Dymphy Huntjens

A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

PurposePredicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human brain disposition.MethodsA mathematical model consisting of several physiological brain compartments in the rat was developed using rich concentration-time profiles from nine structurally diverse drugs in plasma, brain extracellular fluid, and two cerebrospinal fluid compartments. The effect of active drug transporters was also accounted for. Subsequently, the model was translated to predict human concentration-time profiles for acetaminophen and morphine, by scaling or replacing system- and drug-specific parameters in the model.ResultsA common model structure was identified that adequately described the rat pharmacokinetic profiles for each of the nine drugs across brain compartments, with good precision of structural model parameters (relative standard error <37.5%). The model predicted the human concentration-time profiles in different brain compartments well (symmetric mean absolute percentage error <90%).ConclusionsA multi-compartmental brain pharmacokinetic model was developed and its structure could adequately describe data across nine different drugs. The model could be successfully translated to predict human brain concentrations.

Therapeutic efficacy of a respiratory syncytial virus fusion inhibitor

Respiratory syncytial virus is a major cause of acute lower respiratory tract infection in young children, immunocompromised adults, and the elderly. Intervention with small-molecule antivirals specific for respiratory syncytial virus presents an important therapeutic opportunity, but no such compounds are approved today. Here we report the structure of JNJ-53718678 bound to respiratory syncytial virus fusion (F) protein in its prefusion conformation, and we show that the potent nanomolar activity of JNJ-53718678, as well as the preliminary structure–activity relationship and the pharmaceutical optimization strategy of the series, are consistent with the binding mode of JNJ-53718678 and other respiratory syncytial virus fusion inhibitors. Oral treatment of neonatal lambs with JNJ-53718678, or with an equally active close analog, efficiently inhibits established acute lower respiratory tract infection in the animals, even when treatment is delayed until external signs of respiratory syncytial virus illness have become visible. Together, these data suggest that JNJ-53718678 is a promising candidate for further development as a potential therapeutic in patients at risk to develop respiratory syncytial virus acute lower respiratory tract infection.Respiratory syncytial virus causes lung infections in children, immunocompromised adults, and in the elderly. Here the authors show that a chemical inhibitor to a viral fusion protein is effective in reducing viral titre and ameliorating infection in rodents and neonatal lambs.

Predicting Drug Concentration-Time Profiles in Multiple CNS Compartments Using a Comprehensive Physiologically-Based Pharmacokinetic Model

Drug development targeting the central nervous system (CNS) is challenging due to poor predictability of drug concentrations in various CNS compartments. We developed a generic physiologically based pharmacokinetic (PBPK) model for prediction of drug concentrations in physiologically relevant CNS compartments. System‐specific and drug‐specific model parameters were derived from literature and in silico predictions. The model was validated using detailed concentration‐time profiles from 10 drugs in rat plasma, brain extracellular fluid, 2 cerebrospinal fluid sites, and total brain tissue. These drugs, all small molecules, were selected to cover a wide range of physicochemical properties. The concentration‐time profiles for these drugs were adequately predicted across the CNS compartments (symmetric mean absolute percentage error for the model prediction was <91%). In conclusion, the developed PBPK model can be used to predict temporal concentration profiles of drugs in multiple relevant CNS compartments, which we consider valuable information for efficient CNS drug development.

A comparison of two semi-mechanistic models for prolactin release and prediction of receptor occupancy following administration of dopamine D2 receptor antagonists in rats.

