day. The human dose of 200 mg/day was insufficient to suppress bacterial growth in the HFIM, indicating that further components contribute to the clinical effect of tedizolid. This study supports the warning/precaution for tedizolid to limit its use in immunocompromised patients.

Establishment of Level a In Vitro-In Vivo Correlation (IVIVC) via Extended DoE-IVIVC Model: A Donepezil Case Study.

This study aimed to establish an extended design of experiment (DoE)-in vitro in vivo correlation (IVIVC) model that defines the relationship between formulation composition, in vitro dissolution, and in vivo pharmacokinetics. Fourteen sustained-release (SR) tablets of a model drug, donepezil, were designed by applying a mixture design of DoE and prepared by the wet granulation method. The in vitro dissolution patterns of donepezil SR tablets were described by Michaelis–Menten kinetics. The mathematical relationship describing the effects of SR tablet compositions on the in vitro dissolution parameter, i.e., the in vitro maximum rate of release (Vmax), was derived. The predictability of the derived DoE model was validated by an additional five SR tablets with a mean prediction error (PE%) of less than 3.50% for in vitro Vmax. The pharmacokinetics of three types of donepezil SR and the immediate-release (IR) tablets was assessed in Beagle dogs following oral administration (n = 3, each). Based on the plasma concentration-time profile, a population pharmacokinetic model was developed, and the in vivo dissolution of SR tablets, represented by in vivo Vmax, was estimated. By correlating the in vitro and in vivo Vmax, level A IVIVC was established. Finally, the extended DoE-IVIVC model was developed by integrating the DoE equation and IVIVC into the population pharmacokinetic model. The extended DoE-IVIVC model allowed one to predict the maximum plasma concentration (Cmax) and the area under the plasma concentration-time curve (AUC) of donepezil SR tablets with PE% less than 10.30% and 5.19%, respectively, by their formulation composition as an input. The present extended DoE-IVIVC model may provide a valuable tool to predict the effect of formulation changes on in vivo pharmacokinetic behavior, leading to the more efficient development of SR formulations. The application of the present modeling approaches to develop other forms of drug formulation may be of interest for future studies.

Population Pharmacokinetic Models for Direct Oral Anticoagulants: A Systematic Review and Clinical Appraisal Using Exposure Simulation.

Available data have shown an association between direct oral anticoagulant (DOAC) plasma concentration and clinical, particularly bleeding, events. Factors that may influence DOAC plasma concentration are therefore the focus of particular attention. Population pharmacokinetic (PopPK) analyses can help in identifying such factors while providing predictive models. The main aim of the present study was to identify all the PopPK models to date for the four most frequently used DOACs (dabigatran, apixaban, rivaroxaban, and edoxaban). The secondary aim was to use these models to simulate different DOAC plasma concentration–time profiles in relevant clinical scenarios. The results of our model‐based simulations confirm the clinical relevance of the known major factors influencing DOAC exposure and support the current approved dose adaptation, at least for atrial fibrillation. They also highlight how the accumulation of covariates, not currently considered for dose adaptation due to their seemingly minor influence on DOAC exposure, lead to supratherapeutic blood concentrations and could thus enhance the risk of major bleeding. The present results therefore question DOAC dose adaptation in the presence of these covariates, such as drug–drug interaction or genotypes, alongside the known existing covariates. As the overall effect of accumulation of several covariates could be difficult to apprehend for the clinicians, PopPK modeling could represent an interesting approach for informed precision dosing and to improve personalized prescription of DOACs.

Pharmacokinetics of Cannabidiol Following Intranasal, Intrarectal, and Oral Administration in Healthy Dogs.

The therapeutic potential of cannabidiol (CBD), a non-psychtropic component of the Cannabis sativa plant, is substantiated more and more. We aimed to determine the pharmacokinetic behavior of CBD after a single dose via intranasal (IN) and intrarectal (IR) administration in six healthy Beagle dogs age 3–8 years old, and compare to the oral administration route (PO). Standardized dosages applied for IN, IR and PO were 20, 100, and 100 mg, respectively. Each dog underwent the same protocol but received CBD through a different administration route. CBD plasma concentrations were determined by ultra-high performance liquid chromatography-tandem mass spectrometry before and at fixed time points after administration. Non-compartmental analysis was performed on the plasma concentration-time profiles. Plasma CBD concentrations after IR administration were below the limit of quantification. The mean area under the curve (AUC) after IN and PO CBD administration was 61 and 1,376 ng/mL*h, respectively. The maximal plasma CBD concentration (Cmax) after IN and PO CBD administration was 28 and 217 ng/mL reached after 0.5 and 3.5 h (Tmax), respectively. Significant differences between IN and PO administration were found in the Tmax (p = 0.04). Higher AUC and Cmax were achieved with 100 mg PO compared to 20 mg IN, but no significant differences were found when AUC (p = 0.09) and Cmax (p = 0.44) were normalized to 1 mg dosages. IN administration of CBD resulted in faster absorption when compared to PO administration. However, PO remains the most favorable route for CBD delivery due to its more feasible administration. The IR administration route is not advised for clinical application.

