In the next six years, AI’s role in the life sciences is expected to grow by nearly 30%, creating a 5 billion dollar market. As it grows more advanced, artificial intelligence has started to play a larger role in all parts of the biotech industry. For example, in the area of drug discovery, predictive AI is extremely helpful. Data from hundreds of patients from hospitals and clinics are fed into an algorithm that records and analyzes various factors of the patient’s malady. From this data set, the program can recognize patterns and help fast-track the research process.
Universities Cambridge and Aberystwyth put the accuracy of AI to the test, creating an experiment that tested if the program could locate enzymes in the genetic code that could catalyze a yeast reaction. In addition to the 9 known genes, the program was able to locate 9 novel genes.
This is only the tip of the iceberg for AI in the biotech field; many other applications have the potential for integration with AI.
Graph made in MATLAB
AI In the Pandemic
The coronavirus pandemic has opened many opportunities for AI in healthcare. One of these is the use of AI to help epidemiologists track and predict the spread of the virus. The SIR model is a tool commonly used to predict the severity and contagiousness of a virus. The model uses three parameters: infected, susceptible, and recovered. From this epidemiologists can determine the course of an outbreak. However, collecting values for the three parameters is an arduous task. This is where AI comes in. An AI program can parse through dense data easily and simply output the necessary information. This would simplify the process for epidemiologists and streamline the process to fight future pandemics.
Lastly, knowledge management systems and chatbots powered by deep learning can be beneficial to hospitals of any size. With an AI program to manage patient’s information, a doctor can have all the relevant information at their fingertips. With an online chatbot, patients can schedule appointments with minimum inconvenience.
AI In the Future
However, there are still some hurdles to overcome before AI can be fully integrated into the healthcare system. In a study conducted by Chinese researchers, an AI bot, called DoctorBot, was introduced to a hospital. Over the course of the experiment, the researchers found that there were two main issues: the bot gave a diagnoses that differed from the doctor’s and the diagnosis the bot gave was too complicated, confusing the patient. Because of this, the researchers had to conclude that more design improvement was necessary before chatbots with a knowledge system could be included in hospitals. The researchers ended with stating several design improvements for future bots. According to them, a bot had to be “more informative, easy-to-use, and trustworthy.”
Future chatbot knowledge systems, such as EIVA, created by LAUNCH!, are addressing these problems. New chatbots could utilize a more humanlike user interface using natural language processing instead of a keyword search to make the bot more trustworthy and easy to use. In addition to that, a system that allows for more crowdsourcing that connects more qualified people can make the bot more informative and accurate.
The scope of applications of AI in the biotechnology industry is extremely large and investing in this space early, will allow the technology to develop and return exponentially increasing rewards.
Sources: 1) Fleming, Nic. “How Artificial Intelligence Is Changing Drug Discovery.” Nature News, Nature Publishing Group, 30 May 2018, http://www.nature.com/articles/d41586-018-05267-x. 2) Fan1*, Xiangmin, et al. “Utilization of Self-Diagnosis Health Chatbots in Real-World Settings: Case Study.” Journal of Medical Internet Research, JMIR Publications Inc., Toronto, Canada, http://www.jmir.org/2021/1/e19928/. 3) “Artificial Intelligence (AI) in Life Sciences Market: Growth, Trends, COVID-19 Impact, and Forecasts (2021 – 2026).” Artificial Intelligence (AI) in Life Sciences Market | Growth, Trends, COVID-19 Impact, and Forecasts (2021 – 2026), http://www.mordorintelligence.com/industry-reports/artificial-intelligence-in-life-sciences-market.
Images: 1) “Genetic Biotech through the Eyes of Artists / Centre for Fine Arts (BOZAR) (BE)” by Ars Electronica is licensed under CC BY-NC-ND 2.0 2)“Image Hertzsprung-Russell Diagram” by Arenamontanus is licensed under CC BY 2.0 3)“Chatbot robot” by Beantin webbkommunikation is licensed under CC BY-SA 2.0