The article examines the complex interaction between the absorptive capacity of scientific knowledge, strategies of external technology search (intensity and scale) and their combined impact on the generation of technological innovations in the context of a circular economy. A formalized conceptual framework integrating organizational learning theory and network analysis is presented. Semantic-mathematical models for quantitative assessment of the efficiency of knowledge flows in interdisciplinary scientific and technical programs are developed. Empirical verification of the models is carried out on the basis of data from a target program in the chemical engineering sphere using ZINB regression. The results demonstrate a significant synergistic effect between scientific competencies and external search, and confirm the critical role of endogenous knowledge generation for the transition to circular economic models.