The field of medical science has enhanced in the last few years due to new-age technologies. Gone are the days when doctors relied on paper-based prescriptions and reports to offer the best treatment to patients. From precision medicine to surgical practice, many processes in the healthcare industry are dependent on new-age technologies. For example, AI in healthcare IT solutions has bought a paradigm shift in the daily healthcare operations. Among all the healthcare processes, drug discovery relies on new-age technologies like AI (Artificial Intelligence) and Machine Learning (ML). Read on to learn how AI enhances the drug discovery process in the healthcare sector.
Understanding drug discover
Before understanding the importance of AI, one should completely understand the drug discovery process. It is a process used for discovering new candidate medications or new drugs for underlying diseases. Back in the day, drug discovery involved knowing the active ingredients for any remedy. Serendipitous discovery also leads to the knowledge of new drugs for treatment. For example, Penicillin is a popular antibiotic that was discovered by luck/chance. For drug discovery, natural extracts or synthetic molecules are injected into cells or organisms to find their impact. With continuous testing, new drugs or combinations of drugs are identified. Drug discovery can be considered a subfield of medicine and pharmacology.
There can be numerous sources of new drugs for treatment. A new drug can be a plant-based drug for any particular disease. Drug researchers can also produce a synthetic drug that hasn’t been discovered yet. Apart from common healthcare services offerings, organizations are now focusing on research processes like drug discovery and precision medicine. Discovering new drugs that can cure diseases will help the public. Apart from helping the public, organizations can also achieve commercial success with the help of drug discovery. For the same reason, healthcare entities are now investing actively in drug discovery. However, drug discovery isn’t an easy task and comes with many challenges. Let us see how the use of artificial intelligence in the healthcare industry can improve the drug discovery process.
Challenges with drug discovery in the healthcare industry
Why are new-age technologies needed for the success of drug discovery? Well, traditional technologies used in the healthcare industry weren’t capable of handling complex drug discovery tasks. For the same reason, healthcare organizations had to consider a change in the technology stack.
Challenges with drug discovery that demand a better solution like AI are as follows:
- Drug discovery depends on a lot of data analysis. From prescriptions to medical history, several records are analysed to discover the right drug for an underlying disease. However, healthcare organizations weren’t familiar with predictive analytics models and struggled with data analysis. Even if they can perform manual data analysis, they struggle to accumulate healthcare data from different sources. Traditional solutions could not collect healthcare data from different sources round the clock.
- Maintaining interoperability is a challenge for any healthcare organization. In any organization, data is to be shared between applications, departments, and systems for drug discovery. An organization that isn’t fully interoperable can never achieve success in drug discovery. For becoming fully interoperable, AI tools for digital transformation in the healthcare industry are needed.
- Drug discovery starts from research in a lab. It may involve mixing different chemicals and substances to discover a new combination. Researchers usually create paper-based drug discovery reports. How will a digital drug discovery system understand the reports written in human language? Healthcare entities struggle to access information from paper-based reports. AI in healthcare IT solutions has the power to understand the human language easily.
- Drug discovery is a complex process that requires intense focus. Human errors are common in the healthcare industry and can disrupt the drug discovery process. Even due to a single error, researchers may have to start the entire drug discovery process again. Human errors during drug discovery will also increase the overall costs. To stop human errors and improve accuracy, the use of artificial intelligence in healthcare is a must.
As you can see, several challenges prevent researchers succeed in drug discovery. Thanks to AI, there are solutions for the aforementioned challenges. However, AI does not work alone to succeed in drug discovery. A group of new-age technologies is used together for drug discovery.
A group of new-age technologies is used together for drug discovery. The group of new-age technologies used along with AI for drug discovery is as follows:
- Along with AI in healthcare IT solutions, researchers also rely on ML. Predictive analytics models powered by ML can find patterns among data sets. ML algorithms can extract rich insights even from a large data set.
- As discussed above, researchers struggle to access information written in human language via software systems. With the help of NLP (Natural Language Processing), a software system can understand the human language.
- By referring to human language, we aren’t only talking about text. For drug discovery, information needs to be accessed from images, videos, and other graphic content. With the help of CV (Computer Vision), a system can extract information from any graphical content.
- To make accurate predictions during drug discovery, researchers rely on ANNs (Artificial Neural Networks). Predictive analytics models that are based on the human neural network are referred to as ANNs.
Pros of using AI for drug discovery in 2022
Some pros of using artificial intelligence and its subfields for drug discovery are as follows:
- AI offers data-driven drug discovery, which is more efficient than target-based drug discovery.
- Large data sets can be easily analysed with the help of AI/ML algorithms to detect the right drug for any underlying disease.
- Drug researchers often come across proteins with an undefined structure. With AI, researchers can find compounds that can bind themselves with undefined structures.
- The use of artificial intelligence in healthcare reduces the need for pre-requisite. Subjective bias is reduced during drug discovery with the help of AI-led solutions.
AI-led drug discovery can help researchers to slash drug discovery costs. One can move the drug discovery process to a virtual environment from a physical lab with new-age technologies. Boost the drug discovery process with AI in 2022!