Alexander Böser

Meet Alexander Böser

Analytical science is the unsung hero of the chemical and pharmaceutical sciences. While advances in drug discovery and synthesis are making headlines, the careful analytical work that establishes structure, purity, and safety silently evolves behind the scenes. That this is the case is not an accident – it reflects systemic problems that conceal analytical science. Advanced regulatory requirements mean any new instrument or technology must undergo rigorous validation, fostering a culture of conservatism. Years pass, and laboratories accumulate technical debt: outdated instruments and data silos that are "good enough" to get by in compliance but too outdated to drive innovation. Together, they all contribute to maintaining an image of analytical teams as sluggish, service-based cost centers and not exciting discovery partners.

It is time to turn the script around. Analytical science is not an optional tick-box exercise for other functions; it is a strategic science and essential to scientific progress. No new medicine or material can be deemed viable without robust analytical evidence of its identity, purity, and function. Analytical scientists guarantee product quality and regulatory acceptability in everyday use – tasks with direct relevance to patient and consumer safety. Also, they have unrealized potential to accelerate innovation: information gleaned from sophisticated data analytics, chromatography, or spectroscopy can reveal new chemistry and biology, prompting scientists to better designs. By considering analytical science as a core driver of R&D rather than an end-stage tester, companies can unlock faster development cycles and more predictable results. Realizing this vision requires cultural change.

First, place analytical experts early in R&D and decision-making. Placing analytical scientists in cross‑functional project teams and leadership roles guarantees that potential issues are caught – and creative solutions offered – from the very beginning. If analytical considerations shape experiments and development plans from the outset, teams avoid costly surprises later on. Second, modernize the analytical infrastructure. Companies must invest in new instruments and digital systems that end data silos. A networked, automated lab not only makes researchers more productive but also allows them to focus on interpretation and innovation rather than wrestling with bloated software or isolated data. Finally, promote data stewardship as a scientific imperative. Tend to analytical data like a precious resource: curate it, normalize it, and use it to guide. Strong data sharing and governance practices can make routine results into a machine learning, process improvement, and improved decision-making center of knowledge for the organization. In short, helping analytical science be the star it should be is both an attitude shift and a practical endeavor. It is giving analytical scientists a place at the strategy table, the tools to make it happen, and the recognition that their work is the foundation of every achievement. Through the implementation of these changes, analytical science will be brought into the spotlight as the key force behind all good science – the important factor that maintains the arch of innovation, quality, and compliance in balance.