Over the last few years, Artificial Intelligence has taken over many aspects in our life, including biotechnology. AI has become integral to many aspects of biotech as its applications help accelerate the processes of drug target identification, drug screening, image screening, and predictive modeling. It also “manages disparate clinical trial datasets, enables virtual screening, and analyzes vast amounts of data. Besides reducing clinical trial costs, AI can gain otherwise unobtainable insights and feed them back into the drug development process.”(Shaffer)
DATA ANALYSIS
One aspect of biotechnology that relies on AI is data analysis. Traditional methods of data analysis in fields, such as drug discovery, work best with straightforward data and tend to fall short when the data becomes complex like multiple diagnoses or complex treatment plans. However, AI with the ability to handle complex, multivariate data can integrate and analyze the data to produce stratified patient groups. Sensyne Health is at the forefront of this clinical data movement. The company intends to move away from the traditional modes of data analysis that burns through billions of dollars and still produces high failure rates to more complex machines with learning-based methods that have higher rates and accuracy. Sensyne Health believes that somewhere in the near future, industries will move away from classical randomized controlled trials, instead conducting virtual trials. Virtual trials are favored for their ability to do heavy lifting and provide all the information needed without the expensive human trials.
SIMULATION
AI is also used for simulations to help reveal patient response to treatments in real-world settings. Concerto Health, offers an example of a typical cancer patient being diagnosed for the first time. “That patient would initially be staged based on tumor location and size, metastatic status, and other features of the disease. Then this information would be used to guide treatment. Then, additional information—“on the fly” information about the patient’s progress or changes in disease status of the disease—may become available. It will not, however, automatically become part of the patient’s electronic medical record (Shaffer). The information gathered is critical for pharmaceutical companies, like how accurate information on staging at different timepoints in the patient history helps pharmaceutical companies understand why a treatment is or isn’t effective. Concerto HealthAI’s technology is very useful for making predictions about how a patient will respond to certain medications. These predictions are valuable in the design of a clinical study and “can offer clinical researchers a direct line of sight into the standard of care, which is important because often physicians will not place patients in a trial if it is too much of a burden compared to the standard of care.”(Shaffer)
In conclusion AI has developed a lot in biotechnology and has become an important aspect in data analysis and simulations, helping researchers save time and money while producing more accurate results.
References
Shaffer, Catherine. “Artificial Intelligence Is Helping Biotech Get Real.” GEN - Genetic Engineering and Biotechnology News, 1 Apr. 2020, www.genengnews.com/insights/artificial-intelligence-is-helping-biotech-get-real/.
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