Human genetics supported targets are sought after for higher success in the clinic during the last decade. While population genetics studies are revealing disease associated locations in the genome, biobank genotyping, whole exome, and whole genome sequencing efforts are in full swing to find rare causal and protective variants that would become drug discovery targets. This presentation willcover the status of current efforts and future directions.

Recent technological advances have enabled the systematic identification of genes that cancer cells rely on for their survival. However, translating these biological insights into new cancer therapeutic targets remains challenging. To facilitate cancer target discovery and advancement, we have developed computational pipelines to prioritize targets from the Cancer Dependency Map datasets and also cell-based assays to validate the most promising gene dependencies towards drug discovery to accelerate precision cancer medicine.

While phenotypic approaches allow for the discovery of new targets and mechanisms, target deconvolution represents a key challenge due to the intrinsic difficulty, time, and expense. Compound-sensitized genome-wide screens using CRISPR/Cas9 are a powerful tool to aid in target identification. We will describe the development of an arrayed screening platform, and its application to generation of target hypotheses for a small molecule that enhances antisense oligonucleotide (ASO) uptake.

Single-cell CRISPR screens produce rich gene expression phenotype information by directly linking to each CRISPR perturbation at single-cell resolution. In this presentation, we explore how recent advances in single cell methodology provide scalable approaches for deeper insights into cellular response and pathways as compared to output from traditional screening methods.

Identification and validation of the “right” target is critical to reduce clinical attrition and to make drug discovery more sustainable. We have invested in the establishment of “end to end” target discovery capability to enable the identification of novel drug targets with better attrition rates, building on advancements in genome editing, translatable models and computational power. I will describe a couple of case studies that epitomise this capability.  

Molecular mechanisms underlying idiopathic PD, which account for 80% of the PD cases, remain elusive. We performed multi-scale gene network analysis of a large gene expression dataset in the substantia nigra from 83 PD cases and 70 controls, and systematically identified and prioritized co-expressed gene modules and key regulators in PD. This study lays down a foundation for developing a comprehensive signaling map and novel therapeutics for PD.

Genome-wide CRISPR screens have revitalized functional genomics. Large-scale data sets enable rapid hypothesis generation, and focused screening efforts can provide detailed mechanistic insights into the function of any gene of interest. Here I will discuss how CRISPR screens are being employed in gene function discovery projects, with an emphasis on the latest technological advances.

CRISPR knockout screening can identify essential genes in cancer cell lines, and when these genetic vulnerabilities are strongly associated with a specific oncogene or tissue, they present ideal candidate therapeutic targets. However, functional buffering by related genes masks these vulnerabilities. We discuss how this blind spot in CRISPR screens can mislead drug targeting efforts, and discuss new CRISPR multiplex perturbation technologies to fill in the gap.

In vivo CRISPR screen is a powerful means for discovering therapeutic targets in physiologically relevant settings. Here, we describe recent advancements in in vivo T cell CRISPR screen for immunotherapy target discovery and characterization of example targets.

There has been much progress towards the experimental development of robust, scalable, and reproducible 3D cellular models, including spheroids, organoids, biofabricated tissues and microphysiological on chip systems, as assay platforms for preclinical drug testing.  However, there is a need for systematic physiological and pharmacological validation and benchmarking of the different 3D cellular models to establish their true clinical predictability and use for decision making in the drug discovery and development pipeline.