Renal Transporter-Mediated Drug-Biomarker Interactions of the Endogenous Substrates Creatinine and N1 -Methylnicotinamide: A PBPK Modeling Approach.

Endogenous biomarkers for transporter-mediated drug-drug interaction (DDI) predictions represent a promising approach to facilitate and improve conventional DDI investigations in clinical studies. This approach requires high sensitivity and specificity of biomarkers for the targets of interest (e.g., transport proteins), as well as rigorous characterization of their kinetics, which can be accomplished utilizing physiologically-based pharmacokinetic (PBPK) modeling. Therefore, the objective of this study was to develop PBPK models of the endogenous organic cation transporter (OCT)2 and multidrug and toxin extrusion protein (MATE)1 substrates creatinine and N1 -methylnicotinamide (NMN). Additionally, this study aimed to predict kinetic changes of the biomarkers during administration of the OCT2 and MATE1 perpetrator drugs trimethoprim, pyrimethamine, and cimetidine. Whole-body PBPK models of creatinine and NMN were developed utilizing studies investigating creatinine or NMN exogenous administration and endogenous synthesis. The newly developed models accurately describe and predict observed plasma concentration-time profiles and urinary excretion of both biomarkers. Subsequently, models were coupled to the previously built and evaluated perpetrator models of trimethoprim, pyrimethamine, and cimetidine for interaction predictions. Increased creatinine plasma concentrations and decreased urinary excretion during the drug-biomarker interactions with trimethoprim, pyrimethamine, and cimetidine were well-described. An additional inhibition of NMN synthesis by trimethoprim and pyrimethamine was hypothesized, improving NMN plasma and urine interaction predictions. To summarize, whole-body PBPK models of creatinine and NMN were built and evaluated to better assess creatinine and NMN kinetics while uncovering knowledge gaps for future research. The models can support investigations of renal transporter-mediated DDIs during drug development.

Prediction of Pharmacokinetics of IDP-73152 in Humans Using Physiologically-Based Pharmacokinetics.

IDP-73152, a novel peptide deformylase inhibitor with an antibacterial effect against Gram-positive bacteria, is in phase I development. The objective of this study was to develop a physiologically-based pharmacokinetic model (PBPK) for IDP-73152 in animals, and to extend the model to humans. Biopharmaceutical properties of IDP-73152 are determined using in vitro/in vivo experimentations for the PBPK model. A transit model consisting of gastrointestinal segments is applied for an estimation of the intestinal absorption kinetics. The PBPK model of IDP-73152 in rats is able to appropriately predict the plasma concentration–time profiles after the administration of IDP-73152 at different doses and by different routes (combined absolute average fold error (cAAFE), 1.77). The model is also found to be adequate in predicting the plasma concentration–time profiles of IDP-73152 in mice (cAAFE 1.59) and dogs (cAAFE 1.42). Assuming the oral administration of IDP-73152 to humans at doses of 640 and 1280 mg, the model is able to reproduce the concentration–time profiles obtained in humans (cAAFE 1.38); therefore, these observations indicate that the PBPK model used for IDP-73152 is applicable to animal species and humans. This model may be useful in predicting efficacious doses of IDP-73152 for the management of infectious disease in humans.

