Bringing candidate drugs to market quickly and cost-effectively and pinpointing and eliminating failures from drug development pathways early helps to reduce costs and maintain a competitive edge. A typical research lab will have a range of analytical instruments with bespoke workflows, and the consequent fragmentation of vendor-specific data analysis tools prevents an enterprise from realising full value from the data generated.
Organisations are seeking to unify their instrumentation infrastructure into a cohesive analytical engine that accelerates drug discovery and development, reduces processing bottlenecks and better uses skilled scientific resources. This is only possible when data from diverse modalities are connected and processed in a streamlined, vendor-agnostic software platform.
The mass spectrometry (MS) data systems market reached USD $413M in 2023 with projected growth to USD $560M by 2028.1 This expansion is driven primarily by the rapid growth of the pharmaceutical and biopharmaceutical industries, growing government investment, public and environmental health concerns, and the integration of artificial intelligence (AI).2
The complex structures of advanced pharmaceutical products, such as biologics and biosimilars, are increasing the demand for advanced testing using MS technologies and their derivative analytical modalities, such as ion mobility, matrix-assisted laser desorption/ionisation (MALDI) and MS imaging, to identify and quantify thousands of small molecules, metabolites and biomolecules with high accuracy and sensitivity. MS analysis provides the deep structural insights and critical quality attributes (CQAs) that improve drug candidate evaluation and shorten time-to-insight in the research and development (R&D) process for pharma and biopharma companies.3
