Advanced analysis of disintegrating pharmaceutical compacts using deep learning-based segmentation of time-resolved micro-tomography images.

The mechanism governing pharmaceutical tablet disintegration is far from fully understood. Despite the importance of controlling a formulation's disintegration process to maximize the active pharmaceutical ingredient's bioavailability and ensure predictable and consistent release profiles, the current understanding of the process is based on indirect or superficial measurements. Formulation science could, therefore, additionally deepen the understanding of the fundamental physical principles governing disintegration based on direct observations of the process. We aim to help bridge the gap by generating a series of time-resolved X-ray micro-computed tomography (µCT) images capturing volumetric images of a broad range of mini-tablet formulations undergoing disintegration. Automated image segmentation was a prerequisite to overcoming the challenges of analyzing multiple time series of heterogeneous tomographic images at high magnification. We devised and trained a convolutional neural network (CNN) based on the U-Net architecture for autonomous, rapid, and consistent image segmentation. We created our own µCT data reconstruction pipeline and parameterized it to deliver image quality optimal for our CNN-based segmentation. Our approach enabled us to visualize the internal microstructures of the tablets during disintegration and to extract parameters of disintegration kinetics from the time-resolved data. We determine by factor analysis the influence of the different formulation components on the disintegration process in terms of both qualitative and quantitative experimental responses. We relate our findings to known formulation component properties and established experimental results. Our direct imaging approach, enabled by deep learning-based image processing, delivers new insights into the disintegration mechanism of pharmaceutical tablets.

Zebrafish (Danio rerio) larvae as a predictive model to study gentamicin-induced structural alterations of the kidney.

Nephrotoxicity is an important drug safety aspect to be assessed during drug discovery and development. To study renal toxicity, in vitro cell-based assays are often used. Unfortunately, translating the results of such cell assays to vertebrates including human remains challenging. Therefore, we aim to evaluate whether zebrafish larvae (ZFL) could serve as a vertebrate screening model to detect gentamicin-induced changes of kidney glomeruli and proximal tubules. To validate the model, we compared the results of ZFL with those obtained from kidney biopsies of gentamicin-treated mice. We used transgenic zebrafish lines expressing enhanced green fluorescent proteins in the glomerulus to visualize glomerular damage. Synchrotron radiation-based computed tomography (SRµCT) is a label-free approach providing three-dimensional representations of renal structures with micrometre resolution. Clinically used gentamicin concentrations induce nephrotoxicity and affect glomerular and proximal tubular morphology. Findings were confirmed in mice and ZFL. There was a strong correlation between fluorescent signals in ZFL, SRµCT- derived descriptors of glomerular and proximal tubular morphology and the histological analysis of mouse kidney biopsies. A combination of SRµCT and confocal microscopy provides unprecedented insights into anatomical structures of the zebrafish kidney. Based on our findings, we suggest to use ZFL as a predictive vertebrate screening model to study drug-induced nephrotoxicity and to bridge the gap between cell culture-based test systems and experiments in mammals.

Particle Forming Amorphous Solid Dispersions: A Mechanistic Randomized Pharmacokinetic Study in Humans.

Amorphous solid dispersions (ASDs) are a promising drug-delivery strategy to overcome poor solubility through formulation. Currently, the understanding of drug absorption mechanisms from ASDs in humans is incomplete. Aiming to gain insights in this matter, we conducted a randomized cross-over design open-label clinical study (NCT03886766) with 16 healthy male volunteers in an ambulatory setting, using micro-dosed efavirenz as a model drug. In three phases, subjects were administered (1) solid ASD of efavirenz 50 mg or (2) dissolved ASD of efavirenz 50 mg or (3) a molecular solution of efavirenz 3 mg (non-ASD) as a control in block-randomized order. Endpoints were the pharmacokinetic profiles (efavirenz plasma concentration vs. time curves) and derived pharmacokinetic parameters thereof (AUC0-t, Cmax, tmax, and ka). Results showed that the dissolved ASD (intervention 2) exhibited properties of a supersaturated solution (compared to aqueous solubility) with rapid and complete absorption of the drug from the drug-rich particles. All interventions showed similar AUC0-t and were well tolerated by subjects. The findings highlight the potential of particle forming ASDs as an advanced drug-delivery system for poorly soluble drugs and provide essential insights into underlying mechanisms of ASD functioning in humans, partially validating current conceptual models.