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CAS Life Sciences Data

When making new life sciences discoveries, complete, connected data is crucial for success. Dive deep into relationships between diseases, targets, and novel molecules with the world’s most trusted and reliable source of scientific information, the CAS Content Collection™.

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Des données pour accélérer votre processus de découverte de médicaments

Grâce à nos centaines de scientifiques et à notre couverture approfondie de la littérature scientifique au cours du siècle dernier, CAS aide les scientifiques à se tenir au courant des dernières percées et des fondations sur lesquelles elles sont construites. Que vous recherchiez des cibles de maladies, que vous planifiiez des études structure-activité-relation (SAR), que vous évaluiez le potentiel d’activité hors cible ou que vous répondiez aux nombreuses questions de dépôt de nouveaux médicaments (IND) avant la recherche, gagnez du temps en tirant parti de la richesse des données publiées existantes.

SAR, ADME data, toxicity values, and other bioactivity observations and pharmacological data facilitate the discovery of novel targets for therapeutic intervention.

Indexed nucleic acid and protein sequences provide a better understanding of how sequence changes affect biological functions.

Molecular biomarkers used in predictions, diagnoses, and prognoses reveal underlying causes and effects of a disease.

Metabolic signaling pathways and interactions further enable inferences and discoveries of connections between diseases, molecules, and pharmacological responses.

Antibodies, antibody-drug conjugates, antibody-fusion proteins, chimeric antigen receptors, and related engineered proteins hold diagnostic, therapeutic, or immune indications/applications.

Connections between disparate data types reveal reliable critical relationships.

"The comprehensiveness of the CAS database is unparalleled."
TVID: 17E-012-6D1
R&D vice president/director,
Small business pharmaceuticals company
CAS data experts Nicole Stobart, Jeff Wilson, Ph.D., and Mark Schmidt examine the difficulties and importance of creating new authority constructs to organize life sciences data.
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