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    Machine learning model to predict the fitness of AAV capsids for gene therapy

    3 weeks ago

    A new study in Human Gene Therapy describes a machine learning (ML) model that can be used as a surrogate for laborious in vitro experiments. This in silico approach aims to increase the fitness of clinical adeno-associated virus (AAV) capsids to make gene therapies more economically viable for patients.
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