Effect of a Ketohexokinase Inhibitor (PF‐06835919) on In Vivo OATP1B Activity: Integrative Risk Assessment Using Endogenous Biomarker and a Probe Drug

PF-06835919 is a first-in-class ketohexokinase inhibitor (KHKi), recently under development for the treatment of metabolic and fatty liver diseases, which inhibited organic anion transporting polypeptide (OATP)1B1 in vitro and presented drug-drug interaction (DDI) risk. This study aims to investigate the dose-dependent effect of KHKi on OATP1B in vivo activity. We performed an open-label study comparing pharmacokinetics of atorvastatin (OATP1B probe) dosed alone (20 mg single dose) and coadministered with two dose strengths of KHKi (50 and 280mg once daily) in 12 healthy participants. Additionally, changes in exposure of coproporphyrin-I (CP-I), an endogenous biomarker for OATP1B, were assessed in the atorvastatin study (1.12-fold and 1.49-fold increase in area under the plasma concentration-time profile (AUC) with once-daily 50 and 280mg, respectively), and a separate single oral dose study of KHKi alone (100-600mg, n=6 healthy participants; up to a 1.80-fold increase in AUC). Geometric mean ratios (90% confidence interval) of atorvastatin AUC following 50 and 280mg KHKi were 1.14 (1.00-1.30) and 1.54 (1.37-1.74), respectively. Physiologically-based pharmacokinetic modeling of CP-I plasma exposure following a single dose of KHKi predicted in vivo OATP1B inhibition from about 13% to 70% over the 100 to 600mg dose range, while using the in vitro inhibition potency (1.9µM). Model-based analysis correctly predicted "no-effect" (AUC ratio <1.25) at the low dose range and "weak" effect (AUC ratio <2) on atorvastatin pharmacokinetics at the high dose range of KHKi. This study exemplified the utility of biomarker-informed model-based approach in discerning even small effects on OATP1B activity in vivo, and to project DDI risk at the clinically relevant doses.

Development and application of a pediatric mechanistic kidney model.

Pediatric physiologically‐based pharmacokinetic (P‐PBPK) models have been used to predict age related changes in the pharmacokinetics (PKs) of renally cleared drugs mainly in relation to changes in glomerular filtration rate. With emerging data on ontogeny of renal transporters, mechanistic models of renal clearance accounting for the role of active and passive secretion should be developed and evaluated. Data on age‐related physiological changes and ontogeny of renal transporters were applied into a mechanistic kidney within a P‐PBPK model. Plasma concentration–time profile and PK parameters of cimetidine, ciprofloxacin, metformin, tenofovir, and zidovudine were predicted in subjects aged 1 day to 18 years. The predicted and observed plasma concentration–time profiles and PK parameters were compared. The predicted concentration–time profile means and 5th and 95th percent intervals generally captured the observed data and variability in various studies. Overall, based on drugs and age bands, predicted to observed clearance were all within two‐fold and in 11 of 16 cases within 1.5‐fold. Predicted to observed area under the curve (AUC) and maximum plasma concentration (Cmax) were within two‐fold in 12 of 14 and 12 of 15 cases, respectively. Predictions in neonates and early infants (up to 14 weeks postnatal age) were reasonable with 15–20 predicted PK parameters within two‐fold of the observed. ciprofloxacin but not zidovudine PK predictions were sensitive to basal kidney uptake transporter ontogeny. The results indicate that a mechanistic kidney model accounting for physiology and ontogeny of renal processes and transporters can predict the PK of renally excreted drugs in children. Further data especially in neonates are required to verify the model and ontogeny profiles.

Non-clinical studies indicating lack of interactions between iron/calcium ions and linzagolix, an orally available GnRH antagonist

Linzagolix is an orally available gonadotropin-releasing hormone antagonist used to treat sex-hormone-dependent diseases in women. This study aimed to investigate drug-drug interactions between linzagolix and iron/calcium ions in the intended clinical setting by conducting pharmacokinetic studies in vitro and in rats. Insoluble precipitate formation with metal ions was evaluated by measuring linzagolix concentrations in four types of bio-relevant dissolution media (fasted/fed state simulated gastric fluid and fasted/fed state simulated gastric fluid version 2), and chelate complex formation with metal ions was evaluated by release of linzagolix from a cellulose membrane sac. In these in vitro studies, linzagolix showed no potential for insoluble precipitate formation under fasted/fed conditions and no chelate complex formation in the presence of metal ions. In rats, the plasma concentration-time profiles of linzagolix and iron ion were similar regardless of whether they were administered with or without ferrous sulfate and linzagolix choline at clinically relevant doses. Thus, linzagolix and iron ion had no effect on each other’s absorption in vivo. In conclusion, linzagolix is unlikely to cause clinically relevant drug-drug interactions by chelating metal ions according to the results of in vitro and in vivo studies.

