BY: Ria Fazulbhoy (MSIWM031)
The healthcare industry is going through a massive shift in many ways and using methods. The new world of artificial intelligence and technology has left no stone unturned, including the field of biology. From personal assistants like Siri, Alexa and Google home to smart watches tracking your steps, heart rates and sleep patterns, and mobile applications directing fitness and mental health, this amalgamation of technology and biology has made its way into everyone’s life. This is just the beginning, and we have a long way to go in the exploration of applications of this unique innovation.
Various emerging Industry Applications:
- Medical imaging: Many companies today are involving Artificial Intelligence – associated platforms in the medical field for scanning devices in order to improve image clarity and clinical outcomes. This is done by reducing exposure to radiation (For Example: CT scans for liver and kidney lesions).
- Management of chronic diseases: Machine learning is being integrated into devices like sensors, to detect, monitor and automate the delivery of treatment. This reduces manpower and increases efficiency.
- Drug discovery: A number of applications are there which involve the use of AI with drugs. This includes designing of drugs, polypharmacology, drug repurposing, screening of drugs and chemical synthesis.
- Telemedicine: Electronic consultations, medicine management and analyzing medical records and other data of the patients drastically helps the doctors, nurses as well as the patients. Today’s technology has enabled telemedicine to be an emerging field and has helped millions across the globe, especially during the trying times of the Covid-19 pandemic.
- Robot assisted surgeries: Data from real surgical processes are collected by cognitive surgical robotics to improve on and improve the already existing approaches to surgery. This greatly helps with minimizing the patient’s treatment time and chance or probability of error.
These are a few upcoming trends amongst various others.
Noteworthy examples of Integration of artificial intelligence in healthcare:
KENSCI is a company targeted towards AI for hospital risk prediction. Its main goal is to combine artificial intelligence and big data to predict financial, operational and clinical risk in hospitals. It takes data from different and existing sources, which can then predict who may get sick and also keeps hospital costs in check.
- XTALPI (Cloud based digital drug discovery)
This unique technology combines cloud and quantum physics which results in the prediction of small molecules’ chemical and pharmaceutical properties which plays an extremely important role in drug design and development, and thus, drug discovery. This company has a polymorph prediction i.e., crystal structure prediction technology, which is able to predict complex molecular systems and structures within days, as compared to the normal time of weeks and months.
Atom wise constitutes a neural network for clinical trials, known as Atom Net. This helps to identify differing biological activity of patients, including their characteristics. The technology can screen anywhere between 10 to 20 million genetic compounds every day and has been found to deliver results 100 times faster than other competitive pharmaceutical companies in the markets. Clinical trials are essential for new discovery of pharmaceuticals and vaccines, and this practice is helping us move toward a cure for serious diseases, including Ebola and multiple sclerosis.
- DEEP GENOMICS
This is a Canadian based platform which aims at helping researchers find candidates that would be compatible with drugs that are mainly targeted towards neuromuscular and neurodegenerative disorders. Finding the right candidate can improve chances of successful clinical trials. This also aids in the revolutionizing stream of personal medicine.