
Biopharma
Automation & AI
The Genedata Biopharma Platform is first-in-class enterprise software that automates R&D workflows and drives scientific innovation. It delivers analytics- and AI-driven insights that help bring better life-saving therapies to patients faster and more cost-effectively.
All Therapeutic Modalities. Supported.
A central end-to-end digital backbone enables the registration and tracking of both complex biologics and small molecules, integrating analytics and functional assay results into a ‘single source of truth’ across R&D.

Small Molecules

Antibodies,
Enzymes

Next Generation Molecules:
Bi- & Multi-specifics, ADCs…

Cell & Gene Therapies:
CAR Ts, TCR-Ts, iNKs, Lentivirus, AAV…

RNA Therapies & Vaccines:
Oligonucleotides, mRNA-LNP…
Seven Systems. Working Separately or Together.
The Genedata Biopharma Platform is composed of seven systems that can be used together or individually to enable innovation, accelerate R&D workflows, increase R&D efficiency and ultimately improve clinical success.

Discover the Platform
- BIOLOGICS - Biotherapeutics Discovery
- BIOPROCESS - Bioprocess Development
- CHROMATICS - Chromatography Data Analysis and Management
- EXPRESSIONIST - Mass Spectrometry Data Analysis
- PROFILER - Precision Medicine
- SCREENER - Assay Analytics & Management
- SELECTOR - NGS-Based Development & Biosafety
Increase Bioengineering Output by a Factor of 10
Software Benefits:
- Register all biotherapeutic modalities
- Streamline screening and optimization processes and biological data handling
- Automate data capture and analysis from instruments and robotics
- Drive innovation with a structured data foundation for AI/ML
- Ensure data integrity & traceability
Increase Process Development Efficiency by 200%
Software Benefits:
- E2E bioprocess development
- Regulatory compliance
- Quality by design
- Instrument integration & process automation
- Digital twin/modeling
Cut Chromatography Data Analysis Time by over 15x
Software benefits:
- Streamlined analysis and reporting of all chromatography data
- Automated, harmonized, end-to-end workflow for peak quantification and analysis
- High quality, FAIR protein purification and developability data
- Enables data sharing across R&D teams and fosters AI-readiness
Eliminate >90% of Manual Data Processing Hours
Software Benefits:
- Streamlined mass spec workflows
- In-depth molecular characterization
- Automated & custom data processes
- MAM implementations
- GXP-ready product quality assessment
Design Smarter Clinical Trials to Improve the Success Rate by 20%
Software Benefits:
- Identify new therapies
- Define new therapeutic indications
- Discover/validate novel biomarkers
- Leverage real world data
- Design smarter, targeted clinical trials
- Enable precision medicine
Reduce Compound Screening Analysis Time from 3 Days to 3 Hours
Software Benefits:
- Harmonize all plate-based assays and analysis on a single platform
- Get structured data and standardized metadata and for FAIR, AI-ready datasets
- Automate assay analysis from reader to report
- Employ cutting-edge assay technologies, including multiplexed and label-free
- Perform deep, scientifically-appropriate analysis using smart fitting and model selection
- Automate routine analyses with AI/ML-based methods
Reduce Assay Time of NGS Workflows for Product Characterization by 90%
Software Benefits:
- NGS-based workflow automation
- Proprietary genome annotation
- CRISPR-based target engineering
- Development of stable cell lines
- Critical quality attributes (CQA) & MAM assessment
- Bioprocess optimization with omics data
- Biosafety testing in GMP environment
Trusted by World-Leading Companies
Unlock Synergies Across Groups & Workflows. Drive Automation and AI.

Automating Biotherapeutic Characterization
Discover how automated MS data workflows enhance productivity, harmonize analysis, eliminate errors, and facilitate collaboration in biopharmaceutical developability assessments at Novartis.

Data Backbone Connects R&D Organization
“Now that we have a central data backbone in place where all information can be accessed and shared, our R&D groups can spend their time on critical scientific tasks, instead of manual data reporting and management.”