Physiologically based pharmacokinetic (PBPK) modeling of piroxicam with regard to CYP2C9 genetic polymorphism.

Piroxicam is a non-steroidal anti-inflammatory drug used to alleviate symptoms of osteoarthritis and rheumatoid arthritis. CYP2C9 genetic polymorphism significantly influences the pharmacokinetics of piroxicam. The objective of this study was to develop and validate the piroxicam physiologically based pharmacokinetic (PBPK) model related to CYP2C9 genetic polymorphism. PK-Sim® version 10.0 was used for the PBPK modeling. The PBPK model was evaluated by predicted and observed plasma concentration-time profiles, fold errors of predicted to observed pharmacokinetic parameters, and a goodness-of-fit plot. The turnover number (kcat) of CYP2C9 was adjusted to capture the pharmacokinetics of piroxicam in different CYP2C9 genotypes. The population PBPK model overall accurately described and predicted the plasma concentration-time profiles in different CYP2C9 genotypes. In our simulations, predicted AUCinf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.83-, 2.07-, and 6.43-fold higher than CYP2C9*1/*1 genotype, respectively. All fold error values for AUC, Cmax, and t1/2 were included in the acceptance criterion with the ranges of 0.57-1.59, 0.63-1.39, and 0.65-1.51, respectively. The range of fold error values for predicted versus observed plasma concentrations was 0.11-3.13. 93.9% of fold error values were within the two-fold range. Average fold error, absolute average fold error, and root mean square error were 0.93, 1.27, and 0.72, respectively. Our model accurately captured the pharmacokinetic alterations of piroxicam according to CYP2C9 genetic polymorphism.

Assessing the Effect of Organic Anion Transporter Inhibition on Circulating Pyridoxic Acid, an Endogenous Transporter Biomarker, using Physiologically‐based Pharmacokinetic Modeling

Transporter‐mediated renal secretion plays a critical role in the systemic clearance of ~30% of the Food and Drug Administration (FDA)‐approved drugs and is attributed to clinically significant drug‐drug interactions (DDIs). For example, organic anion transporters (OATs) are inhibited by perpetrator drugs (e.g., probenecid), leading to higher circulating levels of OAT substrates (e.g., furosemide).1 Recently, OAT inhibition has been shown to be associated with increased plasma levels of endogenous substrates, e.g., pyridoxic acid (PDA) and homovanillic acid, which can serve as potential OAT biomarkers.2 The objective of our study was to develop and validate a physiologically‐based pharmacokinetic (PBPK) model of PDA to allow prospective evaluation of the magnitude of potential DDI of an OAT inhibitor‐substrate pair. Probenecid and furosemide were used as selective inhibitor and substrate of OATs, respectively. Physicochemical properties and in vitro data pertaining to the pharmacokinetics of probenecid and PDA were collated from literature. A PBPK model was first constructed to predict the plasma concentration‐time profiles of probenecid after oral administration using Simcyp (v20). Then, utilizing the fraction secreted versus filtered as well as the unbound fraction (fu = 0.092) data of PDA,2 the total elimination and synthesis rates of PDA at steady‐state were used to develop a baseline PBPK model. The effect of OAT inhibition by probenecid on the PDA levels was estimated and the predicted area under the plasma concentration‐time profile (AUC), change in clearance, and the highest plasma concentration (Cmax) values were compared with the observed data.2 The model was able to capture the changes within 2‐fold of the clinical data. Using the predicted AUC profile of PDA and assuming 100% inhibition at Cmax, the magnitude of inhibition was estimated across different time points. The biomarker‐informed magnitude of inhibition showed significant correlation (r2 = 0.9336) with the observed change in furosemide concentrations in the presence of probenecid (Fig. 1). PDA‐informed PBPK model developed here can be used to prospectively predict the magnitude of OAT inhibition, which is particularly applicable to assessing DDI potential of investigational drugs or prescribed drugs in special populations with sparse samples, without the requirement of an exogenous probe substrate.

