Zebrafish-Based CNS Disease Models for Preclinical Research | ZEFIT

ZEFIT is a contract research organization that utilizes zebrafish-based models to advance preclinical drug discovery, reducing reliance on traditional mammalian models and accelerating drug candidate validation. ZEFIT CNS-FITTM platform uses zebrafish for advanced modelling of central nervous system model disorders, providing cost-effective, precise, and scalable data for early-stage drug discovery. The preclinical testing platform analyses locomotor activity, neural structures, and cognitive functions, generating robust behavioral and electrophysiological datasets, making it ideal for big data-driven research. 

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Key Features of the Central Nervous System Disease Model: 

  • Cognitive & Memory Function Testing: CNS-FITTM tests learning ability, memory retention, and behavioral adaptability in zebrafish larvae and juveniles using visual stimuli and movement tracking algorithms it helps identify cognitive impairment and alter perception under different lighting conditions, potentially aiding in screening compounds for neuroprotective effects. 
  • Anxiety Behavior Modelling: Zebrafish larvae are effective models for neuropsychiatric disorder research due to their measurable responses to anxiety-inducing conditions. The CNS-FITTM platform tracks thigmotaxis and reactivity to external stimuli, making it suitable for studying generalized anxiety disorder, panic disorder, and drug screening. 
  • Convulsion Monitoring: The central nervous system model (CNS-FITTM) is a tool for real-time monitoring of brain activity and motor responses in neurological disorders like epilepsy. It uses electrobiological recordings, seizure frequency, intensity, and duration tracking and quantification of hyperactive swimming patterns and motor spasms. This method evaluates anticonvulsant efficacy, identifies neurotoxic effects, and explores seizure pathways. 
  • Trusted Models for Drug Discovery: CNS-FITTM is a standardized tool for modelling disease-specific phenotypes, including Alzheimer’s, Parkinson’s, and epilepsy. These models provide high translational value, enabling early compound screening, mechanistic studies, and lead candidate validation in a cost-effective and time-efficient manner. 

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