Recommended Guidelines for Developing, Qualifying, and Implementing Complex In Vitro Models (CIVMs) for Drug Discovery.

The pharmaceutical industry is continuing to face high research and development (R&D) costs and low overall success rates of clinical compounds during drug development. There is an increasing demand for development and validation of healthy or disease-relevant and physiological human cellular models that can be implemented in early-stage discovery, thereby shifting attrition of future therapeutics to a point in discovery at which the costs are significantly lower. There needs to be a paradigm shift in the early drug discovery phase (which is lengthy and costly), away from simplistic cellular models that show an inability to effectively and efficiently reproduce healthy or human disease-relevant states to steer target and compound selection for safety, pharmacology, and efficacy questions. This perspective article covers the various stages of early drug discovery from target identification (ID) and validation to the hit/lead discovery phase, lead optimization, and preclinical safety. We outline key aspects that should be considered when developing, qualifying, and implementing complex in vitro models (CIVMs) during these phases, because criteria such as cell types (e.g., cell lines, primary cells, stem cells, and tissue), platform (e.g., spheroids, scaffolds or hydrogels, organoids, microphysiological systems, and bioprinting), throughput, automation, and single and multiplexing endpoints will vary. The article emphasizes the need to adequately qualify these CIVMs such that they are suitable for various applications (e.g., context of use) of drug discovery and translational research. The article ends looking to the future, in which there is an increase in combining computational modeling, artificial intelligence and machine learning (AI/ML), and CIVMs.

In Vivo Imaging of Small Molecular Weight Peptides for Targeted Renal Drug Delivery: A Study in Normal and Polycystic Kidney Diseased Mice.

Autosomal dominant polycystic kidney disease (ADPKD) is a leading monogenetic cause of end-stage renal disease with limited therapeutic repertoire. A targeted drug delivery strategy that directs a small molecule to renal niches around cysts could increase the safety margins of agents that slow the progression of ADPKD but are poorly tolerated due to extrarenal toxicity. Herein, we determined whether previously characterized lysine-based and glutamic acid-based megalin-binding peptides can achieve renal-specific localization in the juvenile cystic kidney (JCK) mouse model of polycystic kidney disease and whether the distribution is altered compared with control mice. We performed in vivo optical and magnetic resonance imaging studies using peptides conjugated to the VivoTag 680 dye and demonstrated that megalin-interacting peptides distributed almost exclusively to the kidney cortex in both normal and JCK mice. Confocal analysis demonstrated that the peptide-dye conjugate distribution overlapped with megalin-positive renal proximal tubules. However, in the JCK mouse, the epithelium of renal cysts did not retain expression of the proximal tubule markers aquaporin 1 and megalin, and therefore these cysts did not retain peptide-dye conjugates. Furthermore, human kidney tumor tissues were evaluated by immunohistochemistry and revealed significant megalin expression in tissues from patients with renal cell carcinoma, raising the possibility that these tumors could be treated using this drug delivery strategy. Taken together, our data suggest that linking a small-molecule drug to these carrier peptides could represent a promising opportunity to develop a new platform for renal enrichment and targeting in the treatment of ADPKD and certain renal carcinomas.

Selective Spectrum Antibiotic Modulation of the Gut Microbiome in Obesity and Diabetes Rodent Models.

The gastrointestinal tract microbiome has been suggested as a potential therapeutic target for metabolic diseases such as obesity and Type 2 diabetes mellitus (T2DM). However, the relationship between changes in microbial communities and metabolic disease-phenotypes are still poorly understood. In this study, we used antibiotics with markedly different antibacterial spectra to modulate the gut microbiome in a diet-induced obesity mouse model and then measured relevant biochemical, hormonal and phenotypic biomarkers of obesity and T2DM. Mice fed a high-fat diet were treated with either ceftazidime (a primarily anti-Gram negative bacteria antibiotic) or vancomycin (mainly anti-Gram positive bacteria activity) in an escalating three-dose regimen. We also dosed animals with a well-known prebiotic weight-loss supplement, 10% oligofructose saccharide (10% OFS). Vancomycin treated mice showed little weight change and no improvement in glycemic control while ceftazidime and 10% OFS treatments induced significant weight loss. However, only ceftazidime showed significant, dose dependent improvement in key metabolic variables including glucose, insulin, protein tyrosine tyrosine (PYY) and glucagon-like peptide-1 (GLP-1). Subsequently, we confirmed the positive hyperglycemic control effects of ceftazidime in the Zucker diabetic fatty (ZDF) rat model. Metagenomic DNA sequencing of bacterial 16S rRNA gene regions V1-V3 showed that the microbiomes of ceftazidime dosed mice and rats were enriched for the phylum Firmicutes while 10% OFS treated mice had a greater abundance of Bacteroidetes. We show that specific changes in microbial community composition are associated with obesity and glycemic control phenotypes. More broadly, our study suggests that in vivo modulation of the microbiome warrants further investigation as a potential therapeutic strategy for metabolic diseases.

Rosiglitazone Induces Mitochondrial Biogenesis in Differentiated Murine 3T3-L1 and C3H/10T1/2 Adipocytes.

Growing evidence indicates that PPARγ agonists, including rosiglitazone (RSG), induce adipose mitochondrial biogenesis. By systematically analyzing mitochondrial gene expression in two common murine adipocyte models, the current study aimed to further establish the direct role of RSG and capture temporal changes in gene transcription. Microarray profiling revealed that in fully differentiated 3T3-L1 and C3H/10T1/2 adipocytes treated with RSG or DMSO vehicle for 1, 2, 4, 7, 24, and 48 hrs, RSG overwhelmingly increased mitochondrial gene transcripts time dependently. The timing of the increases was consistent with the cascade of organelle biogenesis, that is, initiated by induction of transcription factor(s), followed by increases in the biosynthesis machinery, and then by increases in functional components. The transcriptional increases were further validated by increased mitochondrial staining, citrate synthase activity, and O(2) consumption, and were found to be associated with increased adiponectin secretion. The work provided further insight on the mechanism of PPARγ-induced mitochondrial biogenesis in differentiated adipocytes.