AI is all the rage in pharma at the moment. With its ability to make predictions and provide insights, it can help pharmaceutical companies across a number of different areas.
Artificial intelligence is a growing technological field with many applications for the pharmaceutical industry. In fact, AI can be applied in a variety of ways to help pharma companies work more efficiently and cost-effectively. The way it’s being applied to the pharmaceutical industry has many benefits, like increased accuracy and improved customer experience. It can also make drug discovery faster and more affordable, improve healthcare outcomes, and help patients find the right treatment for their condition much quicker.
There are different areas where AI technology could be applied in pharmaceuticals.
- AI in identifying molecular structure in drugs.
Identifying molecular structure is built on the molecular graph that is a common machine-readable representation. In this case, molecular nodes are represented using letters instead of traditional circles or spheres and points at the place where the bonds meet. Based on this, there were developed different algorithms for the visualization of compounds in the form of 2D images. The machine learning model predicts 3D information like atomic coordinates, chirality, bond angle based on the 2D graph of its molecular structure.
- Biological reaction to a drug.
The deep learning model predicts reactions based on enzymatic reactions depending on the concentration of the substrate. This approach uses the data from almost 10,000 enzyme-substrate combinations for training data.
- AI in drug discovery
While the process of drug discovery is an important part of creating new medicines, it can be slow and uncertain. The deep level of expertise needed for these campaigns coupled with high failure rates makes them difficult to succeed without ample funding or time.
A successful campaign will often involve many steps from selecting chemical compounds all the way through testing Outcome measures such as effectiveness against disease targets until finally arriving at a treatment that works well enough alone but also stacks up nicely when combined with other drugs.
One way that scientists are trying to speed up their research on drugs by developing computer algorithms called “bioassays” which predict whether compounds will have an active effect against certain target proteins by using fewer chemicals and less time than before; leading towards better drugs with lower failure rates in therapy.
AI has already begun to transform the pharmaceutical industry, and it’s only going to get bigger. In this blog post, we’ve just explored some of the many ways AI is being used in this field.
If you want to get started with AI-powered tools, contact us at info@datapipe, so we can help you find out about how AI could impact your company going forward and stay competitive.