Scientists’ Experiences, Trust, and Meaning in AI-Assisted Drug Design
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Abstract
Artificial intelligence has increasingly transformed medicinal chemistry by enhancing the efficiency and scope of drug design processes. However, little is known about how medicinal chemists experience and interpret the integration of AI in their daily research practices. This study explores how medicinal chemists construct meaning, trust, and professional judgment when using AI in drug design. Using an interpretive phenomenological approach, data were collected through semi-structured interviews with medicinal chemistry professionals and analyzed using Interpretative Phenomenological Analysis (IPA). The findings indicate that AI is experienced both as a tool that accelerates molecular exploration and as a source of epistemic tension that requires ongoing human interpretation. While AI expands scientific imagination and supports decision-making, it also raises challenges related to trust and interpretability. Participants described their evolving role as evaluators and interpreters of AI-generated outputs. This study contributes to the understanding of human–AI interaction in medicinal chemistry by highlighting the importance of combining technological advancement with human-centered interpretation to support responsible drug discovery.
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