What makes the initial DMTA cycles particularly challenging is that one first needs to achieve compounds with measurable and preferably on-scale (<50 µM) activity or affinity before common medicinal chemistry design principles become applicable. For this reason, fragment-based efforts have come to rely on large libraries and careful assay cascades to ensure fragment hits are identified with activity or affinity that is reliably measurable, so that they can be progressed with confidence. This draws on best-practice paradigms from High-Throughput Screening (HTS), where rigorous secondary and even tertiary assays are essential for confirming initial hits. Increasingly, however, fragment hits are being exploited that have no measurable affinity yet are readily identifiable and structurally compelling; these are common where protein crystallography is the primary screen and assay concentrations high, a now very accessible technique. Examples include Resnick et al. where such a fragment was merged with a covalent electrophilic fragment hit to achieve on-scale potency; and Boby et al. report how the merging of two such fragments led to an entire drug discovery effort. Algorithmic approaches have also become available: one approach is to ensure structural motifs observed in the fragments are directly recapitulated in the follow-up designs ; another uses the pharmacophoric information from multiple fragments to guide docking ; alternatively, interactions can be assessed and prioritised by Dynamic Undocking. Nevertheless, there invariably remains a long journey, both conceptually and experimentally, from merely onscale potency to the nanomolar potency required of a lead compound or chemical probe, and the ability to cycle DMTA effectively remains the purview of only expert and well-funded organisations. A key cost driver is the continued requirement for sufficiently purified compound, to minimise confounding assay results. Certainly, access to such compounds has been transformed over the last decade, thanks to a vastly expanded landscape of commercial vendors and providers, who have invested heavily in expertise, technology, building block collections and algorithms, thereby eliminating the need for up-front laboratory investment by individual discovery efforts, even for synthetically complex targets. Additionally, progress has been made in recent years to developing low-cost HTS platforms for the synthesis, purification and analysis of compounds. However, it appears that the scale of compound exploration must be at least an order of magnitude larger than can be supported by these evolutions on typical early discovery budgets. For instance, Gao et al. have used "on-the-fly" nanoscale library syntheses by acoustic dispensing to generate large arrays. Elsewhere, surface plasmon resonance (SPR) protocols have been used to identify hits from crude mixtures. Such approaches not only increase the chances of directly identifying potent compound series, they also generate a critical quantity of data to support robust modelling of the structure-activity relationships (SAR). These approaches, however, retain key weaknesses: they can only explore focused regions of chemical space; and the required synthetic approach must be curtailed to accommodate the constraints of the assay readouts. They therefore cannot yet serve as a general approach for generating the data that optimally populates computational models to allow them to effectively identify high-potency compounds.