CASE Ultra is software program used in computational toxicology that identifies structural alerts related to toxicity using (Q)SAR. 

Predict Toxicity using QSAR

CASE Ultra (Q)SAR models are validated using OECD guidelines and come with QMRF reports. Models are available for the following toxicological endpoints:

Bacterial Mutagenicity/ICH M7 more

Genotoxicity

Carcinogenicity

Skin Sensitization

Acute Toxicity

Endocrine Disruption

Reproductive Toxicity

Developmental Toxicity

Cardiotoxicity

Hepatotoxicity

Renal Toxicity

ADME

Ecotoxicity

Identify Structural Alerts

Similarity measures are automatically employed to find analogs that have the same structural alerts as the query chemical. The program also alerts the user to alerts contained by analogs that are not shared with the query chemical when appropriate.

Different types of searches are usually needed to support in silico toxicity assessments. The databases in the MultiCASE platform are used for these tasks:

Bioactivity Search

This type of search is applied automatically by the software. When a query chemical is submitted for assessment, the connected databases are searched to determine if any experimental activity data is available. If found, the search result is reported with details such as assay conditions, dosage, duration of treatment, and species/strain information.

Similarity-Based Search

Similarity-based searches can be carried out for read-across purposes and to search for structural analogs to aid in expert review.

Substructure Search

Substructure searches are sometimes used to determine the toxicity potential of specific parts of a query chemical structure. Retrieved hits with specific structural alerts can be used to determine the alerts’ relevance in the context of the query chemical. Special alert environment similarity measures are employed for finding relevant analogs that have a similar structural environment around an alert.

Data Curation

Curation of chemical data is a crucial starting step in any workflow and is carried out using the DataKurator tool. Appropriate curation is critical in getting accurate results and needed for harmonizing the structures of the query chemicals with the databases to reduce out of domain outcomes and to increase the success of the database searches. DataKurator can be used to perform batch curation of tens of thousands of chemicals at a time.

Pay-Per-Test

for limited testing needs
  • Fixed Number of Queries
  • No Expiration Date
  • Local Installation
  • Software Updates Included

Annual License

for routine testing needs
  • Unlimited Queries
  • Yearly Renewal
  • Local Installation
  • Software Updates Included
Best Value

Consulting

for minimal testing needs
  • Results and Reports Provided
  • Optional Expert Review
  • No Installation Required
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Software packages are customized to meet the needs of the user. Factors that affect pricing include length of license, number of endpoints, and number of users. Please contact us to request a quote.

Related Research

2024, CASE Ultra, Publication

Quantitative Structure–Activity Relationship Models to Predict Cardiac Adverse Effects

27 Nov 2024

Drug-induced cardiotoxicity represents one of the most common causes of attrition of drug candidates in preclinical...

2024, CASE Ultra, Poster

Improving the Predictivity of QSAR Models to Evaluate Rodent Carcinogenicity

15 Mar 2024

Carcinogenicity is considered one of the most important toxicity endpoints to evaluate concerning human safety. The...

2023, CASE Ultra, Collaboration, Publication

Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project

13 Nov 2023

To promote superior model development, the Division of Genetics and Mutagenesis, National Institute of Health Sciences,...

2023, CASE Ultra, Webinar

QSAR Models for Endocrine Disruption

1 Aug 2023

MultiCASE's Mounika Girireddy explores the cutting-edge world of QSAR models tailored for assessing endocrine disruption potential...

2022, CASE Ultra, Publication

Assessment of Endocrine Disruption Potential of Chemicals Using Combined Quantitative Structure-Activity Relationship Modeling of In Vitro and In Vivo Assays

16 Dec 2022

We developed a method to predict in vivo endocrine disruption potential of chemicals using naive Bayes...

2022, CASE Ultra, Collaboration, Publication

Development of QSAR Models to Predict Blood-Brain Barrier Permeability

20 Oct 2022

Two statistical-based quantitative structure-activity relationship (QSAR) models were developed to predict BBB permeability of drugs based...