The predictive value of pre-clinical biological models remains a central bottleneck in drug discovery. Traditional rodent systems and immortalized cell lines, although experimentally tractable, often fail to translate to human outcomes and are a key contributor to clinical attrition. Human-translatable systems, such as induced pluripotent stem cells (iPSCs) and human primary cells, capture disease biology with markedly higher fidelity and can now be deployed at scale. Here, we describe an industrialized, cross-therapeutic-area platform that reconciles human-relevant biology with the throughput required by modern drug discovery,with applications spanning cardiovascular, respiratory, neurological, and rare diseases.For target identification, we apply arrayed CRISPR knockout (KO) screens directly in iPSC derived and primary cell models. Across a portfolio of six to ten disease-relevant cell models,end-to-end automation (encompassing cell expansion, differentiation, and assay execution)has enabled us to deliver several genetic screens with the reproducibility and throughput required for unbiased discovery. We present case examples across therapeutic areas that illustrate how this approach surfaces mechanistically anchored targets while remaining aligned with the specific questions posed by each program.The same platform is adapted for therapeutic development across multiple modalities,including small molecules, oligonucleotides, and genomic medicines. Automated liquid handling, imaging, and AI/ML-supported data pipelines allow multi-modality interrogation at scale without sacrificing biological complexity. Collectively, these cases demonstrate that integrating human-translatable models, arrayed genetic screening, and broad modality coverage within a single automated framework enables scalable, translationally relevant drug discovery across a diverse disease portfolio.

Advances in multiplexing and computational analysis have revolutionised our comprehension of tissue-specific biology and therapeutic interactions. Spatial multiplexing facilitates drug discovery by characterising patient biopsies, elucidating model systems, and identifying novel biomarkers. It also contributes to understanding drug distribution, molecular heterogeneity, and the mechanisms underlying off-target toxicity. This presentation provides an overview of recent developments in the field, along with examples from projects.

Traditional high-throughput screening (HTS) and bulk RNA sequencing have long served as workhorses in early drug discovery, but averaging transcriptional signals across heterogeneous cell populations often masks cell-type-specific drug responses, rare resistance phenotypes, and nuanced mechanisms of action. Recent advances in high-throughput single-cell transcriptomics from 10x Genomics now make it practical to screen compounds at scale with single-cell resolution. In this webinar, we explore how transitioning from bulk RNA profiling to scalable single-cell transcriptomics transforms phenotypic drug screening. We will discuss workflows for handling high-sample-number compound screens, strategies for preserving sample integrity during scaling, and how high-resolution transcriptomics accelerates lead prioritization and target validation across complex cellular models.

Linking omics characterisation with advanced & complex models, implementation of ML-based omic analytical approaches, combination of different technologies and how new technologies are translated into a clinically regulated space