Intestinal P‐glycoprotein (P‐gp) Contribution to Talinolol Pharmacokinetics in Human

ObjectiveUnderstanding the mechanisms of intestinal secretion and recirculation is important to the realm of drug metabolism and pharmacokinetics (DMPK). P‐glycoprotein (P‐gp), one of the major efflux transporters in the intestine, has broad substrate specificity and could contribute to the intestinal secretion/recirculation of drugs. The pharmacokinetic (PK) model incorporating intestinal P‐gp contribution will be able to accurately capture the interactions for the compounds of P‐gp substrate, allowing the model to aid in determining first in‐human (FIH) dose predictions as well as related potential drug‐drug interactions (DDIs). Talinolol, a beta‐adrenergic receptor antagonist utilized for cardioprotective and antihypertensive treatments, is a good substrate of P‐gp, and a double peak of plasma concentration has been observed. We hypothesize that intestinal secretion/recirculation by P‐gp could contribute to this unique plasma concentration‐time profile of talinolol. The aim of this study was to assess whether the double peak of plasma concentration of orally administered talinolol can be captured using physiological‐based pharmacokinetic (PBPK) modeling.MethodsThe plasma concentration‐time profiles of talinolol were obtained by digitizing literature data. The P‐gp‐mediated transport kinetics of talinolol were also obtained from Caco‐2 assays present in literature. Using the plasma concentration of talinolol data after intravenous (IV) administration, the intestinal secretion clearance (CLGI) was estimated using SimCYP (v19). After estimating CLGI, the regional absorption of talinolol affected by intestinal P‐gp was assessed using plasma talinolol concentration data after oral administration and the advanced dissolution, absorption, and metabolism (ADAM) model was subsequently generated utilizing SimCYP.ResultsCLGI of talinolol was estimated through using plasma concentration data of the drug after IV infusion reported by Schwarz et al., and CLGI was estimated to be 12.6 L/hr. This CLGI value was validated by capturing another plasma concentration‐time profile of talinolol after IV infusion reported by Westphal et al. The dual‐peak of the plasma talinolol concentration after oral administration was captured using ADAM model, but this model will be further refined to better capture this dual‐peak after oral administration of talinolol in human with consideration of regional differences of absorption and/or recirculation (i.e., more P‐gp in ileum compared to duodenum and jejunum).ConclusionA model was successfully generated to accurately capture the PK profiles of talinolol after IV administration. Further refinement of the model will be required for oral administration. The outcomes from the investigation essentially broaden our overall understanding of the processes underlying intestinal secretion and recirculation.

Prediction of CYP‐mediated DDIs involving inhibition: Approaches to address the requirements for system qualification of the Simcyp Simulator

Physiologically‐based pharmacokinetic (PBPK) modeling is being increasingly used in drug development to avoid unnecessary clinical drug–drug interaction (DDI) studies and inform drug labels. Thus, regulatory agencies are recommending, or indeed requesting, more rigorous demonstration of the prediction accuracy of PBPK platforms in the area of their intended use. We describe a framework for qualification of the Simcyp Simulator with respect to competitive and mechanism‐based inhibition (MBI) of CYP1A2, CYP2D6, CYP2C8, CYP2C9, CYP2C19, and CYP3A4/5. Initially, a DDI matrix, consisting of a range of weak, moderate, and strong inhibitors and substrates with varying fraction metabolized by specific CYP enzymes that were susceptible to different degrees of inhibition, were identified. Simulations were run with 123 clinical DDI studies involving competitive inhibition and 78 clinical DDI studies involving MBI. For competitive inhibition, the overall prediction accuracy was good with an average fold error (AFE) of 0.91 and 0.92 for changes in the maximum plasma concentration (Cmax) and area under the plasma concentration (AUC) time profile, respectively, as a consequence of the DDI. For MBI, an AFE of 1.03 was determined for both Cmax and AUC. The prediction accuracy was generally comparable across all CYP enzymes, irrespective of the isozyme and mechanism of inhibition. These findings provide confidence in application of the Simcyp Simulator (V19 R1) for assessment of the DDI potential of drugs in development either as inhibitors or victim drugs of CYP‐mediated interactions. The approach described herein and the identified DDI matrix can be used to qualify subsequent versions of the platform.

Physiologically Based Pharmacokinetic (PBPK) Modeling of Clopidogrel and Its Four Relevant Metabolites for CYP2B6, CYP2C8, CYP2C19, and CYP3A4 Drug-Drug-Gene Interaction Predictions.

