Predictive Toxicology for Informed Lead Selection

High-throughput screening of new active substances is the cornerstone of successful drug discovery. Identifying structural alerts and predicting biological effects early in the pipeline prevents the costly advancement of high-risk candidates. By leveraging advanced computational models, you can prioritize leads with the highest probability of clinical success.

SAXOCON provides a sophisticated suite of computer-based models to identify structural alerts and predict biological outcomes, including:

• Validated QSAR Models:
  Established and rigorously validated Quantitative Structure-Activity Relationship (QSAR) modelling.
• Custom Modelling:
  Tailored QSAR solutions developed from your proprietary data libraries.
• ICH M7 Classification:
  Early-stage screening and classification of mutagenic impurities in accordance with ICH M7 guidelines.
• Read-Across Methodologies:
  Strategic use of data from analogous substances to fill data gaps without additional testing.
• Expert Interpretation:
  Contextual analysis of computational readouts by senior toxicologists.

Why Choose SAXOCON?

Our drug discovery services provide the technical clarity needed to de-risk your pipeline:

• Computational Toxicology Leadership:
  Best-in-class expertise in modelling biological effects based strictly on chemical structure.
• Data-Driven Strategies:
  Cost-effective screening protocols that streamline candidate selection and shorten development timelines.
• Holistic Guidance:
  A multidisciplinary approach that bridges the gap between raw computational data and actionable drug development decisions.

Delivery

SAXOCON delivers a comprehensive expert statement summarizing all computational findings. This documentation provides a clear, defensible rationale to support your candidate selection process and informs your ongoing safety assessment strategy.