The active phase of a clinical trial is defined by a protocol schema consisting of participant-related events organized into multiple visits. Current efforts to model protocol schemas in a computable format have focused on high-level abstractions, such as the temporal relationships between visits. However, such approaches do not address the need for a more granular computational model of the individual events that comprise each visit. To address the preceding gap in knowledge, this paper will describe a study in which conceptual knowledge acquisition (CKA) techniques were applied to a corpus of 32 clinical trials protocol documents in order to develop a knowledge collection of common participant-related clinical research events. These techniques identified 7 high-level concepts that could be used as organizing principles in the resulting knowledge collection. Such results confirm the utility of CKA methods in the clinical research domain.