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  1. How Isogenic Organ-Chips Are Transforming The Future Of Research 6/25/2026

    Modeling the human brain requires more than simplified systems. New approaches that incorporate diverse cell types are improving how researchers study neurovascular function with greater precision.

  2. Organizing Digital Systems Around Novel Modalities 6/24/2026

    Cell therapies represent an important advancement in our ability to treat difficult cancers, but continued exploration of this new modality will require new digital tools and equipment.

  3. Automating cell therapy manufacturing without redesigning established workflow 6/24/2026
  4. The Future Is Ancient: Evolution, Metabolics, And AI 6/23/2026

    We caught up with Hannah Gordon, Ph.D., chief scientific officer of Enveda, to discuss why the future may depend more on decoding nature’s evolutionarily selected chemistry.

  5. The Next Chapter Of Obesity And Type 2 Diabetes Care: ADA 2026 Signals A More Personalized Future 6/23/2026

    The American Diabetes Association 2026 conference showed where we are and where we're going with GLP-1 therapies.

  6. Beyond Engineered Antibodies: Harnessing The Natural Human Repertoire 6/19/2026

    We caught up Srikanth Pendyala, MD, CMO of Infinimmune, to discuss the importance of learning directly from the human immune system itself in antibody research.

  7. Aligning Standards, Validation, And Governance For Digital Preclinical Research 6/18/2026

    No single body integrates preclinical data components into a coherent discipline supported by shared standards, common terminology, and collective accountability.

  8. Designed For Difficult Biology 6/17/2026

    Macrocycles expand drug discovery into previously inaccessible targets. With validated success and flexible approaches, they provide a powerful path for tackling the most challenging biology.

  9. Calculate Physicochemical Properties 6/11/2026

    Calculators & Predictors for LogP, LogD, pKa, Aqueous Solubility, and more…

    The physicochemical properties of a molecule can help you better understand its likely behavior, support QSPR high-throughput screening (HTS) of libraries, and data-driven lead optimization.

    ACD/PhysChem Suite is made up of a number of prediction modules. It provides high-quality, structure-based calculations of physicochemical properties.

    • Predict aqueous solubility,* boiling point, logD,* logP,* pKa,* Sigma, and other molecular descriptors for organic compounds, from structure
    • Evaluate the calculated results with sorting, plotting tools
    • Assess the reliability of predicted physicochemical property values
    • Investigate quantitative structure-property relationships, structure modifications, and/or lead optimization for a target profile
    • Train predictors with experimental data to better reflect novel chemical space
    • Include custom models and in-house prediction algorithms

    *Models are trainable with experimental data

  10. Insights For Data-Driven Decisions 6/11/2026

    The Percepta Platform is a portfolio of software applications and a technology ecosystem for predicting and managing physicochemical, ADME/Tox, and other molecular property data.

    With Percepta applications you can predict molecular properties from structure, and train models with experimental data. You can even include custom models created in-house to centrally manage in silico calculations and training sets for distribution so that everyone calculating property data is using up-to-date information.