Booth 502
Date
September 30 - October 2, 2025
Stay tuned for more talks and posters.
| Time | Type | Description | Room / Location | Presenter |
| 10:00 | Plenary | Architecting Discovery: Getting the Most Out of Data, AI, and Automation
Genedata | Plenary Theater | Jana Hersch |
| 18:10 | POSTERS | NGS-Powered CMC Strategies: Enhancing Quality and Compliance in Biologics Manufacturing Poster: 69
In the rapidly evolving field of biological drug products, Chemistry, Manufacturing, andControls (CMC) is instrumental in ensuring product quality, safety, and regulatorycompliance. Biopharmaceutical companies are increasingly adopting next-generationsequencing (NGS)-based assays to support the development and characterization ofstarting materials, such as cell lines or vectors.Biological drug modalities, such as antibody therapies, must be rigorously characterizedto meet stringent quality standards. To mitigate manufacturing risks, for examplecontaminations or genetic instabilities, and to ensure regulatory compliance, it isessential to characterize Critical Quality Attributes (CQAs), including identity, integrity,and purity of the production cell line.By leveraging NGS technology, biopharmaceutical companies can enhance thereliability and consistency of their manufacturing processes, delivering safer, moreeffective GMP-grade therapies to patients faster. For this to succeed, validated in-houseNGS platforms are required. Successful validation demands careful control of methodvariability, as well as instrument and protocol standardization. Furthermore, robust datahandling and strict adherence to regulatory requirements are essential.Genedata Selector® is an enterprise software platform that automates and acceleratescomplex NGS data processing, analysis, interpretation and decision-making processes,supporting companies in overcoming CMC challenges in biologics production.
Genedata | Poster Area | Christoph Bredack |
| 18:10 | POSTERS | High-Throughput Mass Spectrometry Analytics for ML/AI-Ready Drug Discovery Poster: 68
As the demand for scalable mass spectrometry (MS) analytics increases, standardized dataacquisition and automation of time-consuming manual processes are needed to deliver high-throughput,qualityresults.Bystreamlininginformationexchangewithcentralizeddatamanagement systems, data processing from different vendors, and result review, the GenedataBiopharma Platform enables large-scale screening and generation of structured datasets forML/AI-ready drug discovery, supporting enterprise-level biopharma digitalization and deliveringfaster insights for decision-making.
Genedata | Poster Area | Laura Radu Parlog |
| 18:10 | POSTERS | Workflow Automation for Ultra-High-Throughput Spectral Shift Analysis Poster: 73
HighThroughputSpectralShift(HT-SpS)isacutting-edgebiophysicalscreeningtechnology that enables direct detection of binders and allosteric modulators, includingboth small molecules and biologics. For the first time, hits can be identified through directbiophysical measurements at the earliest stages of drug discovery. The NanoTemperDianthus uHTS is a high-performance instrument based on SpS technology, capable ofmeasuring a full 1536-plate in approximately 7 minutes.Here we present an automated end-to-end workflow in Genedata Screener (part of theGenedata Biopharma Platform) that enables HT-SpS hit detection with unprecedentedthroughput. [YA1] Genedata Screener fully automates the entire analysis workflow forDianthus uHTS data, including data loading, processing, quality control, result calculation,hit identification, and reporting to downstream applications. It efficiently handles diverse(HT-)SpS datasets, enables interactive review of raw spectral scan graphs at any step,performs automated outlier detection, provides robust QC metrics, and supports sampleranking via direct affinity constant determination.With the addition of SpS to the broadsuite of assay technologies covered, Genedata Screener thus continues to accelerate theidentification of new molecules from the beginning of the discovery cycle.
