To conclude, we have shown that the Pariser-Parr-Pople theory, a simple semi-empirical 𝜋-electron theory with a minimal valence basis, can be used to screen for molecules with inverted singlet-triplets energy gaps, both locally and globally. Unfortunately, the method does not seem capable of screening for oscillator strengths with the same accuracy, with exceptions for some scaffolds. The chief limitation of the method is that it only includes the 𝜋-electron system and therefore struggles with: (1) functional groups without a clear 𝜎-𝜋 separation (found in common functional groups such as sulfonyls) (2) inductive effects and (3) neglect of 𝑛 → 𝜋 * transitions. Further limitations of the approach used in this study include (4) lack of solvation model and need for (5) already optimized geometries. We believe that at least some of these limitations could be mitigated by a reparametrization specifically targeting inverted gaps, while our preliminary tests indicate that geometries from the fast GFN-xTB family of methods would be suitable. Alternatively, these limitations could be overcome by applying the perturbation theory description of dynamic spin polarization 3 to the more costly but potentially more accurate all-electron semi-empirical methods, such as those of the OMx family. Taken together, we foresee that the presented methodology can be used for ultra-high-throughput virtual screening campaigns and in inverse design algorithms, followed by curation of hits using more accurate quantum-chemical methods. Active learning schemes could also be used with machine learning corrections to the PPP singlet-triplet gaps. The method has great potential to accelerate the discovery of the next generation of OLED materials based on INVEST.