Population pharmacokinetics of serelaxin in patients with acute or chronic heart failure, hepatic or renal impairment, or portal hypertension and in healthy subjects.

AIMS: Serelaxin is a recombinant human relaxin-2 peptide being developed for the treatment of acute heart failure (AHF). The present analyses aimed to evaluate serelaxin pharmacokinetics following intravenous administration and to identify covariates that may explain pharmacokinetic variability in healthy subjects and patients. METHODS: Serum concentration-time data for 613 subjects from nine phase I and II studies were analysed using a nonlinear mixed-effects model to estimate population pharmacokinetics and identify significant covariates. A quantile regression analysis was also conducted to assess the relationship between clearance and covariates by including sparse data from a phase III study. RESULTS: A three-compartment disposition model was established to describe serelaxin pharmacokinetics. Three out of 23 covariates, including baseline body mass index (BMI) and estimated glomerular filtration rate (eGFR) and study A1201, were identified as significant covariates for clearance but with a moderate impact on steady-state concentration, reducing the intersubject variability from 44% in the base model to 41% in the final model with covariates. The steady-state volume of distribution (Vss) was higher in patients with AHF (544 ml kg-1 ) or chronic heart failure (434 ml kg-1 ), compared with typical nonheart failure subjects (347 ml kg-1 ). Quantile regression analysis showed that a 20% increase in BMI or a 20% decrease in eGFR decreased serelaxin clearance by 9.2% or 5.2%, respectively. CONCLUSIONS: Patients with HF showed higher Vss but similar clearance (and therefore steady-state exposure) vs. non nonheart failure subjects. BMI and eGFR were identified as the main covariates explaining intersubject variability in clearance; however, the impact of these covariates on steady-state concentration was moderate and therefore unlikely to be clinically relevant.

Pharmacokinetic/Pharmacodynamic Modeling of Renin-Angiotensin Aldosterone Biomarkers Following Angiotensin-Converting Enzyme (ACE) Inhibition Therapy with Benazepril in Dogs.

PURPOSE: The objective of this research was to provide a comprehensive description of the effect of benazepril on the dynamics of the renin-angiotensin aldosterone system (RAAS) in dogs. METHODS: Blood specimens for renin activity (RA), angiotensin II (AII), and aldosterone (ALD) quantitation in plasma were drawn from 12 healthy adult beagle dogs randomly allocated to 2 treatment groups: (i) benazepril 5 mg PO, q24 h (n: 6) and (ii) placebo (n: 6), in a cross-over design. A mechanism-based pharmacokinetic/pharmacodynamic model, which includes the periodic nature of RA, AII, and ALD during placebo treatment and the subsequent changes in dynamics following repeated dosing with benazepril, was developed. RESULTS: The disposition kinetics of benazepril active metabolite, benazeprilat, was characterized using a saturable binding model to the angiotensin converting enzyme. The modulatory effect of benazeprilat on the RAAS was described using a combination of immediate response models. Our data show that benazepril noticeably influences the dynamics of the renin cascade, resulting in a substantial decrease in AII and ALD, while increasing RA throughout the observation span. CONCLUSIONS: The model provides a quantitative framework for better understanding the effect of ACE inhibition on the dynamics of the systemic RAAS in dogs.

A model-based approach for historical borrowing, with an application to neovascular age-related macular degeneration.

Bayesian historical borrowing has recently attracted growing interest due to the increasing availability of historical control data, as well as improved computational methodology and software. In this article, we argue that the statistical models used for borrowing may be suboptimal when they do not adjust for differing factors across historical studies such as covariates, dosing regimen, etc. We propose an alternative approach to address these shortcomings. We start by constructing a historical model based on subject-level historical data to accurately characterize the control treatment by adjusting for known between trials differences. This model is subsequently used to predict the control arm response in the current trial, enabling the derivation of a model-informed prior for the treatment effect parameter of another (potentially simpler) model used to analyze the trial efficacy (i.e. the trial model). Our approach is applied to neovascular age-related macular degeneration trials, employing a cross-sectional regression trial model, and a longitudinal non-linear mixed-effects drug-disease-trial historical model. The latter model characterizes the relationship between clinical response, drug exposure and baseline covariates so that the derived model-informed prior seamlessly adapts to the trial population and can be extrapolated to a different dosing regimen. This approach can yield a more accurate prior for borrowing, thus optimizing gains in efficiency (e.g. increasing power or reducing the sample size) in future trials.

Mitigating Drug-Target-Drug Complexes in Patients With Paroxysmal Nocturnal Hemoglobinuria Who Switch C5 Inhibitors.