We compared the model performance of two semi-mechanistic pharmacokinetic-pharmacodynamic models, the precursor pool model and the agonist-antagonist interaction model, to describe prolactin response following the administration of the dopamine D2 receptor antagonists risperidone, paliperidone or remoxipride in rats. The time course of pituitary dopamine D2 receptor occupancy was also predicted. Male Wistar rats received a single dose (risperidone, paliperidone, remoxipride) or two consecutive doses (remoxipride). Population modeling was applied to fit the pool and interaction models to the prolactin data. The pool model was modified to predict the time course of pituitary D2 receptor occupancy. Unbound plasma concentrations of the D2 receptor antagonists were considered the drivers of the prolactin response. Both models were used to predict prolactin release following multiple doses of paliperidone. Both models described the data well and model performance was comparable. Estimated unbound EC50 for risperidone and paliperidone was 35.1nM (relative standard error 51%) and for remoxipride it was 94.8nM (31%). KI values for these compounds were 11.1nM (21%) and 113nM (27%), respectively. Estimated pituitary D2 receptor occupancies for risperidone and remoxipride were comparable to literature findings. The interaction model better predicted prolactin profiles following multiple paliperidone doses, while the pool model predicted tolerance better. The performance of both models in describing the prolactin profiles was comparable. The pool model could additionally describe the time course of pituitary D2 receptor occupancy. Prolactin response following multiple paliperidone doses was better predicted by the interaction model.

A comparison of RSV and influenza in vitro kinetic parameters reveals differences in infecting time

Influenza and respiratory syncytial virus (RSV) cause acute infections of the respiratory tract. Since the viruses both cause illnesses with similar symptoms, researchers often try to apply knowledge gleaned from study of one virus to the other virus. This can be an effective and efficient strategy for understanding viral dynamics or developing treatment strategies, but only if we have a full understanding of the similarities and differences between the two viruses. This study used mathematical modeling to quantitatively compare the viral kinetics of in vitro RSV and influenza virus infections. Specifically, we determined the viral kinetics parameters for RSV A2 and three strains of influenza virus, A/WSN/33 (H1N1), A/Puerto Rico/8/1934 (H1N1), and pandemic H1N1 influenza virus. We found that RSV viral titer increases at a slower rate and reaches its peak value later than influenza virus. Our analysis indicated that the slower increase of RSV viral titer is caused by slower spreading of the virus from one cell to another. These results provide estimates of dynamical differences between influenza virus and RSV and help provide insight into the virus-host interactions that cause observed differences in the time courses of the two illnesses in patients.

A human challenge model for respiratory syncytial virus kinetics, the pharmacological effect of a novel fusion inhibitor, and the modelling of symptoms scores

Abstract Respiratory syncytial virus (RSV) causes acute lower respiratory tract infections, and is a major cause of hospital admissions and death in young children. Limited treatments currently exist that can prevent or minimise exacerbation of the disease. The aims of this work were: 1) to develop a population pharmacodynamic model to describe RSV kinetics (RSVK) in nasal lavage, 2) evaluate the impact of an investigational fusion inhibitor, JNJ‐53718678, on RSVK, and 3) determine the relationship between RSVK and symptoms scores. The best model to fit the RSVK data was a target‐cell limited viral kinetics model previously developed for influenza A infections (Baccam et al., 2006), which included a series of compartments for infected, non‐producing and infected, and producing cell populations. The model was adapted to account for longer incubation times seen in RSV, by including 4 additional transit compartments, with the virus elimination rate constant and initial number of target cells fixed to literature values to ensure model parameter identifiability. Between‐subject variability was included on the infection rate constant and virus production rate constant. The effect of JNJ‐53718678 on RSVK was best described by a non‐dose dependent transformation of the infectious virions into a non‐infectious state, with a proportional odds model successfully describing symptoms scores, using individual model predicted viral loads as predictor. Graphical Abstract No caption available.

Modeling of prolactin response following dopamine D2 receptor antagonists in rats: can it be translated to clinical dosing?

