Does 'Big Data' exist in medicinal chemistry, and if so, how can it be harnessed?

The term ‘Big Data’ has gained increasing popularity within the chemistry field and across science broadly in recent years. Chemical databases have seen a dramatic growth over the past decade, with, for example, ChEMBL, REAXYS and PubChem providing hundreds of millions of experimental facts for tens of millions of compounds. Moreover, even larger datasets of experimental measurements are held within in-house data collections at pharma companies. Overall, the total number of entries across these databases is in the range of a billion, 10⁹; however, although this number may seem impressive, it pales into comparison relative to other fields, where the amount of data is frequently measured in exabytes, 10¹⁸. Thus, does Big Data really exist within the chemistry field? What are such data within medicinal chemistry specifically and where do the challenges lie in analysis of these data? Big Data refer to data out of the scale of traditional applications, which require efforts beyond the traditional analysis. In this article, we will be discussing how it applies to medicinal chemistry, as well as providing an overview of some of the most important trends in the medicinal chemistry–Big Data field.