Using Artificial Intelligence (AI) to help repurpose existing drugs for treating new illnesses has a “bright future”, but the world needs to be more prepared to share health data, a virtual panel hosted by Qatar Foundation’s global health initiative has been told.
The World Innovation Summit for Health (WISH) brought together experts from the fields of biomedicine, computing, and healthcare collaboration, as well as the World Health Organisation (WHO), to explore how AI and bioinformatics could support the modification of already-approved medicines to provide more rapid solutions for the likes of Covid-19.
The event formed part of Qatar Foundation’s contribution to Global Goals Week, during which it has staged a series of sessions themed around developing local solutions to worldwide challenges. Among those who joined the WISH-organised discussion were scientists from Qatar Computing Research Institute (QCRI) and Qatar Biomedical Research Institute (QBRI), both part of QF member Hamad Bin Khalifa University.
“If you have 20,000 approved drugs in the market and want to test each of them in a clinical setting for a set of patients, it would cost billions of dollars and tens of thousands of hours, and it’s almost unrealistic to do that," Dr Raghvendra Mall, a scientist at QCRI, said.
“AI models can help, such as through screening and helping to prioritise which of these 20,000 drugs will potentially be most suitable in blocking diseases such as Covid-19, and this is what we are trying to do. The goal is to find which set of drugs can be tried first and that are most likely to be effective, and this is where different machine learning models can be used to reach a consensus.”
Dr Prasanna Kolatkar, a senior scientist at QBRI, said that the myriad ways that proteins – “the active players and engines for what makes us” – interact within the body means biological data science cannot yet be 100% accurate, but added: “It’s clearly helpful and is changing the way science works – it would be ignorant not to take advantage of AI because it allows us to point ourselves in the right direction, and we are now able to carry out this work at a biological level.
“People may say that a repurposed drug is already proven to be safe. However, by understanding it as a molecular level, you can have a good idea of what is binding and what the possibility of off-target drug effects is, and even modify it in the future to make even better drugs. It can definitely save time and, depending on how severe the disease is, perhaps it will eventually be possible to allow certain repurposed drugs to be released earlier if something is needed rapidly to treat a disease among certain groups.”
Also joining the discussion, moderated by WISH’s head of content Maha El Akoum, was Bernardo Mariano Junior, chief information officer at WHO, who said health data is one of the major gaps in the global health sector, and a governance framework that allows data scientists to help speed the response to diseases is needed.
“The tech industry uses data to monetise it, but the health sector has a culture of donation rather than monetisation,” he said. “We need to bring these two worlds together and really ensure we leverage data for global good and to have a positive impact on health.”
Prof Aziz Sheikh, director at the University of Edinburgh’s Usher Institute noted: “We’re still at a pretty early stage of the journey, but we are already beginning to see a number of ways in which the field of AI can interact with public health provision – diagnosis, trying to identify potential cures and treatments and see which ones may get traction, and to guide decision-making by clinicians and increasingly by patients.”
The event formed part of Qatar Foundation’s contribution to Global Goals Week, during which it has staged a series of sessions themed around developing local solutions to worldwide challenges. Among those who joined the WISH-organised discussion were scientists from Qatar Computing Research Institute (QCRI) and Qatar Biomedical Research Institute (QBRI), both part of QF member Hamad Bin Khalifa University.
“If you have 20,000 approved drugs in the market and want to test each of them in a clinical setting for a set of patients, it would cost billions of dollars and tens of thousands of hours, and it’s almost unrealistic to do that," Dr Raghvendra Mall, a scientist at QCRI, said.
“AI models can help, such as through screening and helping to prioritise which of these 20,000 drugs will potentially be most suitable in blocking diseases such as Covid-19, and this is what we are trying to do. The goal is to find which set of drugs can be tried first and that are most likely to be effective, and this is where different machine learning models can be used to reach a consensus.”
Dr Prasanna Kolatkar, a senior scientist at QBRI, said that the myriad ways that proteins – “the active players and engines for what makes us” – interact within the body means biological data science cannot yet be 100% accurate, but added: “It’s clearly helpful and is changing the way science works – it would be ignorant not to take advantage of AI because it allows us to point ourselves in the right direction, and we are now able to carry out this work at a biological level.
“People may say that a repurposed drug is already proven to be safe. However, by understanding it as a molecular level, you can have a good idea of what is binding and what the possibility of off-target drug effects is, and even modify it in the future to make even better drugs. It can definitely save time and, depending on how severe the disease is, perhaps it will eventually be possible to allow certain repurposed drugs to be released earlier if something is needed rapidly to treat a disease among certain groups.”
Also joining the discussion, moderated by WISH’s head of content Maha El Akoum, was Bernardo Mariano Junior, chief information officer at WHO, who said health data is one of the major gaps in the global health sector, and a governance framework that allows data scientists to help speed the response to diseases is needed.
“The tech industry uses data to monetise it, but the health sector has a culture of donation rather than monetisation,” he said. “We need to bring these two worlds together and really ensure we leverage data for global good and to have a positive impact on health.”
Prof Aziz Sheikh, director at the University of Edinburgh’s Usher Institute noted: “We’re still at a pretty early stage of the journey, but we are already beginning to see a number of ways in which the field of AI can interact with public health provision – diagnosis, trying to identify potential cures and treatments and see which ones may get traction, and to guide decision-making by clinicians and increasingly by patients.”
