Summary
In this chapter, we summarized the types of molecular data and how they are represented. We understood why it’s important to understand molecular data and its role in the drug discovery and design process. Next, we were introduced to the complex process of drug discovery and design. We looked at a few innovations that have advanced the field over the years. We also looked at some common applications of ML in this field. For the technical portion of this chapter, we learned about the use of custom containers in SageMaker. We saw how this option allows us to run custom packages for bioinformatics and cheminformatics on SageMaker. Lastly, we built an ML model to predict the molecular properties of some compounds.
In Chapter 9, Applying Machine Learning to Clinical Trials and Pharmacovigilance, we will look at how ML can optimize the steps of clinical trials and track the adverse effects of drugs.
