Large-Scale Screening of Pharmaceutical Compounds to Explore the Application Space of On-Tissue MALDI and MALDI-2 Mass Spectrometry.

The successful application of matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) in pharmaceutical research is strongly dependent on the detection of the drug of interest at physiologically relevant concentrations. Here we explored how insufficient sensitivity due to low ionization efficiency and/or the interaction of the drug molecule with the local biochemical environment of the tissue can be mitigated for many compound classes using the recently introduced MALDI-MSI coupled with laser-induced postionization, known as MALDI-2-MSI. Leveraging a MALDI-MSI screen of about 1,200 medicines/drug-like compounds from a broad range of medicinal application areas, we demonstrate a significant improvement in drug detection and the degree of sensitivity uplift by using MALDI-2 versus traditional MALDI. Our evaluation was made under simulated imaging conditions using liver homogenate sections as substrate, onto which the compounds were spotted to mimic biological conditions to the first order. To enable an evaluable detection by both MALDI and MALDI-2 for the majority of employed compounds, we spotted 1 µL of a 10 mM solution using a spotting robot and performed our experiments with a Bruker timsTOF fleX MALDI-2 instrument in both positive and negative ion modes. Specifically, we demonstrate using a large cohort of drug-like compounds that ∼60% of the tested compounds showed a more than 10-fold increase in signal intensity and ∼16% showed a more than 100-fold increase upon use of MALDI-2 postionization. Such increases in sensitivity could help advance pharmaceutical MALDI-MSI applications toward the single-cell level.

Multimodal imaging distribution assessment of a liposomal antibiotic in an infectious disease model.

Liposomes are promising targeted drug delivery systems with the potential to improve the efficacy and safety profile of certain classes of drugs. Though attractive, there are unique analytical challenges associated with the development of liposomal drugs including human dose prediction given these are multi-component drug delivery systems. In this study, we developed a multimodal imaging approach to provide a comprehensive distribution assessment for an antibacterial drug, GSK2485680, delivered as a liposomal formulation (Lipo680) in a mouse thigh model of bacterial infection to support human dose prediction. Positron emission tomography (PET) imaging was used to track the in vivo biodistribution of Lipo680 over 48 h post-injection providing a clear assessment of the uptake in various tissues and, importantly, the selective accumulation at the site of infection. In addition, a pharmacokinetic model was created to evaluate the kinetics of Lipo680 in different tissues. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) was then used to quantify the distribution of GSK2485680 and to qualitatively assess the distribution of a liposomal lipid throughout sections of infected and non-infected hindlimb tissues at high spatial resolution. Through the combination of both PET and MALDI IMS, we observed excellent correlation between the Lipo680-radionuclide signal detected by PET with the GSK2485680 and lipid component signals detected by MALDI IMS. This multimodal translational method can reduce drug attrition by generating comprehensive biodistribution profiles of drug delivery systems to provide mechanistic insight and elucidate safety concerns. Liposomal formulations have potential to deliver therapeutics across a broad array of different indications, and this work serves as a template to aid in delivering future liposomal drugs to the clinic.

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.

PelvicSim--a computational-experimental system for biomechanical evaluation of female pelvic floor organ disorders and associated minimally invasive interventions.

In this paper we describe the prototype of a new computational simulation system, PelvicSim. This system is being developed to simulate the in vivo biomechanics of the female pelvic floor organ system with the intent to provide clinical researchers, medical device designers with a virtual environment to understand the various biomechanical pathologies occurring in the pelvic floor. This information can then be used to develop new reconstructive surgical techniques, or design non surgical/surgical devices for the treatment of urinary incontinence and pelvic organ prolapse. In this paper, we provide the initial results from the development of the PelvicSim modules which combine in vivo sensing experiments, Ultrasound and MRI imaging datasets, and an inverse finite element modeling technology based on hyperviscoelastic constitutive modeling of the pelvic floor organs and tissues.