The emergence of closed-loop automation systems, digital workflow management practices and IVD regulatory compliance protocols are driving the life sciences industry toward a new paradigm of connected labs.
That’s an analysis proferred by Frost & Sullivan, whose new report forecasts the global life science instrumentation and research tools market to reach $82.57 billion by 2023.
The driving factors: increased spending by biopharmaceutical companies seeking higher efficiencies throughout the clinical development lifecycle. The report says, “Genomics research is taking the center stage and replacing older methods, especially in drug discovery. This segment has now overtaken proteomics arena and is likely to exhibit a faster growth rate over the next five years.”
Called, “Global Life Science Instrumentation and Research Tools Market – Forecast to 2023,” the report evaluates and discusses market projections, key trends, competitors, growth opportunities for existing companies, new entrants, and impact of digital transformation. The research scope includes instruments, equipment, reagents, chemicals, consumables, suppliers and IT solutions used research labs.
“The industry has witnessed a number of mergers and acquisitions over the last 10 years as large companies were looking to aggressively expand their product portfolio and customer base, and we expect that trend to continue,” says Nitin Naik, Life Sciences Global Vice President at Frost & Sullivan. “It is imperative that established players refocus to capture customer lifecycle value rather than just instrument or product sales. Furthermore, players reframing [their] business model to implement turnkey digital workflow solutions will emerge as market leaders in the long term.”
Frost & Sullivan also noted the following additional growth opportunity trends:
• Analytics based-solutions: Applications of laboratory information management system and electronic laboratory notebook systems (LIMS/ELN) will move over tipping point during the forecast period.
• CRISPR-based solutions: This platform has broad applicability (both in vivo and ex vivo) and holds immense potential to leverage machine learning-based tools to automate sgRNA identification from databases and integrate results with LIMS/ELN.
