This research established a simulation based on the hydrophobic subtraction model (HSM) of retention and selectivity and basic liquid chromatography (LC) principles for tandem-column LC. The simulation was used to compare the separation potential of different modes of LC and to guide a method development experiment of a set of pharmaceutical compounds. LC is the most commonly used analytical technique for the analysis of pharmaceutical products. The modern pharmaceutical quality control system requires a high standard of analysis, usually a complete separation of all related compounds in a given pharmaceutical sample. This is often a challenge for conventional single-column LC (SC-LC). However, techniques with higher probability of successful separation, such as two-dimensional LC, require a much higher investment in instrumentation. Tandem-column LC (TC-LC) can use the same instrumentation as conventional SC-LC, but it can provide a higher separation potential than SC-LC (still lower than 2D-LC). A series of simulations were conducted to compare the separation potential of SC-LC and TC-LC. The simulation included 16 HSM reference compounds. More than ten-thousand virtual samples were generated for the simulation. TC-LC showed a significant advantage in the comparisons. The simulation also showed that a TC-LC column inventory can be much smaller than one for SC-LC, but still have a higher separation potential. The simulations of both fixed combinations of tandem-column pair and exchangeable combination of tandem-column pair proved the idea. An optimal order of columns to employ in platform methods or screening was also established based on simulation results. TC-LC uses two columns in-tandem to get a different selectivity than the two columns provide individually. It's therefore challenging to select the columns based on a chromatographer's experience and thus assistance from simulation is necessary or at least very helpful. A new workflow for TC-LC method development was established in the experiments. In this study, HSM solute parameters were experimentally determined for a small molecule pharmaceutical (Linrodostat) and ten of its related impurities using multiple linear regression of their retentions on 16 selected RPLC columns against in-house determined HSM column parameters. R_C values were calculated based on HSM database column parameters for a pool of about 200 available stationary phases in both single-column mode (2.1 mm i.d. ©7 100 mm) or tandem-column paired mode (two 2.1 mm i.d. ©7 50 mm) formats. Four column configurations (two single and two tandem) were predicted to achieve successful separations under isocratic HSM separation conditions, with a fifth tandem pair predicted to have a single co-elution. Of these five potential candidates, one tandem pair yielded compete baseline resolution of the 11-component mixture in an experimental separation. In this specific case, the tandem column pairs outperformed single columns, with better predicted and experimental R_C values for the Linrodostat mixture under the HSM separation conditions. The results reported in this study demonstrated the enormous selectivity potential of TC-LC in pharmaceutical compound separations and are consistent with our previous study that examined the potential of tandem column approaches using purely computational means, though there is room for substantial improvement in the prediction accuracy. The proposed workflow can be used to prioritize a small number of column combinations by computational means before any experiments are conducted. This is highly attractive from the point of view of time and resource savings considering over 200,000 different tandem column pairings are possible using columns for which there is data in the HSM database. This research showed TC-LC is potentially a good approach in analysis of small molecule compounds in pharmaceutical or other related applications. TC-LC can save hardware investment for labs and human resources in method development. It could also be an attractive LC technique in related fields.