The power of modelling pulsatile profiles

The quantitative description of individual observations in non-linear mixed effects models over time is complicated when the studied biomarker has a pulsatile release (e.g. insulin, growth hormone, luteinizing hormone). Unfortunately, standard non-linear mixed effects population pharmacodynamic models such as turnover and precursor response models (with or without a cosinor component) are unable to quantify these complex secretion profiles over time. In this study, the statistical power of standard statistical methodology such as 6 post-dose measurements or the area under the curve from 0 to 12 h post-dose on simulated dense concentration-time profiles of growth hormone was compared to a deconvolution-analysis-informed modelling approach in different simulated scenarios. The statistical power of the deconvolution-analysis-informed approach was determined with a Monte-Carlo Mapped Power analysis. Due to the high level of intra- and inter-individual variability in growth hormone concentrations over time, regardless of the simulated effect size, only the deconvolution-analysis informed approach reached a statistical power of more than 80% with a sample size of less than 200 subjects per cohort. Furthermore, the use of this deconvolution-analysis-informed modelling approach improved the description of the observations on an individual level and enabled the quantification of a drug effect to be used for subsequent clinical trial simulations

Quantification of the endogenous growth hormone and prolactin lowering effects of a somatostatin-dopamine chimera using population PK/PD modeling

A phase 1 clinical trial in healthy male volunteers was conducted with a somatostatin-dopamine chimera (BIM23B065), from which information could be obtained on the concentration-effect relationship of the inhibition of pulsatile endogenous growth hormone and prolactin secretion. Endogenous growth hormone profiles were analyzed using a two-step deconvolution-analysis-informed population pharmacodynamic modeling approach, which was developed for the analyses of pulsatile profiles. Prolactin concentrations were modelled using a population pool model with a circadian component on the prolactin release. During treatment with BIM23B065, growth hormone secretion was significantly reduced (maximal effect [E-MAX] = - 64.8%) with significant reductions in the pulse frequency in two out of three multiple ascending dose cohorts. A circadian component in prolactin secretion was identified, modelled using a combination of two cosine functions with 24 h and 12 h periods. Dosing of BIM23B065 strongly inhibited (E-MAX = - 91%) the prolactin release and demonstrated further reduction of prolactin secretion after multiple days of dosing. This study quantified the concentration-effect relationship of BIM23B065 on the release of two pituitary hormones, providing proof of pharmacology of the chimeric actions of BIM23B065

A two-step deconvolution-analysis-informed population pharmacodynamic modeling approach for drugs targeting pulsatile endogenous compounds

Pharmacodynamic modeling of pulsatile endogenous compounds (e.g. growth hormone [GH]) is currently limited to the identification of a low number of pulses. Commonly used pharmacodynamic models are not able to capture the complexity of pulsatile secretion and therefore non-compartmental analyses are performed to extract summary statistics (mean, AUC, Cmax). The aim of this study was to develop a new quantification method that deals with highly variable pulsatile data by using a deconvolution-analysis-informed population pharmacodynamic modeling approach. Pulse frequency and pulse times were obtained by deconvolution analysis of 24 h GH profiles. The estimated pulse times then informed a non-linear mixed effects population pharmacodynamic model in NONMEM V7.3. The population parameter estimates were used to perform simulations that show agonistic and antagonistic drug effects on the secretion of GH. Additionally, a clinical trial simulation shows the application of this method in the quantification of a hypothetical drug effect that inhibits GH secretion. The GH profiles were modeled using a turnover compartment in which the baseline secretion, kout, pulse secretion width, amount at time point 0 and pulse amplitude were estimated as population parameters. Population parameters were estimated with low relative standard errors (ranging from 2 to 5%). Total body water (%) was identified as a covariate for pulse amplitude, baseline secretion and the pulse secretion width following a power relationship. Simulations visualized multiple gradients of a hypothetical drug that influenced the endogenous secretion of GH. The established model was able to fit and quantify the highly variable individual 24 h GH profiles over time. This pharmacodynamic model can be used to quantify drug effects that target other endogenous pulsatile compounds.</p

Variabiliteit in farmacokinetiek van intraveneuze paracetamol bij gezonde ouderen

BACKGROUND and OBJECTIVE: Paracetamol is the most used analgesic in older people. The physiological changes occurring with ageing influence the pharmacokinetics of paracetamol and its variability. A population pharmacokinetic analysis to describe the pharmacokinetics of intravenous paracetamol in fit older people was performed. Thereafter, simulations were conducted to illustrate target attainment and variability of paracetamol exposure following current dosing regimens (1000 mg q6h, q8h) using steady-state concentration (Cssmean) of 10 mg/L as target for effective analgesia. DESIGN and METHODS: A population pharmacokinetic-analysis, using NONMEM 7.2, was performed based on 601 concentrations of paracetamol from 30 fit older people (median age = 77.3 years [61.8- 88.5], body weight = 79 kg [60-107]). All had received an intravenous paracetamol dose of 1000 mg – over 15 min – after elective knee surgery. RESULTS: A two-compartment pharmacokinetic-model best described the data. Volume of distribution of paracetamol increased exponentially with body weight. Clearance was not influenced by any covariate. Simulations of the standardized dosing regimens resulted in a Css-mean of 9.2 mg/L (q6h) and 7.2 mg/L (q8h). Variability in paracetamol pharmacokinetics resulted in a Css-mean above 5.4 (q6h) and 4.1 mg/L (q8h) in 90%, and above 15.5 (q6h) and 11.7 mg/L (q8h) in 10% of the population. CONCLUSION: The target concentration was achieved in the average patient with 1000 mg q6h, while q8h resulted in underdosing for the majority of the population. Due to large unexplained interindividual variability in paracetamol pharmacokinetics a relevant proportion of the fit older people remained either under- or overexposed

