In recent years, artificial intelligence (AI) has become a hot topic, largely due to its potential to transform the ability of computers to solve increasingly complex problems in technology and society.
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Machines that are able to learn and “think” like a human brain offer great potential in advancing science and innovation by evaluating complicated scenarios in a fraction of the time it would take a person. While AI is still in its early stages, the biotech industry is already leveraging AI tools to accelerate drug discovery and advance health research.
Managing a Flood of Data
Worldwide, health research is occurring at a larger volume than any time in human history. Thousands of peer-reviewed articles are generated every month – a single person cannot keep up with the constant surge of new information, let alone quickly process and integrate it into their existing knowledge base.
Many biotech researchers are now using AI to manage the onslaught of data and make sure no meaningful pieces slip through the cracks. AI can quickly find, aggregate, interpret, and summarize multiple articles in different languages in a matter of minutes, making meaningful insights that researchers can use to drive health innovation.
Understanding the Body
In order to treat disease, it’s critical to understand how the body works down to the cellular level, and how a disease interferes with healthy processes. Uncovering these processes can inspire new treatments and preventative measures that can transform how doctors manage a disease. Without a comprehensive knowledge of how a disease progresses and the biological pathways it impacts, it can be difficult to predict what medical interventions will be effective and which are likely to cause unwanted side effects.
AI is being used to analyze previous research and patient data to illuminate biological pathways that are implicated in health and disease. AI technology can also be utilized to build more advanced models of bodily processes that can predict how different treatments will impact a disease. Researchers armed with this knowledge can pursue new drug targets and interventions that get to the core of disease and improve patient health with fewer side effects.
Transforming Clinical Trials
Pre-clinical drug screening and clinical trials in human patients are costly processes with a low rate of drugs that make it to market. Unclear results, unexpected side effects, and patient dropout can derail the journey to drug approval. Very few candidate medicines make it into the hands of patients and the difficulty of this process often delays the availability of potentially life-saving drugs for years.
Researchers are utilizing AI to streamline drug testing by planning better experiments, predicting drug effects, and improving clinical trial recruiting and patient retention. This empowers drug developers to save time and money by focusing on the best candidate medications and ensuring a smooth path to market.
AI Supports Health Innovation
The power of AI is already changing how health research progresses. Leveraging AI scientists are able to better research and understand diseases while biotech and pharma are better able to identify and qualify the medicines of the future.