5 Outdated Practices Holding Back Modern Bioanalysis

By Ander Tallett, COO, Dash Bio

Bioanalysis is at a critical turning point. While the complexity of molecules and regulatory demands have rapidly evolved, now including ADCs, bispecifics, cell therapies, and gene therapies, many labs still rely on outdated workflows from decades ago. The challenge stems not from science, but from infrastructure and legacy practices that no longer meet today’s needs. Key outdated habits include reliance on paper as the system of record, rebuilding studies from scratch, transferring critical data via email, treating validation as a one-time event, and using people as middleware to manually move data between disjointed systems.

This reliance on manual, fragmented processes creates compliance risks, inefficiencies, and bottlenecks that inhibit real-time decision-making and scale. Regulatory agencies now expect computerized systems with continuous verification and full traceability, making digital-native platforms essential.

Modern bioanalysis infrastructure demands integrated, automated platforms built on version-controlled modules, automated data pipelines, continuous monitoring, and digital audit trails. These systems enable scientists to focus on interpreting data and improving methods rather than administrative tasks, enhancing both speed and scientific rigor.

As drug development increasingly involves complex biologics, global trials, and adaptive protocols, legacy models can no longer keep pace. The future belongs to labs that treat data flow, system integration, and process automation as core competencies, embracing technology that compounds organizational learning and meets the sophistication required for next-generation therapies.