市場調查報告書
商品編碼
1398862
單細胞分析:技術成長機會Single-cell Analysis: Technology Growth Opportunities |
單細胞分析的技術進步將帶來新的診斷和治療機會。
單細胞分析可以透過研究細胞內基因組學、轉錄組學、蛋白質組學、代謝組學和其他細胞間相互作用來診斷異質細胞群樣本的狀態。它將幫助我們更好地了解腫瘤微環境,並根據新發現的不同腫瘤類型的知識來開發藥物。這種分析方法產生的大量資料可以深入了解基因表現和決定病理的其他因素。
這種方法引起了投資者和研究機構的關注,因為它推進了現有的診斷和藥物研發方法,但它也存在技術挑戰(必須透過技術平台的進步來克服),並且存在一個以大測序為主導的高度競爭的環境已經成長為提供小公司無法提供的端到端解決方案的公司。
許多公司在基因組和轉錄組層面進行單細胞分析,但只有少數公司進行蛋白質體學和多組體學單細胞分析。技術的進步有助於避免繁瑣的過程,例如在文庫製備過程中透過獨特的條碼過程進行單細胞分離。空間體學和活細胞測序等現代方法也補充了現有的單細胞分析過程。這種方法的主要挑戰之一是測序結果的資料分析,這是透過雲端平台解決的,無需任何生物資訊經驗即可操作。使用這種分析方法對尚未理解的主題進行研究有很大的空間,我們確信這種方法將在未來十年內顯著成長,希望不僅能改善癌症的診斷,還能改善其他疾病的診斷。
該研究確定了該行業的挑戰、促進因素、新技術平台和成長機會,並預測了成長前景。它還確定了利益相關相關人員和市場參與企業應該利用的著名併購、資金籌措和合作夥伴關係,並概述了相關人員生態系統。
Technological advancements in single-cell analysis propel new diagnostic and therapeutic opportunities.
Single-cell analysis can diagnose a condition in heterogenous cell population samples by studying genomics, transcriptomics, proteomics, metabolomics, and other cellular interactions in cells. It helps to understand a tumor microenvironment better and develop drugs based on newly uncovered knowledge of various types of tumors. The rich data provided through this method of analysis gives in-depth insight into gene expression and other factors determining a pathological condition.
As this method is an advancement to already existing methods of diagnosis and drug discovery, it is gaining the attention of investors and research institutions, although there are a few challenges in terms of technology (which must be navigated through advancements in technology platforms) and the monopoly of large sequencing companies that have grown to provide end-to-end solutions that cannot be provided by small and mid-sized companies, creating an intensely competitive environment.
Many companies perform single-cell analysis at the genomic and transcriptomic levels; however, only a few do the same in proteomic and multi-omics single-cell resolution. Technology advancements are helping to bypass tedious processes, such as single-cell separation through a unique barcoding process during library preparation. Modern methods, including spatial omics and live-cell sequencing, are also complementing the existing single-cell analysis process. One of the major challenges in this method is the data analysis of sequenced results, which is being tackled through cloud platforms that operate without the need for prior bioinformatics experience. There is significant scope for research on topics that are underexplored in this method of analysis, which ensures good growth of this technique in the next decade and promises improved diagnosis not only for cancer but also for other diseases.
This study identifies the challenges, drivers, new technology platforms, and growth opportunities in this space and foresees a growth outlook. It also provides an overview of the stakeholder ecosystem, identifying notable mergers and acquisitions, funding, and partnerships for stakeholders and market participants to leverage.