Enhancing Clinical Predictability through Human Disease-relevant Preclinical Models in CNS and Muscle Drug Discovery

Title :Enhancing Clinical Predictability through Human Disease-relevant Preclinical Models in CNS and Muscle Drug Discovery

Webinar Overview :
Drug discovery for central nervous system (CNS) and muscle diseases continues to face major translational challenges. Conventional models often fail to capture human disease biology, while functional readouts can be difficult to reproduce, interpret, and translate into clinically meaningful outcomes.

In this webinar, we will discuss practical approaches to improve translational decision-making by integrating disease-relevant models, functional assessment, and mechanistic insight across CNS and muscle disease research. By connecting model selection, functional readouts, and clinically relevant outcomes, this webinar will provide insights into how integrated preclinical strategies can support better go/no-go decisions and improve the probability of clinical success.

Key Topics:

CNS Drug Discovery Focus

• Enhancing human relevance and functional translatability with iPSC-derived brain organoid models
• Utilizing EEG and microdialysis-based translational pharmacodynamic assessments to link target engagement to pharmacological effects
• Improving objectivity and reproducibility in behavioral assessment with AI-assisted phenotyping technologies

Muscle Disease Research Focus

• Implementing a translational framework that combines disease-relevant models with quantitative functional readouts
• Using dystrophin/utrophin double knockout models to better capture disease severity, progression, and cardiac phenotypes
• Bridging preclinical and clinical functional assessment using electrophysiological and force-based biomarkers such as CMAP and in vivo torque measurement