From chemometrics to foundation models in pharmaceutical analysis: Current evidence, limitations, and future directions
Year: 2026
Type: article
Abstract: Pharmaceutical analysis has always been shaped by a careful dialogue between measurement and meaning. Early chemometric approaches brought structure to this dialogue, allowing scientists to uncover patterns within complex chemical data and to make informed decisions about quality, identity, and safety. In recent years, this landscape has begun to change, as more flexible and data-rich modeling strategies—often described as Foundation models—enter the field. These newer approaches offer the possibility of learning from diverse datasets and adapting across analytical contexts, raising expectations for faster and more integrated workflows. Yet, this progress also invites reflection. The growing reliance on large and often opaque models challenges long-standing values in pharmaceutical science, particularly the need for transparency, robustness, and trust. Questions remain about how well such systems capture underlying chemical realities, how they perform under constrained or imperfect data conditions, and how they can be aligned with regulatory standards. This review traces the path from traditional chemometric methods to emerging model paradigms, highlighting both continuity and change. It considers current evidence, outlines practical and conceptual limitations, and explores future directions that balance innovation with responsibility. Despite these advances, this review is limited by the scarcity of validated foundation-model studies in pharmaceutical analysis, the lack of standardized benchmark datasets, and evolving regulatory guidance, which restrict firm conclusions regarding routine industrial implementation. In doing so, it argues that the future of pharmaceutical analysis will depend not only on technological advancement but also on preserving the interpretive insight and critical thinking that have long defined the field.
Source: Current Pharmaceutical Analysis
Author: Annasaheb S. Gaikwad
Language: English
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,100
OpenAlex ID: W7202288148