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Japan extends timeline for approving Fujifilm's Avigan drug for COVID-19

The Japan Times

The government has decided to postpone approving Fujifilm Holdings Corp.'s Avigan drug for the treatment of COVID-19 until June or later, health minister Katsunobu Kato said Tuesday. Prime Minister Shinzo Abe had said earlier this month he hoped the drug, known generically as favipiravir, would be approved some time in May if its efficacy and safety could be confirmed. But Kato told a news conference Tuesday that clinical tests on the drug would continue into next month or beyond, while noting that there was no change in the government's policy of approving the drug swiftly once its effectiveness is confirmed. Fujifilm shares slumped last week after it was reported that an interim study showed no clear evidence of efficacy for Avigan in COVID-19 cases. Researchers at Fujita Health University, which is conducting a clinical trial on the drug, said in a statement the interim study was done to ensure the scientific validity of the trial, not to determine the efficacy of the drug.

More than 1,700 COVID-19 Clinical Trials Registered Worldwide - Expert System


These are the initial findings from Expert System's Artificial Intelligence platform, Clinical Research Navigator (CRN), which is collecting biomedical research information from official reports and studies published worldwide. Following the launch of its AI-based Clinical Research Navigator (CRN), which is focused on accelerating research on COVID-19, Expert System mined over 620,000 clinical trials, including more than 1,700 trials related to the virus that are taking place around the globe. Clinical landscape is changing rapidly in the context of the current pandemic situation. It is therefore critical to have a global coverage of the trial registries to serve clinical experts with appropriate and effective means to conduct their research on the disease. Expert System analyzed data collected with its Artificial Intelligence CRN platform to gain some insight on key trends correlated to official reports and studies published worldwide.

12 applications of artificial intelligence in medicine


Applications of artificial intelligence (AI) in medicine are creating a bigger impact on global healthcare by bridging the gap between the patient and the provider. It has the potential to improve productivity, efficiency, speed, accuracy and workflow of both the patients and physicians significantly. According to the recent declaration by CB Insights, the role of AI in healthcare is very crucial and hence is being used by almost about 86% healthcare service providers, biotechnology companies, and pharmaceutical companies. Experts have suggested that by the end of the year 2020, on an average, a burden of $54 million will be borne by these industries to ease the life of the common man. This unique convergence of technology and medicine can help in streamlining tedious processes with more patient empowerment and substantial reduction in repetitive tasks. The standard medical practice in future would be like patients visiting a computer first before seeing the doctor. Events of misdiagnosis and medical errors would be a thing of past. Doctors can spend more quality time with patients bringing back the care in healthcare.

Drug research turns to artificial intelligence in COVID-19 fight


Variational AI Inc.'s bread and butter rests in novel drug discovery, specifically using artificial intelligence (AI) to compress the years-long preclinical process to perhaps a single year. But in the midst of a pandemic, even a year might be too long to find a treatment for COVID-19, according to CEO Handol Kim. "Even if we're able to collapse the front end, you still have five or six years of clinical trials and who knows if we need a drug in five or six years for COVID-19?" he said. "We thought, 'Well, the fastest way to do this is repurposing existing drugs.'" The pitch caught the interest of the Digital Technology Supercluster, which last month committed to spending $60 million of its $153 million budget to develop partnerships across its networks to address issues brought on by the pandemic.

How Machine Learning Is Redefining The Healthcare Industry


The global healthcare industry is booming. As per recent research, it is expected to cross the $2 trillion mark this year, despite the sluggish economic outlook and global trade tensions. Human beings, in general, are living longer and healthier lives. There is increased awareness about living organ donation. Robots are being used for gallbladder removals, hip replacements, and kidney transplants.

What AI still can't do


Machine-learning systems can be duped or confounded by situations they haven't seen before. A self-driving car gets flummoxed by a scenario that a human driver could handle easily. An AI system laboriously trained to carry out one task (identifying cats, say) has to be taught all over again to do something else (identifying dogs). In the process, it's liable to lose some of the expertise it had in the original task. Computer scientists call this problem "catastrophic forgetting."

AI is helping triage coronavirus patients. The tools may be here to stay.


Rizwan Malik had always had an interest in AI. As the lead radiologist at the Royal Bolton Hospital, run by the UK's National Health Service (NHS), he saw its potential to make his job easier. In his hospital, patients often had to wait six hours or more for a specialist to look at their x-rays. If an emergency room doctor could get an initial reading from an AI-based tool, it could dramatically shrink that wait time. A specialist could follow up the AI system's reading with a more thorough diagnosis later.

AI in Life Sciences: Faster Cures for Viral Disease - Digitally Cognizant


COVID-19 is upending life as we know it. The potential effect of this viral disease on mortality and public health, as well as the lasting socioeconomic impact of the crisis, is unfathomable. To mitigate the wide-scale impact of this growing pandemic, our hopes are trained on a vaccine, prophylactic or curative, and the life sciences industry that can produce it. Prior to the emergence of COVID-19, advanced forms of artificial intelligence (AI) were facilitating and accelerating each stage of the research, discovery and production process. Now, AI continues to be an essential tool in the search for "repurposable" molecules.

International coronavirus treatment trial uses AI to speed results


The first hospital network in the U.S. has joined an international clinical trial using artificial intelligence to help determine which treatments for patients with the novel coronavirus are most effective on an on-going basis. Why it matters: In the midst of a pandemic, scientists face dueling needs: to find treatments quickly and to ensure they are safe and effective. By using this new type of adaptive platform, doctors hope to collect clinical data that will help more quickly determine what actually works. State of play: No treatments have been approved for COVID-19 yet. Researchers have made headway in mapping how the virus attaches and infects human cells -- helping "guide drug developers, atom by atom, in devising safe and effective ways to treat COVID-19," National Institutes of Health director Francis Collins writes.

How AI could help in the fight against COVID-19


From developing drug treatments to predicting the next hotspot, artificial intelligence may help researchers, healthcare workers, and everyday people offset the impact of the coronavirus. As the worldwide fight against coronavirus COVID-19 continues, companies and governments around the world are pulling out all the stops in an effort to stave off the pandemic's worst impacts. One tool in that toolbox that might prove particularly useful is artificial intelligence (AI). Even though AI has been around since the 1960s, it's only been in the past few years that its adoption outside of science labs and research institutions has really taken off. Perhaps the most common application of AI people have come into contact with today are virtual assistants like Apple's Siri and Amazon's Alexa, which rely on natural language processing (NLP) algorithms to understand human speech.