The Maxwell RSC 48 is an automated nucleic acid purification platform that provides efficient and reproducible isolation of DNA, RNA, or protein from various sample
types, including tissues, cells, blood, and FFPE samples. With the ability to process up to 48 samples simultaneously, it ensures high purity and yield, making it suitable for downstream applications such as next-generation sequencing, qPCR, and genotyping.

The TapeStation is a fully automated electrophoresis instrument used for DNA, RNA, and protein quality control. By providing rapid analysis of sample integrity, size
distribution, and quantification, it ensures accurate evaluation of sample quality prior to applications such as sequencing, PCR, and library preparation for next-generation sequencing. It offers streamlined workflows with minimal sample preparation and reliable data output.

The 10x Visium HD technology is a spatial transcriptomics solution designed to map gene expression within intact tissue sections. By capturing mRNA directly from tissue slides and linking gene expression profiles to their spatial context, it enables detailed characterization of tissue architecture and cellular heterogeneity. Its applications include oncology, neuroscience, developmental biology, and pathology, providing insights into tissue organization and disease mechanisms.

The 10x Chromium is a microfluidics-based platform used for high-throughput single-cell and single-nucleus analysis. It partitions individual cells or nuclei into nanoliter- scale droplets, allowing for comprehensive profiling of gene expression, immune repertoire, chromatin accessibility, and more. Its applications include single-cell RNA sequencing (scRNA-seq), ATAC-seq, and multi-omics approaches, enabling researchers to study complex biological systems at single-cell resolution.

The PromethION 2 Integrated is a high-throughput nanopore sequencing platform designed for large-scale genomic and transcriptomic studies. It combines next-generation sequencing data generation with integrated compute, enabling real-time basecalling and analysis. With the capacity to run up to two flow cells independentlyor simultaneously, it provides flexibility for various applications, including whole-genome sequencing, epigenomics, transcriptomics, and metagenomics.

This project aims to develop a machine learning approach to infer patient-specific therapeutic strategies. By integrating in situ transcriptomic and genetic profiling of
morphologically distinguishable tumor niches with treatment data from our patient derived combinatorial therapy models, we will build an algorithm capable of predicting personalized targeted therapies directly from standard histopathological images.
 

In this project, we utilize advanced preclinical models, including human organotypic slice cultures and patient-derived tumor fragments xenografted into immunocompromised
animals. Our objective is to investigate the impact of drug combinations, tailored to specific biotypes, on tumor progression. Integrating this approach with genetically modified, patient-derived in vitro co-culture models of different cell populations will permit a detailed assessment and validation of drug selectivity and reveal cellular adaptive responses within distinct tumor niches.