Cheminformatics, a sub-field of chemometrics, utilizes "Big Data" to answer questions related to chemical synthesis. In particular, it can help to answer the question of how to discover the next (possibly newly synthesized) useful molecule that is easy to produce, and subsequently, evolve that molecule from a theoretical point of view to the production scale. Cheminformatics offers the application of optimization techniques in an interdisciplinary field to answer these questions. It requires insight from computer science, information science, chemistry, operations research, and statistics. Based on a review of the scholarly literature, this work will introduce the landscape of cheminformatic research and its overlap with Industrial Engineering. A short history of the field is provided and current cheminformatic areas are aligned with Industrial Engineering skill sets and interests. The authors discuss three stages of cheminformatic research: 1) capturing data; 2) storing data; and, 3) mining data. Summary tables of research areas, journals, and overlap between cheminformatics and Industrial Engineering are provided in an analysis of published literature to show what challenges are being heavily researched. Finally, a synergy of Industrial Engineering and cheminformatic research is considered for future directions.