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Using computational models to overcome the blood brain barrier

Live webinar 24 February 2022

A key challenge when designing compounds that target the central nervous system (CNS) is the prediction of blood-brain barrier (BBB) penetration. The BBB can hinder paracellular transport, so CNS drugs typically pass into the brain via transcellular permeation. However, this route can be challenged by issues with the efflux of the drug from within the cells, which can drive higher dosage requirements to ensure the correct concentration in brain tissues. Higher exposure of a compound in the brain generally translates into better (neuro-) pharmacokinetics and ultimately lower dosage requirements. Pre-screening of potential compounds ahead of analysis in vivo is desirable for the identification of the best performers, and computational and chemoinformatic methods are routinely applied to design and screen compound libraries. Multi-parameter optimization (MPO) of physicochemical properties along with machine learning driven predictive modeling has been reported in the literature for these designs. Recent work using MPO techniques has shown that it is possible to push the physicochemical property landscape boundaries to design and optimize CNS drugs.

What you will learn:

In this webinar, Dr Sandeep Pal will show you the approach Concept Life Sciences (CLS) uses to design CNS-penetrant compound libraries, covering techniques such as:

CNS-MPO

Sparse array design

Machine learning/AI

You can register for free to all our webinars and you will automatically receive the On-Demand version

Details

  • Malvern WR14 1XZ, UK
  • Malvern Panalytical

    Keywords