The Topological Polar Surface Area (TPSA) is a core molecular descriptor in pharmacology, whose spatial distribution across chemical spaces has historically been treated as a continuous variable. This study introduces a normative geometric framework in which TPSA is quantized as a function of the fundamental Bohr area unit L0=a_0^2=28003 Å^2. Utilizing a pure logarithmic grid model (m=0) derived from a three-dimensional spatial resonance constant A=1.1547, we evaluated three independent datasets:120 clinically approved synthetic drugs, and 50 failed or market-withdrawn compounds.The results reveal a radical statistical asymmetry: the successful drug cohort structurally couples to the discrete nodes of the lattice with extreme mathematical significance (P = 0.0002) and a compressed mean residual of 0.030. Conversely, the failed drug cohort exhibits a distribution indistinguishable from stochastic background noise (P-value 0.30). This paper elucidates the computational behavior of Monte Carlo simulations under highly dense grid topologies and formalizes a zero-parameter biophysical screening route capable of pre-clinically anticipating molecular viability.