Protein Engineering Market Projected to Reach USD 7.39
From GlobeNewswire: 2024-11-18 10:56:00
The global Protein Engineering Market was valued at USD 2.15 billion in 2023 and is projected to reach USD 7.39 billion by 2032, with a CAGR of 14.72% during 2024-2032. This growth is driven by advancements in protein design technologies, increasing demand for biologics, and applications across healthcare, agriculture, and environmental sectors.
Protein engineering involves designing proteins with enhanced properties for biopharmaceuticals, diagnostics, and industrial use. With increased R&D investments and drug approvals, the market is expanding. Demand for engineered proteins is rising, especially in cancer treatment. Automation and screening technologies are making protein production more cost-effective and scalable.
The consumables segment dominated the protein engineering market in 2023, accounting for 45% due to its crucial role in protein workflows. The software & services segment is expected to grow rapidly with the increasing use of AI and machine learning for protein design.
Rational protein design held a 60% market share in 2023, while irrational protein design is growing due to directed evolution techniques. Key segments include monoclonal antibodies, erythropoietin, and vaccines, with biopharmaceutical companies as major end users.
North America leads the protein engineering market, driven by healthcare infrastructure and major biopharmaceutical companies. The Asia-Pacific region is expected to grow rapidly, fueled by healthcare investments and biopharmaceutical industry expansion.
In January 2024, Agilent Technologies Inc. launched a new product in the protein engineering market, aiming to further advance research and development in the field. An advanced automated parallel capillary electrophoresis system was introduced to streamline protein analysis, providing faster and more accurate data for protein characterization. Northpond-backed Laboratory for Bioengineering Research and Innovation partnered with the Wyss Institute for the AmnioX project to advance protein-based drug development. Astellas Pharma collaborated with Cullgen to discover innovative protein degraders targeting disease-causing proteins. NVIDIA expanded its generative AI cloud services to accelerate the development of novel proteins. Arzeda partnered with Takeda to optimize protein biologics using AI-powered protein design technology. These advancements highlight the integration of AI and machine learning in protein engineering, shaping the future of drug development and medical treatments.
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