Genedata Profiler®は、社内外のデータソースからの多種多様なデータの統合を標準化・自動化します。効果的な解析とセキュアなコラボレーションのために、目的に合ったデータセットを作成することができます。
Working closely with Genedata, we have generated a digital biomarker research platform that will enable Merck scientists to better utilize clinical and translational data to generate innovative ideas for new biomarkers and drug targets.
We are pleased to have found a reliable partner who provided us with expert knowledge in big multi-omics data analysis to accelerate our search for precision biomarkers to prognosticate disease course and to guide early and effective personalized treatment decisions.
We chose Genedata Profiler because it is the end-to-end enterprise software able to harmonize our dispersed data analysis pipelines, enhancing our capacity to analyze large amounts of high-dimensional ‘omics data emerging from our rapidly growing number of translational and clinical research projects.
As we expect our clinical and pre-clinical programs and pipeline to continue to grow, we look forward to utilizing Genedata Profiler and Genedata Managed IT Services to assist us in our mission to develop safe, targeted, effective therapeutics for cancer patients.
Data Products.
Bridging Preclinical & Clinical.
Each data product is built on a defined data model, governed by ontologies, business rules, and purpose‑specific logic ensuring FAIRness and ALCOA. Our data products:
• Integrate data from distributed sources and ensure interoperability across modalities
• Support both human and AI consumption
• Enable decision‑making across R&D, clinical, and regulatory teams
Precision Medicine.
AI‑Enabled.
The exploration assistant accelerates scientific work by:
• Finding datasets across distributed systems
• Proposing analytical methods in natural language
• Generating visualizations and guiding interpretation
Annotation Assistant.
Higher Data Quality.
The annotation assistant enables intelligent data annotation for quality and consistency:
• Uses AI and LLMs to automate dataset annotation with metadata and descriptions
• Analyzes column statistics, study details, tags, and more to suggest annotations
• Respects metadata policies for suggestions and allows human review before saving
