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The development of nasal drug delivery systems requires advanced analytical techniques and tools that allow for distinguishing between the nose-to-brain epithelial tissues with better precision, where traditional bioanalytical methods frequently fail. In this study, attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy is coupled to machine learning (ML) and deep learning (DL) techniques to discriminate effectively between epithelial tissues. The primary goal of this work was to develop Safe-by-Design models for intranasal drug delivery using ex vivo pig tissues experiment, which were analyzed by way of ML modeling. We compiled an ATR-FTIR spectral data set from olfactory epithelium (OE), respiratory epithelium (RE), and tracheal tissues. The data set was used to train and test different ML algorithms. Accuracy, sensitivity, specificity, and F1 score metrics were used to evaluate optimized model performance and their abilities to identify specific spectral signatures relevant to each tissue type. The used feedforward neural network (FNN) has shown 0.99 accuracy, indicating that it had performed a discrimination with a high level of trueness estimates, without overfitting, unlike the built support vector machine (SVM) model. Important spectral features detailing the assignment and site of two-dimensional (2D) protein structures per tissue type were determined by the SHapley Additive exPlanations (SHAP) value analysis of the FNN model. Furthermore, a denoising autoencoder was built to improve spectral quality by reducing noise, as confirmed by higher Pearson correlation coefficients for denoised spectra. The combination of spectroscopic analysis with ML modeling offers a promising strategy called, Safe-by-Design, as a monitoring strategy for intranasal drug delivery systems, also for designing the analysis of tissue for diagnosis purposes.

01 Jan 2025·Methods in Molecular Biology

Separation and Purification of CHO Secretome and Extracellular Vesicles for Proteome Analysis

Article

Author: Lehmkuhl, Maren ; Keysberg, Christoph ; Hoffrogge, Raimund ; Otte, Kerstin ; Noll, Thomas

For decades, host cell proteins (HCPs) have been investigated as putative contaminants in downstream processing of biopharmaceutical products of Chinese hamster ovary (CHO) cells. However, little is still known about the composition of the entire protein and vesicle environment in CHO cultivations. Ever evolving mass spectrometry techniques allow more and more insights into cell-cell communication processes and the composition of extracellular matrix, proteases, and further actively segregated compounds such as extracellular vesicles (EVs). EVs themselves are a heterologous group consisting of exosomes, ectosomes, and apoptotic vesicles. To specifically analyze these subsets of the secretome and determine beneficial and detrimental factors for a production process, targeted separation and purification techniques are necessary.In this chapter, we present our optimized workflows for a clear differentiation between directly secreted proteins and the vesicular protein content of different fractions (especially exosomal small EVs) from CHO cell supernatant for proteomic analysis by NanoLC ESI-MS.

01 Jan 2025·Methods in Molecular Biology

MiRNA Chaining for Efficient Stable Overexpression to Improve Protein Quantity and Quality in CHO Cells

Article

Author: Leroux, Ann-Cathrin ; Otte, Kerstin ; Burkhart, Madina ; Hesse, Friedemann ; Klingler, Florian ; Schlossbauer, Patrick

MicroRNAs (miRNAs), small noncoding RNAs with a length of about 22 nucleotides, harbor the potential to be powerful tools for the genetic engineering of production cell lines like Chinese hamster ovary (CHO) cells. Their ability to regulate multiple targets at once and their potential to fine-tune effect strengths contrast with classical engineering approaches. However, most studies of miRNAs rely on transiently flooding the cells with miRNA mimics. Since this approach is not suitable for long-term cultivation in a bioprocess, stable overexpression of miRNAs becomes more and more important for the biotech industry. Here, the user might be confronted with insufficient overexpression of the miRNA of interest. In this chapter, we present a method for the generation of stable CHO cell lines expressing a miRNA from a plasmid-based system containing multiple copies of the miRNA, allowing tuning of overexpression and regulation.

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Pipeline

Pipeline Snapshot as of 02 Aug 2025

The statistics for drugs in the Pipeline is the current organization and its subsidiaries are counted as organizations,Early Phase 1 is incorporated into Phase 1, Phase 1/2 is incorporated into phase 2, and phase 2/3 is incorporated into phase 3

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