Effects of mexiletine and lacosamide on nerve excitability in healthy subjects: a randomized, double-blind, placebo-controlled, crossover study

Selective voltage-gated sodium channel blockers are of growing interest as treatment for pain. For drug development of such compounds, it would be critical to have a biomarker that can be used for proof-of-mechanism. We aimed to evaluate whether drug-induced changes in sodium conductance can be detected in the peripheral nerve excitability profile in 18 healthy subjects. In a randomized, double-blind, 3-way crossover study, effects of single oral doses of 333 mg mexiletine and 300 mg lacosamide were compared with placebo. On each study visit, motor and sensory nerve excitability measurements of the median nerve were performed (predose; and 3 and 6 hours postdose) using Qtrac. Treatment effects were calculated using an analysis of covariance (ANCOVA) with baseline as covariate. Mexiletine and lacosamide had significant effects on multiple motor and sensory nerve excitability variables. Depolarizing threshold electrotonus (TEd40 (40–60 ms)) decreased by mexiletine (estimated difference (ED) −1.37% (95% confidence interval (CI): −2.20, −0.547; P = 0.002) and lacosamide (ED −1.27%, 95% CI: −2.10, −0.443; P = 0.004) in motor nerves. Moreover, mexiletine and lacosamide decreased superexcitability (less negative) in motor nerves (ED 1.74%, 95% CI: 0.615, 2.87; P = 0.004, and ED 1.47%, 95% CI: 0.341, 2.60; P = 0.013, respectively). Strength-duration time constant decreased after lacosamide in motor- (ED −0.0342 ms, 95% CI: −0.0571, −0.0112; P = 0.005) and sensory nerves (ED −0.0778 ms, 95% CI: −0.116, −0.0399; P < 0.001). Mexiletine and lacosamide significantly decrease excitability of motor and sensory nerves, in line with their suggested mechanism of action. Results of this study indicate that nerve excitability threshold tracking can be an effective pharmacodynamic biomarker. The method could be a valuable tool in clinical drug development

Impact of enantiomer-specific changes in pharmacokinetics between infants and adults on the target concentration of racemic ketorolac– a pooled analysis

Aims Ketorolac is a non-steroidal anti-inflammatory racemic drug with analgesic effects only attributed to its S-enantiomer. The aim of this study is to quantify enantiomer-specific maturational pharmacokinetics (PK) of ketorolac and investigate if the contribution of both enantiomers to the total ketorolac concentration remains equal between infants and adults or if a change in target racemic concentration should be considered when applied to infants. Methods Data were pooled from 5 different studies in adults, children, and infants, with 1020 plasma concentrations following single intravenous ketorolac administration. An allometry-based enantiomer-specific population PK model was developed with NONMEM 7.3. Simulations were performed in typical adults and infants to investigate differences in S- and R-ketorolac exposure. Results S- and R-ketorolac PK were best described with a 3- and a 2-compartment model respectively. The allometry-based PK parameters accounted for changes between populations. No maturation function of ketorolac clearance could be identified. All model parameters were estimated with adequate precision (relative standard errorPeer reviewe

The quantification of growth hormone secretion:Application of model-informed drug development in acromegaly

Growth hormone profiles are pulsatile and highly variable between individuals, limiting the implementation of mathematical models to quantify an individual's secretion. In this thesis, five key topics regarding the quantification of growth hormone (GH) in literature and the application in (future) clinical trials were addressed consecutively: 1. The current standards in reporting clinical trial outcomes in acromegaly patients were assessed and recommendations for future reporting were provided 2. A new deconvolution-informed population pharmacodynamic model was developed and validated for the quantification of drug effects on pulsatile profiles 3. Population pharmacokinetic/pharmacodynamic models were developed to better understand the clinical pharmacological properties of BIM23B065 to support decision making and future clinical trial design 4. A population model for GH secretion based on physiological information, including a GHRH pulse generator, was developed based on data from different experiments to be used for the simulation of pulsatile GH profiles in healthy controls, active acromegaly patients and acromegaly patient after surgery. 5. The impact of different sampling protocols, ranging from a single sample to a 24h GH profile, on the study power and classification of responders in GH research were quantified and implementation of the research methodology in new scenarios was stimulated