Drug-target-drug complexes (DTDCs) are phenomena newly observed in patients who switch from the complement component 5 (C5) inhibitor eculizumab to crovalimab, a novel, anti-C5 antibody in development for paroxysmal nocturnal hemoglobinuria (PNH), because these agents bind to different C5 epitopes. In Part 3 of the four-part, phase I/II COMPOSER study, 19 patients with PNH switching from eculizumab received 1,000-mg crovalimab intravenously, then subcutaneous maintenance doses from Day 8 (680 mg every 4 weeks (q4w), 340 mg every 2 weeks, or 170 mg every week). Crovalimab exposure was transiently reduced, and size-exclusion chromatography and crovalimab-specific enzyme-linked immunosorbent assays revealed DTDCs in all 19 patients' sera. Additionally, self-limiting mild to moderate symptoms suggestive of type III hypersensitivity reactions occurred in two patients. Mathematical modeling simulations of DTDC kinetics and effects of dosing on DTDC size distribution using Part 3 data predicted that increased crovalimab concentrations could reduce the proportion of large, slow-clearing DTDCs in the blood. A simulation-guided, optimized crovalimab regimen (1,000 mg intravenously; four weekly, subcutaneous 340-mg doses; then 680 mg q4w from Day 29) was evaluated in Part 4. Confirming the model's predictions, mean proportions of large DTDCs in patients who switched from eculizumab to this optimized regimen decreased by > 50% by Day 22, and target crovalimab concentrations were maintained. No type III hypersensitivity reactions occurred in Part 4. Optimizing crovalimab dosing thus reduced the proportion of large DTDCs, ensured adequate complement inhibition, and may improve safety. Model-based dosing optimization to mitigate DTDC formation offers a useful strategy for patients switching to novel antibody treatments targeting soluble epitopes.

Models and Machines: How Deep Learning Will Take Clinical Pharmacology to the Next Level.

Recent advances in machine learning (ML) have led to enthusiasm about its use throughout the biopharmaceutical industry. The ML methods can be applied to a wide range of problems and have the potential to revolutionize aspects of drug development. The incorporation of ML in modeling and simulation (M&S) has been eagerly anticipated, and in this perspective, we highlight examples in which ML and M&S approaches can be integrated as complementary parts of a clinical pharmacology workflow.

Surface Reconstruction for free-space 360 degrees fluorescence molecular tomography and the effects of animal motion.

Complete projection (360 degrees ) free-space fluorescence tomography of opaque media is poised to enable 3-D imaging through entire small animals in vivo with improved depth resolution compared to 360 degrees -projection fiber-based systems or limited-view angle systems. This approach can lead to a new generation of Fluorescence Molecular Tomography (FMT) performance since it allows high spatial sampling of photon fields propagating through tissue at any projection, employing nonconstricted animal surfaces. Herein, we employ a volume carving method to capture 3-D surfaces of diffusive objects and register the captured surface in the geometry of an FMT 360 degrees -projection acquisition system to obtain 3-D fluorescence image reconstructions. Using experimental measurements we evaluate the accuracy of the surface capture procedure by reconstructing the surfaces of phantoms of known dimensions. We then employ this methodology to characterize the animal movement of anaesthetized animals. We find that the effects of animal movement on the FMT reconstructed image were within system resolution limits (approximately 0.07 cm).

Inversion with early photons.

Optical tomography using early photons can improve resolution and reduce the ill-posed nature of the inversion problem. In this work we use 360 degrees projection experimental data to investigate the inversion performance of three commonly used numerical inversion methods: the random algebraic reconstruction technique (rART), singular value decomposition (SVD), and the conjugate-gradient-type method LSQR. Results are contrasted to each other and the effects of different photon propagation models are also investigated. We find that all methods perform adequately given appropriate regularization parameters, and that an experimentally measured photon weight function yields superior results over two approximate weights that have been previously used.

Fluorescence molecular tomography in the presence of background fluorescence.

Fluorescence molecular tomography is an emerging imaging technique that resolves the bio-distribution of engineered fluorescent probes developed for in vivo reporting of specific cellular and sub-cellular targets. The method can detect fluorochromes in picomole amounts or less, imaged through entire animals, but the detection sensitivity and imaging performance drop in the presence of background, non-specific fluorescence. In this study, we carried out a theoretical and an experimental investigation on the effect of background fluorescence on the measured signal and on the tomographic reconstruction. We further examined the performance of three subtraction methods based on physical models of photon propagation, using experimental data on phantoms and small animals. We show that the data pre-processing with subtraction schemes can improve image quality and quantification when non-specific background florescence is present.

Planar fluorescence imaging using normalized data.

Fluorescence imaging of tissues has gained significant attention in recent years due to the emergence of appropriate reporter technologies that enable noninvasive sensing of molecular function in vivo. Two major approaches have been used so far for fluorescence molecular imaging, i.e., epi-illumination (reflectance) imaging and fluorescence molecular tomography. Transillumination is an alternative approach that has been employed for imaging tissues in the past and could be similarly beneficial for fluorescence molecular imaging. We investigate data normalization schemes in reflectance and transillumination mode and experimentally demonstrate that normalized transillumination offers significant advantages over planar reflectance imaging and over nonnormalized methods. Our observations, based on phantoms and on postmortem and in vivo mouse measurements display image quality improvement, superior depth sensitivity, and improved imaging accuracy over the nonnormalized methods examined. Normalized planar imaging retains implementation simplicity and could be used to improve on standard fluorescence reflectance imaging and as a simplified alternative to the more integrated and accurate tomographic methods.

Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio.

We studied the performance of three-dimensional fluorescence tomography of diffuse media in the presence of heterogeneities. Experimental measurements were acquired using an imaging system consisting of a parallel plate-imaging chamber and a lens coupled charge coupled device camera, which enables conventional planar imaging as well as fluorescence tomography. To simulate increasing levels of background heterogeneity, we employed phantoms made of a fluorescent tube surrounded by several absorbers in different combinations of absorption distribution. We also investigated the effect of low absorbing thin layers (such as membranes). We show that the normalized Born approach accurately retrieves the position and shape of the fluorochrome even at high background heterogeneity. We also demonstrate that the quantification is relatively insensitive to a varying degree of heterogeneity and background optical properties. Findings are further contrasted to images obtained with the standard Born expansion and with a normalized approach that divides the fluorescent field with excitation measurements through a homogeneous medium.

Modeling and simulation of preclinical cardiac safety: towards an integrative framework.

Despite an impressive battery of preclinical cardiac electrophysiology experimental models and the assessment of QT during clinical trials, the risk of Torsades de Pointes (TdP), a potentially lethal ventricular arrhythmia, remains among the common reasons for drug market withdrawal or lack of approval. Due to the low prevalence of TdP, development of statistical evidence that other clinical markers could be better predictors of TdP has proven challenging. Preclinical studies have provided a deeper understanding of torsadogenic mechanisms and potential pro-arrhythmic markers to assess. Translating these preclinical insights into a quantitative clinical risk assessment remains challenging because of (i) species differences in cardiac electrophysiology and drug pharmacokinetics; and (ii) the inability to measure clinically specific cardiac electrophysiology metrics, and therefore ascertain the full predictive value of earlier preclinical components of the risk assessment process. The integrative capacity of cardiac electrophysiology modeling to span time and length scales may provide a quantitative and predictive framework, to complement expert-based preclinical-to-clinical cardiac risk assessment process. In this review, we present salient elements of this risk assessment process and describe essential components of cardiac electrophysiology modeling, to propose that a progressive integration of mechanistic components into a common quantitative framework may help improve the predictability of drug-induced TdP risk.

Free-space fluorescence molecular tomography utilizing 360 degrees geometry projections.

Fluorescence tomography of diffuse media can yield optimal three-dimensional imaging when multiple projections over 360 degrees geometries are captured, compared with limited projection angle systems such as implementations in the slab geometry. We demonstrate how it is possible to perform noncontact, 360 degrees projection fluorescence tomography of mice using CCD-camera-based detection in free space, i.e., in the absence of matching fluids. This approach achieves high spatial sampling of photons propagating through tissue and yields a superior information content data set compared with fiber-based 360 degrees implementations. Reconstruction feasibility using 36 projections in 10 degrees steps is demonstrated in mice.

In-vivo lung cancer imaging in mice using 360 degrees free-space fluorescence molecular tomography.

We present the development and performance characteristics of a free-space fluorescence tomography system. The imaging system can capture complete angle projections of photons propagating through tissue in transillumination using a CCD camera. Experimental data on imaging lung cancer are presented. Overall, this imaging approach can offer unprecedented imaging performance in fluorescence molecular tomography of small animals.

Complete-angle projection diffuse optical tomography by use of early photons.

We present the first, to our knowledge, experimental images of complex-shaped phantoms embedded in diffuse media by use of optical tomography. Imaging is based on a complete-angle projection tomographic technique that utilizes transmitted early photons. Results are contrasted with measurements obtained at later gates as well as pseudocontinuous-wave data. The scanning system developed employs noncontact illumination and detection technologies that allow for high spatial sampling of transmitted photons. Combining this system with complete-angle illumination is found to be an important strategy toward improved imaging performance, resulting in a better-posed inversion problem. The appropriateness of reconstruction algorithms similar to those employed in x-ray computed tomography are showcased, and suggestions for model improvements are provided.

Effects of background fluorescence in fluorescence molecular tomography.

Recent advances in optical imaging systems and systemically administered fluorescent probes have significantly improved the ways by which we can visualize proteomics in vivo. A key component in the design of fluorescent probes is a favorable biodistribution, i.e., localization only in the targeted diseased tissue, in order to achieve high contrast and good detection characteristics. In practice, however, there is always some level of background fluorescence present that could result in distorted or obscured visualization and quantification of measured signals. In this study we observe the effects of background fluorescence in tomographic imaging. We demonstrate that increasing levels of background fluorescence result in artifacts when using a linear perturbation algorithm, along with a significant loss of image fidelity and quantification accuracy. To correct for effects of background fluorescence, we have applied cubic polynomial fits to bulk raw measurements obtained from spatially homogeneous and heterogeneous phantoms. We show that subtraction of the average fluorescence response from the raw data before reconstruction can improve image quality and quantification accuracy as shown in relatively homogeneous or heterogeneous phantoms. Subtraction methods thus appear to be a promising route for adaptively correcting nonspecific background fluorochrome distribution.