Identifying and characterizing ligand-target interactions in a physiologically relevant context remains a critical challenge in the early phases of drug discovery. Thermal shift assays enable assessments of target engagement in cells, with limited target pre-knowledge and SAR. However, since these methods are reliant upon protein aggregation, they often suffer from limited sensitivity and scalability in HTS settings. Here, we present a novel bioluminescence resonance energy transfer (BRET)-based assay for detecting ligand-protein interactions in intact cells using protein denaturation (BRETSA). Cell-permeable denaturation-sensitive dyes are used to detect the denatured state of a NanoLuc-tagged target protein after thermal challenge. Ligand interactions are determined as a change in the thermal stability profile of the target protein, which manifests as a dose-dependent loss of the BRET signal in live cells. The BRETSA method is broadly applicable and has been applied to measure ligand binding to greater than 100 targets across 20 protein families and 6 intracellular locations (including transcription factors and integral membrane proteins). The method has a broad dynamic range and can be used to detect ligand interactions over at least 5 orders of magnitude, surpassing that of aggregation-based thermal shift methods. In addition to small molecule-protein interactions, the method can also be utilized to detect a range of small molecules, including molecular glues, bifunctional degraders, and cooperative ternary complexes. We demonstrate that the BRETSA method can be scaled for high throughput applications such as hit finding and target identification. Our results demonstrate that BRETSA is a uniquely robust, sensitive, and scalable method to assess ligand-binding interactions in a cellular context.

Genomics and AI can now generate candidates at scale - but functional validation remains the bottleneck. A single study can surface thousands of SNVs and gene targets, yet most laboratories are still limited to interrogating one at a time.
This talk explores how industrial-scale CRISPR cell engineering is changing that. Zofia Świątczak will introduce EditCo Bio's automated genome engineering platform, built to deliver hundreds of precise, reproducible edits in parallel - spanning highly edited cell pools, clonal cell lines, and precision knock-ins including SNVs, endogenous tags, programmable degradation tags, affinity tags and reporter & fusion genes.
A real-world case study illustrates the impact: a small biotech generated 12 validated knockout models in under four weeks, pinpointing two high-priority gene targets ahead of a critical investor deadline. This work would have taken the in-house team years.
For projects requiring a single well-characterised edit or a large-scale functional screen, EditCo's platform scales to fit - bridging the gap between computational discovery and experimental validation with speed, consistency, and industrial precision.

Human induced pluripotent stem cells (hIPSCs) have emerged as a transformative platform for drug discovery by enabling access to disease relevant human cell types in scalable, genetically defined systems. hIPSC derived models capture human specific biology, genetic diversity, and clinically relevant phenotypes. In drug discovery, both 2D and 3D models play distinct and complementary roles. 2D neuronal and glial cultures offer experimental tractability, high throughput, and precise control of cellular composition, making them well suited for early stage compound screening, target validation, and mechanism of action studies. In contrast, 3D models such as organoids recapitulate aspects of tissue architecture, cell to cell interactions, and developmental trajectories, enabling the investigation of complex disease mechanisms. At UCB, we are reshaping early drug discovery by bridging the translational gap between preclinical research and clinical outcomes.

Preclinical evaluation of novel anticancer agents relies heavily on the availability of tumor models that faithfully recapitulate human disease. Orthotopic models, in which tumor cells are implanted at their tissue of origin, offer a greater degree of biological relevance than conventional heterotopic approaches — yet they also demand monitoring strategies that are both sensitive and minimally invasive, so as not to compromise the integrity of longitudinal study designs.
In this context, bioluminescence imaging (BLI) based on the luciferin/luciferase system has emerged as a particularly powerful tool. By enabling repeated, whole-body visualization of viable luciferase-expressing tumor cells within the same animal over time. BLI circumvents the limitations of terminal endpoints and reduces inter-individual variability inherent to cohort-based designs. Critically, it provides not only an indicative quantitative readout of tumor burden, but also spatial information on disease localization and dissemination — a dimension that is especially valuable in aggressive, metastasis-prone malignancies such as Ewing sarcoma.
Here, we present an orthotopic murine model of human Ewing sarcoma, established through surgical procedure of intrafemoral injection of luciferase-expressing A673 cells in immunodeficient NSG mice. BLI-guided group allocation at baseline ensures homogeneous tumor burden across experimental groups prior to treatment initiation. Weekly imaging sessions thereafter allowed dynamic tracking of tumor progression at both the local and systemic level, revealing patterns of metastatic spread to the abdominothoracic region that were subsequently corroborated by necropsy findings.
Complementary endpoints — including body weight, clinical scoring, and survival — were integrated alongside imaging data to provide a comprehensive and translatable picture of disease development and treatment response. Together, these parameters illustrate how BLI, when embedded within a rigorous longitudinal framework, can meaningfully strengthen the preclinical assessment of therapeutic candidates in orthotopic tumor models.