Tao Chen

Meet Tao Chen

Analytical science is a multidisciplinary field dedicated to solving complex problems through accurate and precise measurement, effective data interpretation, and critical thinking. It is far more than a routine support function – it is the backbone of scientific discoveries and applications. By providing the reliable, high-quality data required to interrogate chemical and biological systems, analytical science enables the full cycle of scientific inquiry, experimentation, and informed decision-making across many other disciplines.

In the pharmaceutical industry, analytical science plays a foundational and integrative role across every stage of the drug development pipeline – from early molecule discovery to market-ready therapies. During active pharmaceutical ingredient (API) development, it provides crucial data to elucidate reaction mechanisms, monitor impurity profiles, and optimize synthetic routes. In drug product development, it offers critical insights to guide the selection of excipients and delivery systems, evaluate formulation stability, and determine final dosage forms. These data and insights are essential for process and formulation development as well as manufacturing robustness. Moreover, analytical science safeguards patient safety by ensuring product quality, from verifying critical quality attributes (CQAs) to informing packaging decisions and enabling shelf-life projections.

The importance of analytical science becomes even more pronounced in the development of emerging new modalities, such as biologics, peptides, oligonucleotides, cell and gene therapies. These complex entities present unique structural, functional, and stability challenges that far exceed those of traditional small molecules. Advanced and highly specialized analytical techniques are required to ensure molecular-level characterization, quality attribute identification, and the development of robust control strategies for these new modalities. In addition, the successful implementation of these analytical techniques increasingly depends on cross-functional collaboration.

The COVID-19 pandemic significantly catalyzed the adoption of automation across the pharmaceutical sector, one of the most exciting contributions of analytical science is its capability to enable lab-in-the-loop workflows. In these workflows, high-throughput analytical data with strong fidelity feeds directly into ML and AI models, with output results ingested by automated systems to realize the iterative cycle of design-build-test-learn (DBTL). This transformation, from passively collecting data to actively using them to drive real-time decisions and inform follow-up experiments, is fundamentally reshaping how drugs are developed.

In summary, the point of analytical science lies not only in its capability to measure but also in its ability to generate meaningful understandings. It is both the foundation and engine of pharmaceutical innovation and success, generating the knowledge, insight, and confidence that turn promising molecules into safe, effective medicines. Today, as the field evolves alongside new modalities, automation, and ML/AI, it is one of the most thrilling and rewarding times to be a practitioner of analytical science in the pharmaceutical industry.