Prolactin release is a side effect of antipsychotic therapy with dopamine antagonists, observed in rats as well as humans. We examined whether two semimechanistic models could describe prolactin response in rats and subsequently be translated to predict pituitary dopamine D2 receptor occupancy and plasma prolactin concentrations in humans following administration of paliperidone or remoxipride. Data on male Wistar rats receiving single or multiple doses of risperidone, paliperidone, or remoxipride was described by two semimechanistic models, the precursor pool model and the agonist–antagonist interaction model. Using interspecies scaling approaches, human D2 receptor occupancy and plasma prolactin concentrations were predicted for a range of clinical paliperidone and remoxipride doses. The predictions were compared with corresponding observations described in literature as well as with predictions from published models developed on human data. The pool model could predict D2 receptor occupancy and prolactin response in humans following single doses of paliperidone and remoxipride. Tolerance of prolactin release was predicted following multiple doses. The interaction model underpredicted both D2 receptor occupancy and prolactin response. Prolactin elevation may be deployed as a suitable biomarker for interspecies translation and can inform the clinical safe and effective dose range of antipsychotic drugs. While the pool model was more predictive than the interaction model, it overpredicted tolerance on multiple dosing. Shortcomings of the translations reflect the need for better mechanistic models.

Summary data of potency and parameter information from semi-mechanistic PKPD modeling of prolactin release following administration of the dopamine D2 receptor antagonists risperidone, paliperidone and remoxipride in rats.

We provide the reader with relevant data related to our recently published paper, comparing two mathematical models to describe prolactin turnover in rats following one or two doses of the dopamine D2 receptor antagonists risperidone, paliperidone and remoxipride, “A comparison of two semi-mechanistic models for prolactin release and prediction of receptor occupancy following administration of dopamine D2 receptor antagonists in rats” (Taneja et al., 2016) [1]. All information is tabulated. Summary level data on the in vitro potencies and the physicochemical properties is presented in Table 1. Model parameters required to explore the precursor pool model are presented in Table 2. In Table 3, estimated parameter comparisons for both models are presented, when separate potencies are estimated for risperidone and paliperidone, as compared to a common potency for both drugs. In Table 4, parameter estimates are compared when the drug effect is parameterized in terms of drug concentration or receptor occupancy.

Antiviral Activity of Oral JNJ-53718678 in Healthy Adult Volunteers Challenged With Respiratory Syncytial Virus: A Placebo-Controlled Study

Background Respiratory syncytial virus (RSV) disease has no effective treatment. JNJ-53718678 is a fusion inhibitor with selective activity against RSV. Methods After confirmation of RSV infection or 5 days after inoculation with RSV, participants (n = 69) were randomized to JNJ-53718678 75 mg (n = 15), 200 mg (n = 17), 500 mg (n = 18), or placebo (n = 17) orally once daily for 7 days. Antiviral effects were evaluated by assessing RSV RNA viral load (VL) area under the curve (AUC) from baseline (before the first dose) until discharge, time-to-peak VL, duration of viral shedding, clinical symptoms, and quantity of nasal secretions. Results Mean VL AUC was lower for individuals treated with different doses of JNJ-53718678 versus placebo (203.8-253.8 vs 432.8 log10 PFUe.hour/mL). Also, mean peak VL, time to peak VL, duration of viral shedding, mean overall symptom score, and nasal secretion weight were lower in each JNJ-53718678-treated group versus placebo. No clear exposure-response relationship was observed. Three participants discontinued due to treatment-emergent adverse events of grade 2 and 1 electrocardiogram change (JNJ-53718678 75 mg and 200 mg, respectively) and grade 2 urticaria (placebo). Conclusions JNJ-53718678 at all 3 doses substantially reduced VL and clinical disease severity, thus establishing clinical proof of concept and the compounds potential as a novel RSV treatment. Clinical trials registration ClinicalTrials.gov: NCT02387606; EudraCT number: 2014-005041-41.

In vitro and in silico analysis of the effects of D2 receptor antagonist target binding kinetics on the cellular response to fluctuating dopamine concentrations

Target binding kinetics influence the time course of the drug effect (pharmacodynamics) both (i) directly, by affecting the time course of target occupancy, driven by the pharmacokinetics of the drug, competition with endogenous ligands and target turnover, and (ii) indirectly, by affecting signal transduction and homeostatic feedback. For dopamine D2 receptor antagonists, it has been hypothesized that fast receptor binding kinetics cause fewer side effects, because part of the dynamics of the dopaminergic system is preserved by displacement of these antagonists.