Downloads

  1. Small Molecule Discovery Network And Capabilities 6/5/2026

    Our collaborative approach, proven track record, and deep technical expertise enable us to efficiently advance promising candidates, reduce development risk, and help transform innovative ideas into successful therapeutic realities.

  2. From Gene Editing To NGS-Based T Cell Characterization 6/4/2026

    Gene-edited T cells targeting PD-1 and TIGIT are redefining approaches to cancer therapy. Explore how cell engineering and integrated genomic workflows uncover critical insights into T cell function.

  3. Enterprise Decision Support Software For Product Development 6/3/2026

    The Only Software That Brings Together All of Your Team’s Process and Analytical Data in One Place

    The future of science is collaborative

    Modern pharmaceutical and chemical development teams must share information between many scientists, who are often spread across many locations, using different instruments.

    Your data should be useful

    More sources of data mean more spreadsheets, incompatible files, and time spent tracking down results. Information becomes siloed and data management gets in the way of research.

    Make your data work for you with Luminata

    Luminata lets your team store, search, map, process, and reuse all your chemical, analytical, and process data in one application. Streamline your chemical and pharmaceutical development with Luminata’s digital environment.

  4. Streamline High Throughput Experimentation And Process Development 6/3/2026

    Software for Automated, Digitalized Experimentation

    Katalyst D2D® (Design-to-Decide) provides integrated experiment design, planning, execution, and analysis for high-throughput synthesis, process optimization, and preformulation studies. It helps scientists execute experiments more efficiently and connect data with decisions across the design-make-test-analyze (DMTA) cycle.

  5. Assess the Safety Profile Of Pharmaceutical Impurities 6/3/2026

    Predict Genotoxic & Carcinogenic Endpoints to Meet ICH M7(R2) Guidelines

    ACD/Impurity Profiling Suite predicts a variety of toxicological endpoints to help you assess the genotoxic and carcinogenic potential of impurities and degradants. Developed through a collaborative agreement with the US Food and Drug Administration (FDA), the software can be used as part of your ICH M7(R2) workflow—to help prepare regulatory submissions and remain compliant.

    • Determine the ICH M7(R2) classification for impurities and degradants
    • Predict 21 toxicological endpoints from structure; for mechanisms of hazardous activity including:
      • Mutagenicity (AMES test and other procaryote and eucaryote test systems)
      • Clastogenicity
      • Other DNA damage
      • Carcinogenicity
      • Endocrine disruption mechanisms
    • Identify potentially hazardous structural fragments responsible for carcinogenic and genotoxic activity
    • Gain insight into the possible mechanisms of toxic effects
    • Assess the reliability of predictions
  6. Software For Efficient, Comprehensive Metabolite Identification 6/3/2026

    Accelerate metabolite identification with integrated analytics, predictive modeling, and automated data extraction. Visualize pathways, kinetics, and spectra in one place to improve confidence.

  7. Streamline Experiments From Design To Decide 6/3/2026

    Gain insight into how a connected approach to experimental design and data management helps reduce errors, accelerate iteration cycles, and unlock deeper insights.

  8. Assess The Safety Of Pharmaceutical Impurities In Silico 6/3/2026

    Advance impurity risk assessment with predictive modeling that clarifies toxicity mechanisms, strengthens regulatory arguments, and reduces experimental burden—helping teams make confident decisions.

  9. Manage And Share Analytical Data With Context 6/3/2026

    Disconnected analytical data slows discovery and limits insight. Take a look at how a unified, searchable environment brings structure, context, and automation to complex datasets.

  10. Automate Method Development And Achieve QbD 6/3/2026

    Learn about a smarter, data-driven path to chromatographic method development that reduces experimentation, predicts optimal conditions, and improves robustness—all while shortening timelines.