The antiplatelet agent clopidogrel is listed by the FDA as a strong clinical index inhibitor of cytochrome P450 (CYP) 2C8 and weak clinical inhibitor of CYP2B6. Moreover, clopidogrel is a substrate of—among others—CYP2C19 and CYP3A4. This work presents the development of a whole-body physiologically based pharmacokinetic (PBPK) model of clopidogrel including the relevant metabolites, clopidogrel carboxylic acid, clopidogrel acyl glucuronide, 2-oxo-clopidogrel, and the active thiol metabolite, with subsequent application for drug–gene interaction (DGI) and drug–drug interaction (DDI) predictions. Model building was performed in PK-Sim® using 66 plasma concentration-time profiles of clopidogrel and its metabolites. The comprehensive parent-metabolite model covers biotransformation via carboxylesterase (CES) 1, CES2, CYP2C19, CYP3A4, and uridine 5′-diphospho-glucuronosyltransferase 2B7. Moreover, CYP2C19 was incorporated for normal, intermediate, and poor metabolizer phenotypes. Good predictive performance of the model was demonstrated for the DGI involving CYP2C19, with 17/19 predicted DGI AUClast and 19/19 predicted DGI Cmax ratios within 2-fold of their observed values. Furthermore, DDIs involving bupropion, omeprazole, montelukast, pioglitazone, repaglinide, and rifampicin showed 13/13 predicted DDI AUClast and 13/13 predicted DDI Cmax ratios within 2-fold of their observed ratios. After publication, the model will be made publicly accessible in the Open Systems Pharmacology repository.

Physiologically Based Biopharmaceutics Model of Vildagliptin Modified Release (MR) Tablets to Predict In Vivo Performance and Establish Clinically Relevant Dissolution Specifications.

The objective of the study was to predict pharmacokinetic (PK) and pharmacodynamic (PD) parameters of matrix-based modified release (MR) drug product of vildagliptin. Physiologically based biopharmaceutics modeling (PBBM) was developed using GastroPlus™ based on the available data including immediate-release (IR) drug product of vildagliptin. In vitro-in vivo correlation (IVIVC) was developed using mechanistic deconvolution to predict plasma concentration-time profile and PK parameters for a MR drug product planned for clinical use. Both methods, i.e., PBBM and IVIVC, were compared for the predicted PK parameters. Integration of DDDPlus™ and GastroPlus™ modeling was performed to explore clinically relevant dissolution specifications for vildagliptin MR tablets. The bioequivalence (BE) between batches with different dissolution specifications was evaluated using virtual clinical trials. The PD effect of dipeptidyl peptidase-IV (DPP-IV) inhibition was simulated utilizing PDPlus™ model in GastroPlus™. The results indicated that IVIVC best correlated the simulated PK parameters with those observed with the clinical study. The outcomes highlight the importance of integration of in vitro and in silico tools towards predictability of PK and PD parameters for a MR drug product. However, the post absorptive phase was found to be more dependent on the demographics of the healthy subjects.

NUMERICAL SIMULATION ON-TIME EVALUATION OF PLASMA DRUG CONCENTRATIONS FOR ONE-COMPARTMENT MODEL IN PRESENCE OF DRUG INFUSION

In the present numerical study, we apply an ODE IVP to plasma drug concentrations for a one-compartment model in presence of drug infusion. Solution procedure is done in a Matlab environment. The outcome shows that the infusion rate at time t = 4 h is discontinuous but the corresponding plasma concentration-time profile looks smooth at that time.

Chemical, Analytical and Pharmacokinetic Characterisation of RO7304898, an API Consisting of Two Rapidly Interconverting Diastereoisomers.

Exploration of the chemical, analytical and pharmacokinetic properties of the API, RO7304898, an allosteric EGFR inhibitor, intended to be developed as a mixture of two rapidly interconverting diastereoisomers with composition ratio of approximately 1:1. Assessment of diastereoisomer stereochemistry, interconversion rates, binding to EGFR protein, metabolic stability and in vivo PK in Wistar-Han rats was conducted. The two diastereoisomers of the API undergo fast interconversion at physiologically relevant pH and direct EGFR binding studies revealed diastereoisomer B to be the active moiety. Pharmacokinetic studies in rat revealed a low-moderate total plasma clearance of the API along with similar plasma concentration-time profiles for diastereoisomers A and B, and the diastereoisomeric ratio reached stable equilibrium favoring formation of the potent diastereoisomer B. In in vitro incubations, the API was metabolically stable in plasma and hepatocyte suspension incubations in all species tested except that of rat hepatocytes. Additionally, only small species differences in the A:B composition were observed in vitro with the potent diastereoisomer B being the predominant form. We demonstrated that the API, a mixture of two diastereoisomers; A (impotent) and B (potent), undergoes rapid interconversion which is faster than the apparent distribution and elimination rates of the individual diastereoisomers in vivo in rat, serving to diminish concerns that separate diastereoisomer effects may occur in subsequent pharmacologic and pivotal toxicological studies. Whilst vigilant monitoring of the diastereoisomeric ratio will need to be continued, this data adds confidence on the development pathway for this API to the clinic.

