Can machine learning create faster clinical trials for COVID-19?

A recent research paper, published in Statistics in Biopharmaceutical Research, describes how advances in machine learning can provide an opportunity for researchers to create faster and more flexible clinical trials for COVID-19 drugs.

Led by the Director of the Cambridge Centre for AI in Medicine, Professor Mihaela van der Schaar, the paper discusses three areas of clinical trials in which machine learning can make contributions: In trials for COVID-19 treatment using repurposed drugs, trials for new drugs to treat COVID-19, and ongoing clinical trials for drugs unrelated to the ongoing pandemic.

Van der Schaar said: “The coronavirus pandemic represents the greatest global healthcare challenge of our generation. Our recent work in machine learning for clinical trials has shown enormous promise.

“While many of the technical issues discussed in our paper are particularly acute in the context of a pandemic, they are also highly relevant to ongoing clinical practice. It is my hope that machine learning will not only improve the execution and evaluation of clinical trials in the COVID-19 era, but also well beyond that.”

The paper outlines how machine learning can support the creation of ‘virtual’ control groups and integrate data management techniques across hospitals. The proposed solution suggests that data-driven methods can identify patients who have received standard treatments but are otherwise similar to patients who have received experimental treatments to allow researchers to determine the success of new drugs.

Machine learning technologies play an important role in finding patterns and signatures in COVID-19’s biomolecular behaviour, facilitating the identification and repurposing of existing drugs, as well as validating, in silico, whether new medicines may be effective. Using such models can also allow researchers to exploit the large body of data generated by the experimental and compassionate use of drugs to select future drug targets for further clinical trials for COVID-19.

Co-author Professor Frank Bretz from Novartis, a Swiss multinational pharmaceutical company, said: “Machine learning algorithms have proven to be equivalent or superior to expert clinicians in interpreting X-ray and MRI images and slides, for example. This new work aims to bridge the gap between the machine learning community and the data scientists who are engaged in clinical trials that are affected by or related to COVID-19.”

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