Short oligomeric peptides typically do not exhibit the entanglements required for the formation of nanofibers via electrospinning. In this study, the synthesis of nanofibers composed of tyrosine-based dipeptides via electrospinning, has been demonstrated.The morphology, mechanical stiffness, biocompatibility, and stability under physiological conditions of such biodegradable nanofibers were characterized. The electrospun peptide nanofibers have diameters less than 100 nm and high mechanical stiffness.Raman and infrared signatures of the peptide nanofibers indicate that the electrostatic forces and solvents used in the electrospinning process lead to secondary structures different from self-assembled nanostructures composed of similar peptides. Crosslinking of the dipeptide nanofibers using 1,6-diisohexanecyanate (HMDI) improved the physiological stability, and initial biocompatibility testing with human and rat neural cell lines indicate no cytotoxicity. Such electrospun peptides open up a realm of biomaterials design with specific biochemical compositions for potential biomedical applications such as tissue repair, drug delivery, and coatings for implants.

Chemical vapor deposition (CVD) is a technique for the fabrication of thin films of polymeric materials, which has successfully overcome some of the issues faced by wet chemical fabrication and other deposition methods. There are many hybrid techniques, which arise from CVD and are constantly evolving in order to modify the properties of the fabricated thin films. Amongst them, plasma enhanced chemical vapor deposition (PECVD) is a technique that can extend the applicability of the method for various precursors, reactive organic and inorganic materials as well as inert materials. Organic/inorganic monomers, which are used as precursors in the PECVD technique, undergo disintegration and radical polymerization while exposed to a high-energy plasma stream, followed by thin film deposition. In this chapter, we have provided a summary of the history, various characteristics as well as the main applications of PECVD. By demonstrating the advantages and disadvantages of PECVD, we have provided a comparison of this technique with other techniques. PECVD, like any other techniques, still suffers from some restrictions, such as selection of appropriate monomers, or suitable inlet instrument. However, the remarkable properties of this technique and variety of possible applications make it an area of interest for researchers, and offers potential for many future developments.

The discovery of self-assembling peptides, which can form well-ordered structures, has opened a realm of opportunity for the design of tailored short peptide-based nanostructures. In this study, a combined experimental and computational approach was utilized to understand the intramolecular and intermolecular interactions contributing to the self-assembly of linear and cyclic tryptophan-tyrosine (WY) dipeptides. The density functional tight binding (DFTB) calculations with empirical dispersive corrections assisted the identification of the lowest energy conformers. Conformer analysis and the prediction of the electronic structure for the monomeric, dimeric, and hexameric forms of the cyclic and linear WY confirmed the contributions of hydrogen bonding, π–π stacking, and CH−π interactions in the stability of the self-assembled nanotubes. The influence of the processing conditions on the morphological and thermal characteristics, as well as the secondary structures of the synthesized nanostructures, were analyzed. Preliminary studies of the influence of the nanotubes on the fate of neuronal cell lines such as, PC-12 cells indicate that the nanotubes promote cellular proliferation, and differentiation in the absence of growth factors. The aspect ratio of the nanotubes played an essential role in cellular interactions where a higher cellular uptake was observed in nanotubes of lower aspect ratios. These results provide insight for future applications of such nanotubes as scaffolds for tissue engineering and nerve regeneration and in drug delivery.

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Most potential oncology drugs fail at the later stages of the drug development pipeline and in clinical trials, despite having promising data for their efficacy in vitro. This high failure rate is partly due to insufficient predictive models being used to screen drug candidates in the early stages of drug discovery. As such, there is a need to develop and utilize more representative models that are amendable for efficient testing of drug efficacy to discover new therapeutic targets. 3D cell models, specifically patient-derived organoids (PDOs), offer a promising solution to this problem. Cells grown in 3D can better mimic cell-cell interactions and the tissue microenvironment, including cancer stem cell niches. Studies show that patients and their derived organoids respond similarly to drugs, suggesting the therapeutic value of using PDOs to improve therapeutic outcomes. However, challenges commonly associated with using these organoids, such as assay reproducibility, ability to scale up, and cost have limited their widespread adoption as a primary screening method in drug discovery. To address some of the hurdles associated with the use of PDOs in large scale screens, a semi-automated bioprocess has been developed for the controlled production of standardized PDOs at scale. PDOs cultured in the bioprocessor were uniform in size, show high viability and were produced in repeatable batches in an assay-ready format. In this study, patient-derived colorectal cancer (CRC) organoids were seeded in high density (96 or 384 well) microtiter plates manually. We also tested the feasibility of scaling up the use of these CRCs by using an automated liquid handler or a bioprinter to seed and culture the PDOs. CRC PDOs were treated with selected anti-cancer compounds at various concentrations. Compound effects were monitored over time using transmitted light imaging. For the analysis of organoid growth and development, a deep learning-based image segmentation model was developed to automate the segmentation of the organoids. Using this approach, we tracked the effects of the compounds on colorectal organoid size, morphology, texture, and additional morphological and phenotypic readouts. A viability assay was carried out using live/dead cell dyes and the PDOs were imaged in 3D on a high-content confocal imager. Out of the tested panel of known anti-cancer drugs, we found that PDOs treated with romidepsin and trametinib showed the most significant reduction in size, with a greater number of dead cells compared to the other compounds and controls. Overall, our results show the potential for the utility of PDOs in both precision medicine and high throughput drug discovery applications, when using automation with high-content imaging. Citation Format: Angeline Lim, Zhisong Tong, Prathyushakrishna Macha, Oksana Sirenkp. Novel platform for automation of high throughput drug discovery using patient derived colorectal cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 199.