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AZ tackles heart failure with machine learning and AI

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Researchers at AstraZeneca (AZ) are collaborating with other experts in precision medicine to identify novel biomarkers to guide and treat life-threatening heart muscle diseases.

The company has turned to AI, machine learning and gene expression analysis to unravel the complex disease biology of heart failure at the molecular level in individual patients.

Machine learning enables the researchers to analyse large quantities of gene expression data from cardiac biopsy samples and separate patients with heart failure into novel molecular sub-classes, regardless of their clinical signs and symptoms.

Ben Challis, Head of Translational Sciences and Experimental Medicine, Early CVRM, AstraZeneca said:

“Through this process, we have shown that the ‘molecular fingerprints’ shared by people do not always reflect the current cardiomyopathy classifications generally used for diagnosis.

“What we’re starting to do is link sub-class-specific gene expression profiles to dysregulated molecular pathways and processes indicative of distinct disease biology across the different sub-classes.

“Using all this new information, we aim to identify novel therapeutic targets that could form the basis of a precision medicine approach to treat patients with heart failure.”

One gene that plays a role in causing stretched and weakened heart muscle in patienrs with cardiomyopathy (DCM), produces a protein called phospholamban (PLN).

Excessive PLN activity is associated with faulty calcium cycling and impaired heart muscle contraction and relaxation, but this mechanism has proven hard to target with conventional drugs.

Kenny Hansson, Head of Bioscience Cardiovascular, Early CVRM, at AstraZeneca said:

“Encouraging laboratory data has demonstrated the potential of antisense oligonucleotides (ASOs) to target PLN activity in DCM.

“The research, carried out in collaboration with Ionis Pharmaceuticals and international heart failure scientists at University Medical Center Groningen and Karolinska Institute, shows that ASOs – strands of synthetic DNA – can be used to deplete the formation of PLN linked to DCM.”

Encouraging results with ASOs in other heart failure models, suggest that this could be a promising precision medicine approach in cardiomyopathy and possibly other forms of heart failure.

Advances in the care of children born with DMD have improved the outlook for those living with the condition.

However, progressive wasting of heart muscle can lead to life-limiting DCM and heart failure when individuals reach their 20s.

Progress with gene therapy targeted at heart muscle has been limited to date.

However, by using their CRISPR-Cas9 gene editing expertise, the teams at AstraZeneca are investigating the removal of faulty sequences from the dystrophin gene and using adeno-associated viruses to efficiently deliver targeted treatment into heart muscle cells.

If this proves successful, there is also the potential to extend this approach to other inherited diseases.

By exploring subtle genetic mutations, variations in gene expression and gene-environment interactions in more common forms of heart failure, there is a potential to group patients for clinical trials of biomarker-guided targeted treatment.

Hansson said:

“Drawing on innovations in clinical trial design and using an expanding toolkit of novel drug modalities, we’re aiming to target almost any type of underlying disease biology in heart failure, so that one day the right drug is always available for the right patient at the right time.”

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