Monoclonal antibodies have been established as a major product class of biotechnology-based drugs. The increasing demand of monoclonal antibodies has led pharmaceutical companies to adopt efficient production processes. Transferring monoclonal antibody production to the industrial manufacturing requires adequate effort in process development. The strategy to reduce development time and cost comprises high-throughput process development which is especially central for the rapid optimization of the purification process. Chromatography process is the backbone of the purification process that can deliver high purity but it requires significant resources. Combined with high-throughput process development approach, the chromatography process is easy to develop and scale-up from laboratory to manufacturing scale. Design of experiments helps high-throughput process development workflow to provide decision-support techniques. This approach ensures significantly decreased time and material needs while improving the chromatography process. Protein A affinity chromatography is one of the most important chromatographic steps because of its great performance and capabilities. Most of the working parameters can be predefined and are identical for several monoclonal antibodies. However, some parameters like elution pH, loading capacity, resin type need further optimization for each monoclonal antibody. In this study, the loading and elution parameters were screened for Protein A chromatography to identify the best purification conditions using the combination of Design of Experiments and high-throughput process development approach in micro-volume columns. Developed working parameters were used for scale-up and tested under robust process conditions. Specific chromatography conditions were applied in pilot-scale and data comparison was done with micro-volume columns, lab-column scale to validate high-throughput strategy approach