You hear all the breakthroughs with artificial intelligence (AI), whether that’s beating five other professional poker players in a game of Texas Holdem, or Waymo’s self-driving car taxi service that’s quickly coming to production, or even finding faster ways to detect breast cancer.
The field of AI is growing exponentially, with discoveries like those happening frequently. But, what’s not that frequent compared to AI, is the progress in healthcare. Recently, there’s been this new field called pharmacogenomics, which is about studying “how genes affect a person’s response to drugs”.
Just like how AI intersects with many fields, pharmacogenomics is the intersection between “pharmacology (the science of drugs) and genomics (the study of genes and functions)”. This new field aims to solve some of the challenges in developing effective and safe personalized medications.
So many intersections!!
But wait … we can also combine AI with pharmacogenomics to help speed the process up faster!
Recently, there’s this paper published by the University of Michigan exploring the intersection of deep learning (a discipline in AI) with pharmacogenomics. Particularly, the three main points that stood out where AI can be used are the following:
1. For patient stratification (subgrouping patient data before sampling) from medical records
2. Prediction of drug response and interactions with the human body
3. Toxicity prediction of certain chemicals/drugs
Before we start…
Let’s get a basic overview of what AI (specifically deep learning) is and understand the current limitations that are holding us back.
Deep learning attempts to replicate how the brain learns and recognizes things, through neural networks. Just like how the brain has neurons that fires off signals to other neurons, a neural network takes on a similar architecture! Chaining together thousands or millions of neurons allows…