The Black Mirror of AI-Driven Clinical Trial

The areas Artificial Intelligence is used in clinical trials are patient recruitment and retention, designing effective trials, and gathering and sharing data.

Published 3 years ago

Cookie takes a digital copy of a person's consciousness and makes it into the perfect assistant. Cookie knows how you like your toast, what temperature your house should be set at, and how you like your coffee. It knows all this information so accurately because it is you. Cookie takes care of the little things so that you can focus on the bigger picture. This program was employed in Black Mirror, but it is not a new concept. Cookie is an example of Artificial Intelligence. While programs like Cookie can be used for more personal uses, they can also be used to change the pharmaceutical market. The easy, repetitive, and mundane activities of everyday clinical research can be done much quicker, cost effective, and efficiently by AI. Cookie may represent a darker side of AI, but the true goal of AI in today's world is to use technology to its most full potential. We can ignore AI in fear of a world like Black Mirror represented, or we can embrace it in the present and focus on what it is doing right now in clinical trials.

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The areas Artificial Intelligence is used in clinical trials are patient recruitment and retention, designing effective trials, and gathering and sharing data. Billions of dollars are spent annually on recruitment for clinical trials. Then, actually finding eligible patients for trials and connecting them to the right trials is extremely difficult. Taking the responsibility off of a human to comb through all the information, data, and potential patients speeds up the process. AI could even access electronic medical records and directly cross-reference them to hundreds of trials based on whatever criteria applies. After the recruitment process, the problem of actually retaining the patient arises. Using AI can help predict which patients may drop out of the study. AI can predict this by using Real world Evidence (RWE). This evidence can be found from medical claims, labs and prescription data. AI can also help in designing effective trials. As many of you know, a badly structured trial can waste a lot of money, time, and even create faulty data. A solution to this problem is that AI can compare massive sets of data from past trials, which in turn can find similarities and areas of concern. It can even predict the likelihood of success or failure in a protocol design. Another way AI is used in clinical trials is with gathering and sharing data. A lot of time and effort goes into the actual collection and analysis of data. There is manual monitoring of responsiveness and results and collection of data via clinical site visits. The work that goes into gathering this information causes many patients to not enjoy the experience, and therefore dropout. To fix this, AI can gather information remotely and then share the information with doctors. This can all be done in real time and allows the data to be analyzed immediately. The process of using AI in clinical trials isn't about replacing researchers and doctors, but about saving them time, money, and resources. Freeing up their schedule from tasks that can be done just as effectively and even more efficiently will allow them to focus on things that AI can't directly help with.

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Artificial Intelligence is rapidly advancing, with many pharmaceutical and biotech companies jumping on the AI train for clinical trials. Some companies that have already integrated AI into their research are Bristol-Myers Squibb (BMS), Jenssen, Mitsubishi Tanabe Pharma, Novartis. BMS announced in March 2019 that they are partnering with Concerto HealthAI and will cover clinical trials. Jenssen decided to partner with WinterLight Labs in 2018 to attempt to predict dementia and neurodegenerative diseases based on voice samples from Janssen clinical trials. Mitsubishi Tanabe Pharma announced their partnership with Hitachi in 2018 to optimize clinical trial planning using AI. They will complete this task by taking information from scientific papers and Novartis started integrating AI in January 2018 when they partnered with McKinsey's QuantumBlack, which would analyze clinical trial operations with AI. In March 2018, Novartis partnered with IBM Watson to advance clinical trial recruitment. Novartis is continuing down the AI path by creating a predictive analytics platform that uses AI learning algorithms for clinical trial operations. As the world continues to accept AI, these pharma companies are working hard to use it to its full potential.

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As Artificial Intelligence continues to advance, the opportunities seem to be endless. The FDA is starting to increase their awareness on AI. They want to enhance innovation in the AI field, while they are developing regulatory framework. Ultimately, the goal is to support Artificial Intelligence in the pharma and biotech field. As the future of AI adjusts to regulations and new discoveries, it opens up many questions for what is to come. Will AI save research and development billions of dollars? Can AI accelerate discovery? We hope that these questions will soon be answered and that the answer will be yes.

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