Genedata | Poster Area | Simone Borgoni |
| 18:10 | POSTERS | An Automated High Throughput Engineering Platform for AI-Supported Developability Predictions Poster: 70
An Automated High Throughput EngineeringPlatform for AI-Supported Developability PredictionsCombinatorial selection strategies and advances in protein and nucleotide engineering havebeen successful in generating novel large-molecule therapeutics. Bi- and multi-specificantibodies, antibody drug conjugates (ADCs), chimeric antigen receptors (CARs), engineered T-cell receptors (TCRs), and other formats offer new approaches to treatment. However, theefficient design, production, and multi-dimensional characterization represent a major challenge,especially when creating those highly engineered therapeutic candidates in high throughput.Here, we demonstrate how the Genedata Biologics®platform enables a fully automatedworkflow for next-gen modalities, integrating all steps from selection, molecular biology,expression, purification, and analytics. Built-in workflows for automatedin silicomoleculeassembly mechanisms allow efficient design of large panels of novel biomolecules. Dedicatedtools for pooled cloning deconvolution and automated chain pairing recovery automate thegeneration of tens of thousands of molecule variants that are then tested for drug-likeproperties. Data from multi-parametric screening is captured in the system’s highly structureddatabase and systematically analyzed to evaluate the candidates under consideration of allmeta-data, genomic, and phenotype information. We demonstrate the platform’s capabilities byillustrating a fully integrated developability and manufacturability assessment using a novelAI/ML approach for large panels of bi-specific molecules. Further, we illustrate how the platformcan be used to automate the full range of innovative modalities, including CAR-Ts, AAVs, andmRNA-LNPs.
Genedata | Poster Area | Sebastian Kolinko |
| 18:10 | POSTERS | Structured Knowledge Management Platform for Bioprocess Development Poster: 71
Centralized structured data across multiple groups is critical for integrated bioprocessdevelopment with advanced data analytics, machine learning (ML) and artificial intelligence (AI)approaches, and efficient reporting to regulatory agencies. Growing adoption of high-throughputand process analytical technologies (PAT) and laboratory automation led to a substantialincrease in the volume of data to be captured, processed, and analysed during bioprocessdevelopment. We showcase an E2E structured knowledge management platform that supportsthe entire bioprocess development workflow. The goal of bioprocess development is to generaterobust processes to produce a biotherapeutic at desired quality and scale. We designed a dataplatform applicable to all proteins (e.g., IgGs, ADCs, bispecifics, enzymes), RNA & DNAtherapeutics and vaccines (e.g., mRNA, DNA vaccines, ASOs), and cell and gene therapeutics(e.g., AAVs, CAR-T cells). In close collaboration with groups from leading biopharmaceuticaland biotech companies, we validated the platform’s design for support of complete developmentworkflows. The platform automates cell line development, assesses numerous scale-downupstream processes (USP), manages USP up-scaling, supports downstream process (DSP)development, and facilitates analytical and formulation development. It enables lineage trackingof all intermediates and batches. Analytical and process data, raw materials, equipment details,and molecule and cell line information are automatically tracked with the batches, enablingsystematic assessment, robust process understanding, and quality risk management. Theplatform enhances process and product understanding and control. Having accumulatedstructured data can serve as a powerful foundation for learning, modeling, and data analytics,such as mechanistic modeling, ML and AI, to gain process knowledge and perform predictions.
Genedata | Poster Area | Michele Bruschi |
| 18:10 | POSTERS | A Digital Platform for the Development of Next-Generation Antibody Drug Conjugates (ADCs) and Other Antigen-Targeting Conjugates Poster: 72
Antibody Drug Conjugates (ADCs) use antibodies to achieve targeted delivery of therapeuticcargoes to specific cell populations and tissues. In oncology, ADCs are used to selectivelyeliminate tumors while reducing the off-target effects associated with conventionalchemotherapy. Here, we present how Genedata Biologics® supports and accelerates the fullADC discovery process from antibody screening and engineering to antibody expression,purification, drug conjugation, and reporting of ADC-specific analytics (e.g. DAR, drugdistribution, homogeneity). The platform enables the automated generation, registration, andtracking of large panels of ADC candidates and incorporates results from analytics andfunctional assays in one integrated system, thereby substantially increasing throughput andefficiency of the ADC discovery process. Other next-generation antigen-targeting conjugates,including bi-specific ADCs, alternative scaffolds (e.g. scFVs, DARPins), and novel payloads(e.g. oligonucleotides, antibiotics) are also supported by the system to accelerate the applicationof these new technologies.
Genedata | Poster Area | Ines Boehm |
| Time | Type | Description | Room / Location | Presenter |
| 11:45 | ROUNDTABLE | Automation and AI in Mass Spectrometry Workflows: Hype or Hope?
Genedata | Exhibition Floor | Arnd Brandenburg,Senior Scientific Account Manager Dominik Mertens,Scientific Account Manager |
