For the pharmaceutical industry, the preformulation screening of the compatibility of drug and polymeric excipients can often be time-consuming because of the use of trial-and-error approaches. This is also the case for selecting highly effective polymeric excipients for forming molecular dispersions in order to improve the dissolution and subsequent bio-availability of a poorly soluble drug. Previously, we developed a new thermal imaging-based rapid screening method, thermal analysis by structure characterization (TASC), which can rapidly detect the melting point depression of a crystalline drug in the presence of a polymeric material. In this study, we used melting point depression as an indicator of drug solubility in a polymer and further explored the potential of using the TASC method to rapidly screen and identify polymers in which a drug is likely to have high solubility. Here, we used a data bank of 5 model drugs and 10 different pharmaceutical grade polymers to validate the screening potential of TASC. The data indicated that TASC could provide significant improvement in the screening speed and reduce the materials used without compromising the sensitivity of detection. It should be highlighted that the current method is a screening method rather than a method that provides absolute measurement of the degree of solubility of a drug in a polymer. The results of this study confirmed that the TASC results of each drug-polymer pair could be used in data matrices to indicate the presence of significant interaction and solubility of the drug in the polymer. This forms the foundation for automating the screening process using artificial intelligence.