Since the discovery by Toms in 1948, which revealed how the addition of high molecular weight polymers in turbulent flow through pipes can drastically reduce pressure drop, this phenomenon has been widely studied. Numerous studies have been conducted with the aim of improving industrial processes, making them more cost-effective and efficient. In long pipelines, frictional losses between the fluid and the wall are responsible for nearly the entire pressure drop and, consequently, the energy consumption required for fluid transport. While the friction reduction due to the addition of long-chain polymers in single-phase liquid flows through pipes is well-documented, its application in two-phase flow remains less explored in the literature. This work aims to contribute to the understanding of the effects of injecting drag-reducing polymers in gas-liquid two-phase flow, focusing on the performance and degradation of polyisobutene, which is widely used in the oil and gas industry. The potential for friction reduction in the liquid phase and the degradation of the polymer caused by continuous shear and turbulence were evaluated. The tests were conducted on a rotating circular pipe apparatus, an innovative setup that replicates the results of conventional test benches but requires less product and eliminates the need for additional pumps that could accelerate polymer degradation. The study involved testing three concentrations of polyisobutene mixed with a C12 solvent: 100, 80, 60, and 40 ppm. Degradation tests conducted over 3 hours at a fixed Reynolds number of 26,630 indicated friction reduction levels of 20%, 13%, 14%, and 9%, respectively, depending on polymer concentration. The friction reduction gradually declined to zero after approximately 150 minutes. The polymer degradation time showed little dependency on the tested concentrations. The results highlight its applicability in industry. Additional studies, incorporating variables such as Reynolds number, temperature, pressure, and longer testing durations, are recommended to better assess its performance under real-world conditions.