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Implementation of new machine learning algorithms for the optimisation of drug formulations

CORDIS · observation · Publication date unknown

Implementation of new machine learning algorithms for the optimisation of drug formulations Correctly developing and predicting crystalline forms with specific physico-chemical properties is essential to the pharmaceutical industry. The main challenge this industry faces is the fact that most active pharmaceutical ingredients in most drugs can interconvert into a different (usually more stable) polymorph, potentially reducing the solubility of the drug, slowing down the release of the API and affecting the pharmacokinetics, bioavailability and efficacy of the drug. For instance, due to the complex interplay between thermodynamics and kinetics, it often happens that unexpected polymorphs emerge either in development (best case scenario) or long after the drug has been approved for market (worst case scenario). A previously known stable form that disappears or the sudden appearance of an even more stable form c

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recordType

award

status

CLOSED

region

EU

value

150000

unit

EUR