Predicting Drug Interactions In Pharma With ChemicalX Integration

One of many aspects of the pharmaceutical industry includes researching and developing novel drugs for treating different diseases. This process is often expensive and time-consuming. Companies spend around 25% of their yearly budget on research, but only a small number of experiments turns out to be the next big success.

AstraZeneca is one of the industry leaders in the field of drug discovery and development. You might wonder, how does that relate to Memgraph? The core technology used by the industry leaders in the drug discovery field is in fact graph technology. Graphs are an elegant way to represent drug interactions and components participating there.

Now, let’s introduce a concrete example! ChemicalX is a graph machine learning library based on an in-depth understanding of drug interactions. It provides well-known neural network architectures and datasets for drug pair scoring tasks. This blog post will introduce you to the drug discovery world by answering:

As any consumer will probably testify, each drug comes with side effects, but the equation/issue becomes a bit more complicated when drugs are combined as they also interact with each other which can additionally unease the consumer. To relieve some of those concerns, each drug comes with instructions and warning lists larger than average blog posts.

Leave a Comment