By Cathy Tie, CEO of Locke Bio
With the rise of AI chatbots like ChatGPT, AI has taken over the public debate, and players across various industries seem to want to be part of the hype. But the technology’s application goes beyond creating the perfect playlist, curating your next profile picture, and giving you the ability to “chat” with video game characters like Mario. Some people may not realize this. Biotechnology has the potential to change the way we look at healthcare. It will revolutionize the way patients are treated, diseases are diagnosed and medicines are developed.
However, as with any new technology, there are still many problems to solve. Technology investors without clinical experience should be aware of the technology’s current limitations and ethical concerns. Here’s what investors should know before investing in an AI-driven biotech company. This includes notable sectors, progress to date, potential possibilities and current limitations of the technology.
diagnose:
Artificial intelligence (AI) has the potential to revolutionize medical diagnosis, the process of diagnosing certain conditions, by making it more efficient and less prone to human error. Take breast cancer for example. Usually, when a patient is screened for breast cancer, a doctor will evaluate an X-ray of the breast to identify potential tumors that may need to be examined further with a biopsy. They may be hidden inside the breast tissue, making it difficult for doctors to recognize them with the human eye alone. We are identifying tumors that we may have missed. A human doctor can see what the AI finds and decide accordingly if a biopsy is needed.
This is just one example of the many potential applications in this area. The bottom line is that AI can be diligent about detecting patterns that may indicate a medical condition. AI alone may not provide immediate diagnosis, but it can be a great “fact checker” for busy clinicians. Combined with the expertise and discerning eye of a human doctor, AI will make the diagnostic process faster and more accurate, allowing patients to begin treatment sooner.
Genomics:
Using AI in combination with genomics can also improve patient care through personalized medicine. Genetic testing provides a better understanding of the types of conditions patients are susceptible to, giving clinicians a more holistic and personalized view of their patients’ overall health.
However, this data can be complex and making meaningful health predictions can be difficult for clinicians. That’s where AI comes in. Deep genomics is one example. The company’s geneticists, molecular biologists and chemists use biologically accurate artificial intelligence technology to develop new ways to detect and treat disease.
It is hoped that this technology will enable more personalized care to be provided to patients. For example, if someone is known to be predisposed to a particular type of cancer, screening can begin early in life. Similarly, if we know that a particular class of medicine may have adverse side effects in a particular individual, we can offer alternative treatments. Instead, the more we know about a patient’s biology using genomics and AI, the better care we can provide.
Treatment:
AI has also proven to be a valuable tool in therapy, especially when it comes to drug discovery. By using data to model drug-protein interactions, AI helps scientists identify new drug targets that researchers can acquire and test in the lab. The model can also predict the kinds of side effects a drug can have on a patient, giving researchers a better idea of what to look out for, and ultimately making the drug safer for patients. It helps in designing drugs.
AI can greatly accelerate drug discovery because it can operate much faster than humans. This process could otherwise take years and millions of dollars. In fact, there are even drugs developed entirely by artificial intelligence for potentially fatal lung diseases. Applying AI to biology for target discovery and chemistry for drug design demonstrates the potential of AI to make significant contributions to the field of therapy. .
AI Current Limits:
Currently, the technology is so new that biotechnology often doesn’t have enough data to predict specific outcomes. As you can see, the output is sub-optimal if the input doesn’t have enough data. As a result, some clinicians currently do not trust AI to make accurate diagnoses or develop effective drugs without human intervention.
Despite the fact that AI may not be ready to operate without human supervision, this is not always apparent, even to the trained eye. For example, ChatGPT can fabricate research papers, medical data, references, etc. in a fairly convincing way. In one study, researchers found that he was tricked into a fake research abstract one in three times. This raises concerns as researchers worry that plagiarism or outright hoaxes will contaminate the real field of research.
AI also has ethical concerns. We are dealing with human biology, so testing the boundaries of AI is difficult. Unlike other applications of AI like self-driving cars, new drugs cannot be tested in empty parking lots where no one is guaranteed to get hurt. With such new technology, testing on humans or even animals could be considered unethical.
Ultimately, these applications are not fine-tuned enough to be 100% reliable without human intervention, but they are very powerful tools to help clinicians make more accurate decisions in less time. Technology is also advancing rapidly. Investors should look to companies that are changing the way we think about diagnostics, genomics and therapeutics. Because while the technology is still in its infancy, it has incredible potential. Moreover, these technologies will positively impact the way we all experience healthcare.
