MultiCASE, Inc. was founded in 1995 and is located in Mayfield Heights, OH, a suburb of Cleveland. The company focuses on the research and development of innovative (Q)SAR methodologies and software solutions. MultiCASE has maintained strong regulatory, industry, and academic ties in the areas of computational, medicinal, and environmental chemistry.
Build and apply (Q)SAR models for
toxicity-related risk assessments
Assess complex toxicological endpoints
with limited experimental data
Peptide immunogenicity risk assessment
for APIs, variants, and impurities
Predict and search for metabolites
of xenobiotic compounds
Meet the people who make up MultiCASE!
The MultiCASE platform originated from research and numerous publications by Dr. Gilles Klopman and his colleagues, which began in 1984. Their work demonstrated that quantitative structure-activity relationships can be identified using automated, data-driven computational methods without manually selecting descriptors.
MultiCASE debuted its first commercial software, CASE, to study the relationship between structure and biological activity of organic molecules.
The new MCASE algorithm analyzed the structural features relevant to the biological activity of molecules, building on the capabilities of its predecessor, CASE. The key advancement in MCASE was the hierarchical selection of descriptors, introducing the concepts of Biophores and Modulators for more accurate predictions of new molecules' potential activities.
META was an expert system that predicted potential enzymatic attack sites and the resulting chemicals formed by these metabolic transformations. It relied on dictionaries of transformation operators, created by experts to represent known metabolic pathways.
In order to take advantage of the flexible Windows environment and the availability of personal computers, the MCASE and META techniques were implemented into new programs called MC4PC and META PC.
Replacing MC4PC, we launched CASE Ultra, our advanced software that uses fragment-based expert and statistical models to predict toxicological endpoints.
Replacing META PC, we introduced META Ultra, a (Q)SAR system designed to predict xenobiotic metabolites and their toxicological properties.
QSAR Flex is a single program with multiple in silico tools for conducting complex risk assessments using a weight-of-evidence approach.
Our newest software, Seqtara, is a platform designed to support immunogenicity assessment and sequence-based analysis.
