Skip to content

Bridging the automation gap: Challenges of data processing and analysis

Satnam Surae, chief product officer, Aigenpulse examines how automation can benefit the pharma industry when it comes to data processing and analytics.

Bridging the automation gap: Challenges of data processing and analysis
Published: | 4 min read

Satnam Surae, chief product officer, Aigenpulse examines how automation can benefit the pharma industry when it comes to data processing and analytics.

Automation

The benefits of automation to laboratory analysis have been widely reported over the last decade. As such, the total laboratory automation market is thriving, having been valued at USD 4,315.5 million in 2019, and expected to reach a value of USD 6,301.8 billion by 2025, at a CAGR of 6.6% from 2020–2025.1 As technology innovation progresses at a rapid pace, laboratory automation will continue to permeate a broad range of sectors, from genomics and proteomics to drug discovery and clinical diagnostics, for the foreseeable future.

Increasing throughput, reducing human error, boosting productivity, and saving time and money, for example, are what has cemented automation within pharma and biopharma R&D. Another advantage includes enhanced standardisation for accreditation and certification, where increased accuracy and repeatability throughout laboratory processes – enabled by automating operations – facilitate standardisation, thus ensuring compliance with certification and accreditation procedures.

Sign up to our newsletter

The week's biggest stories from this industry, direct to your inbox.

Personal information