APPLICATIONS OF PHENOTYPIC SCREENING FOR TARGET IDENTIFICATION IN DRUG DISCOVERY

Pooled CRISPR screens are widely used to uncover novel insights relevant for drug target identification and to support target validation in drug discovery programs. However, they are usually coupled to rather simplistic read-outs, such as cell fitness/viability. At Myllia, we combine CRISPR/Cas9-based high-content screening with single-cell RNA sequencing, thus combining CRISPR perturbation with high-content phenotyping. Leveraging fitness, flow cytometry and single-cell transcriptomics read-outs for phenotypic screening, we enable genome-wide drug screens, large-scale FACS-based screens and CROP-Seq screens with transcriptomics at single-cell resolution.

Drug target identification and target validation in drug discovery

Blue target icon representing drug target identification.

Drug target identification and target validation in drug discovery

Target identification is the first step of a drug discovery campaign and begins with high-content screening to identify possible ‘druggable’ targets and their role in the respective disease. Myllia’s unique CROP-Seq (Perturb-Seq) technology for phenotypic screening in combination with the best available cellular models (including cancer cells and primary T cells) supports the identification and validation of critical genes and pathways driving certain disease states.

Mode of action (MoA) analysis and high-content screening for drug signatures

Screen illustrated as an icon in blue, symbolizing the drug target validation.

Mode of action (MoA) analysis and high-content screening for drug signatures

Understanding how drugs act in the complex environment of a cell remains one of the critical aspects of drug discovery and development after initial drug target identification. Importantly, phenotypic screening with CROP-Seq (Perturb-Seq) delivers transcriptional profiles associated with drug action and indicates which genes impact the drug profile, thus providing unique insights into its mechanism of action. It also uncovers genes that modify drug responses, thus paving the way for combination therapy.

Identification of disease-associated gene function using functional genomics

Illustrated DNA in blue for identifying disease-associated gene function.

Identification of disease-associated gene function using functional genomics

Genome-wide association studies (GWAS) contribute to target identification in drug discovery, identifying thousands of genetic variants that are linked to disease. Unfortunately, many of these loci lie in non-coding regions of the genome. Pinpointing the gene(s) whose expression is regulated by these regions would elucidate novel drug targets that are causally linked to disease. Myllia has built a high-content screening platform based on CRISPR interference (CRISPRi) that can map disease-associated variants to genes in an unbiased fashion.

Phenotypic screening for immune pathways and drug target identification in primary T cells

Network icon in to illustrate the primary T cell phenotypic screening subsets identified by computational biology.

Phenotypic screening for immune pathways and drug target identification in primary T cells

Engineering of T-lymphocytes has become a crucial factor driving the development of novel cellular medicines and cancer immunotherapies. However, apart from tumor-associated antigens (TAA) and Chimeric Antigen Receptor (CAR) or T Cell Receptor (TCR) discovery, many T cell-intrinsic features involved in CAR-T cell potency remain elusive. At Myllia, CRISPR/Cas9-based high-content screens are performed in primary human T cells to study T cell activation, differentiation and phenotypic plasticity. Utilizing dropout fitness/viability screens, FACS-based screens or CROP-Seq screens at single-cell resolution, we aim to partner with pharmaceutical companies striving to develop the next-generation of CAR-T and TCR-T cell products.

CRISPR/Cas9-based high-content screening accelerates drug target identification across many therapeutic areas and helps unravel gene regulatory networks in cancer cells as well as primary human T cells.