The solid-state chemistry area has received increased attention in the pharmaceutical research and development activities. The comprehension of the solid-state properties of an active pharmaceutical ingredient (API) is critical in the development of formulations due to their impact on the bioavailability and solubility of the final drug, being essential to ensure therapeutic benefit, optimize development and allow a proper intellectual property protection. This research investigates science and technology indicators in the solid-state chemistry area using data science tools applied to scientific publications and patent documents, aiming to contribute to the increase of the competitiveness of the pharmaceutical industry in Brazil and in other emerging markets. Through data science tools, a methodology based on text mining techniques associated to fuzzy relations is proposed. This methodology for identifying specific competencies is applied in the solid-state chemistry area exploring a case study of the discovery of a new polymorphic form of the API dexamethasone acetate. The results reveal the existence of scientific competencies in solid-state chemistry in Brazil. However, when compared to the global university-company interaction, the local pharmaceutical industry shows a lower stage of competitiveness and development. On the other hand, the results indicates the robustness of the methodology and its ability to identify researchers in specific areas, offering solutions to support the decision making and identification of researchers relevant to the development of the pharmaceutical sector.