Model-based meta-analysis of salbutamol pharmacokinetics and practical implications for doping control.

Salbutamol was included in the prohibited list of the World Anti‐Doping Agency (WADA) in 2004. Although systemic intake is banned, inhalation for asthma is permitted but with dosage restrictions. The WADA established a urinary concentration threshold to distinguish accordingly prohibited systemic self‐administration from therapeutic prescription by inhalation. This study aimed at evaluating the ability of the WADA threshold to differentiate salbutamol therapeutic use from violation of antidoping rules. Concentration‐time profile of salbutamol in plasma and its excretion in urine was characterized through a model‐based meta‐analysis of individual and aggregate data collected after administration of a large range of doses following different modes of administration and under a variety of conditions. The developed model adequately fitted salbutamol plasma and urine concentration‐time profiles of the 13 selected studies. Model‐based simulations confirmed that a wide range of salbutamol urine concentrations might be measured after drug intake. Although violation of the WADA Code can be strongly suspected in individuals showing very high salbutamol urine concentrations, uncertainty remains for values close to the WADA threshold as they can be compatible with both permitted therapeutic use and violation. Although not entirely discriminant, the current WADA rule is globally supported by our appraisal. It could be further improved by a slight and reasonable adjustment of inhaled daily dosages allowed for therapeutic use. Our model might help antidoping experts in the evaluation of suspected doping cases through confronting the athlete's urine measurements with their allegations about salbutamol treatment.

Predicting Regional Respiratory Tissue and Systemic Concentrations of Orally Inhaled Drugs through a Novel PBPK Model.

Oral inhalation (OI) of drugs is the route of choice to treat respiratory diseases or for recreational drug use (e.g., cannabis). After OI, the drug is deposited in and systemically absorbed from various regions of the respiratory tract. Measuring regional respiratory tissue drug concentrations at the site of action is important for evaluating the efficacy and safety of orally inhaled drugs (OIDs). Because such a measurement is routinely not possible in humans, the only alternative is to predict these concentrations, for example by physiologically based pharmacokinetic (PBPK) modeling. Therefore, we developed an OI-PBPK model to integrate the interplay between regional respiratory drug deposition and systemic absorption to predict regional respiratory tissue and systemic drug concentrations. We validated our OI-PBPK model by comparing the simulated and observed plasma concentration-time profiles of two OIDs, morphine and nicotine. Furthermore, we performed sensitivity analyses to quantitatively demonstrate the impact of key parameters on the extent and pattern of regional respiratory drug deposition, absorption, and the resulting regional respiratory tissue and systemic plasma concentrations. Our OI-PBPK model can be applied to predict regional respiratory tissue and systemic drug concentrations to optimize OID formulations, delivery systems, and dosing regimens. Furthermore, our model could be used to establish the bioequivalence of generic OIDs for which systemic plasma concentrations are not measurable or are not a good surrogate of the respiratory tissue drug concentrations. SIGNIFICANCE STATEMENT: Our OI-PBPK model is the first comprehensive model to predict regional respiratory deposition, as well as systemic and regional tissue concentrations of OIDs, especially at the drug's site of action, which is difficult to measure in humans. This model will help optimize OID formulations, delivery systems, dosing regimens, and bioequivalence assessment of generic OID. Furthermore, this model can be linked with organs-on-chips, pharmacodynamic and quantitative systems pharmacology models to predict and evaluate the safety and efficacy of OID.

A Pharmaceutical Formulation as a Claim Term Cannot “Target” a Plasma Concentration-Time Profile Under 35 U.S.C. § 112: A Lesson from Horizon Pharma, Inc. v. Dr. Reddy's Laboratories Inc.

A Pharmaceutical Formulation as a Claim Term Cannot “Target” a Plasma Concentration-Time Profile Under 35 U.S.C. § 112: A Lesson from <i>Horizon Pharma, Inc. v. Dr. Reddy's Laboratories Inc.</i>