Catalog number: 0210GEP
Publication date: February 2010
Company-wide electronic copy: $3,975

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Introduction

The growth and propagation of mammalian cells in culture is a routine but critical precursor to the investigation of such fundamental cellular processes as gene expression and protein function and to the development of therapeutics. Cell culture products are widely used not only by scientists working with traditional cell lines but also by researchers engaged in experiments with such emerging model systems as stem cells and engineered cell lines.

This Cell Culture Dashboard was developed based upon the aggregated responses to a 22-question survey completed by more than 480 scientists actively engaged in mammalian cell culture predominantly located in North America and Europe. This Dashboard reveals key market indicators for the research market for cell culture products as a whole as well as for the following product segments:

• Basal media
• Fetal bovine serum
• Animal sera
• Balanced salt solutions
• Serum free media
• Dry powdered media
• Growth and attachment factors

Percepta’s 2010 Cell Culture Dashboard™ the third in a series of reports that examines the characteristics and dynamics of the market for cell culture products. This 2010 Dashboard provides a snapshot of the current market landscape that can be compared with data from the 2008 and 2007 Cell Culture Dashboards, providing an ongoing story of how the market is adapting to new products, new competitors, new culture methods, and new sales and marketing strategies.

Survey Methodology

In June of 2010, Percepta fielded the Mammalian Cell Culture Survey to a subset of the Percepta BioAnalytix™ Panel of life scientists. Individuals were invited by e-mail blast to click through to a webpage at perceptabioanalytix.com where the survey was hosted. Invitations were delivered on June 15, 2010 and results collected through June 30, 2010. A total of 570 scientists participated in the survey, of which 481 are actively engaged in performing mammalian cell culture and 4 plan to culture mammalian cells in the next 12 months. Results based on the aggregate of collected responses are revealed in this Cell Culture Dashboard.

Important Note: This report only includes analyses related to the research market for cell culture products and not the market for products used in bioproduction or pharmaceutical manufacturing.

Respondent Demographics

Respondents from the academic, government and commercial market segments are well represented. 54.2% of respondents work at universities, colleges, or medical schools, while 9.2% are employed at hospitals or medical centers. 18.4% of respondents work for biotechnology companies, while 9.4% are employed by pharmaceutical companies. Overall, 28.5% of respondents work in industrial laboratories.

75.7% of respondents are from North America (68.9% in the United States and 6.8% in Canada), while 23.9% reside in Europe.

Junior (Lab Tech, Grad Students), mid level (Post-Doc, Lab Manager) and senior (Professor/PI, Group Leader) scientists are well represented in the data set, with the most cited job titles being Scientist/Senior Scientist (29.6% of respondents) and Professor/Principal Investigator (17.1%).

A wide variety of scientific areas of specialization is also evident, led by cell biology (indicated by 25.8% of respondents as their primary area of expertise), biochemistry (13.2%), immunology (9.8%), microbiology / infectious disease / virology (8.5%) and oncology (7.4%).

Small (1-5 scientists), medium (6-20 scientists) and large (>20 scientists) laboratories are well represented. 46.3% of respondents are from laboratories where between 1 and 5 scientists perform cell culture. 44.9% of respondents work in labs where between 6 and 20 people culture mammalian cells, while the remaining 8.8% are from labs where more than 20 people perform this technique.

Table of Contents

• 6 Figures and Tables
• 10 Executive Summary
• 12 Key Findings and Implications
• 16 Gene Expression Profiling Dashboard
• 20 Gene Expression Profiling Market Opportunity Matrix
• 22 Survey Methodology
• 24 Survey Invitation Text
• 25 Respondent Demographics
• 37 Frequency of Performance of Life Science Techniques
• 42 Frequency of Performance of Gene Expression Profiling Methods
• 68 Reaction Throughput and Market Growth Rates
• 75 Respondent’s Stated Price Per Reaction
• 78 Total Market Size, Market Segment Sizes and Total Market Growth Rate
• 80 Market Shares by Segment (Share of Mention)
• 101 Customer Satisfaction And Interest In Switching Suppliers
• 109 Product Features That Influence Purchasing Decisions
• 113 Gene Expression Profiling Applications
• 147 Desired Changes to Gene Expression Profiling Products
• 154 Survey Questionnaire

Figures and Tables

• 27 Figure 1: Respondent’s Place of Employment
• 29 Figure 2: Respondent’s Country/Region
• 31 Figure 3: Respondent’s Job Title
• 33 Figure 4: Respondent’s Areas of Expertise/Specialization
• 36 Figure 5: Number of Employees in Respondent’s Laboratories
• 39 Figure 6: Percentage of Respondents Performing Various Techniques at Least a Few Times per Year
• 45 Figure 7: Percentage of Respondents Performing Gene Expression Profiling Experiments
• 46 Figure 7A: Change in Percentage of Respondents Performing Gene Expression Profiling Experiments
• 47 Figure 8: Percentage of Respondents Performing Various Gene Expression Profiling Techniques at Least a Few Times per Year
• 49 Figure 9: Percentage of Respondents That Perform Differential Gene Expression Studies Using Multiplex PCR
• 50 Figure 9A: Change in Percentage of Respondents That Perform Differential Gene Expression Studies Using Multiplex PCR
• 51 Figure 10: Percentage of Respondents That Perform Digital Gene Expression Studies/ Molecular Barcodes
• 52 Figure 11: Percentage of Respondents That Perform Microarray-Based Gene Expression Studies
• 53 Figure 11A: Change in Percentage of Respondents That Perform Microarray-Based Gene Expression Studies
• 54 Figure 12: Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 55 Figure 12A: Change in Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 56 Figure 13: Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 57 Figure 13A: Change in Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 58 Figure 14: Percentage of Respondents That Perform Northern Blot Analysis
• 59 Figure 14A: Change in Percentage of Respondents That Perform Northern Blot Analysis
• 60 Figure 15: Percentage of Respondents That Perform Serial Analysis of Gene Expression (SAGE) Studies
• 61 Figure 15A: Change in Percentage of Percentage of Respondents That Perform Serial Analysis of Gene Expression (SAGE) Studies
• 62 Figure 16: Percentage of Respondents That Perform Transcriptome Studies Using Tiling Arrays
• 63 Figure 17: Percentage of Respondents That Perform Transcriptome Studies via Short Read Sequencing
• 84 Figure 18: Respondent’s Primary Supplier for Differential Gene Expression Studies Using Multiplex PCR
• 86 Figure 19: Respondent’s Primary Supplier for Microarray-Based Gene Expression Studies
• 88 Figure 19A: Change in Respondent’s Primary Supplier for Microarray-Based Gene Expression Studies
• 89 Figure 20: Respondent’s Primary Supplier for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 91 Figure 20A: Change in Respondent’s Primary Supplier for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 92 Figure 21: Respondent’s Primary Supplier for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 94 Figure 21A: Change in Respondent’s Primary Supplier for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 95 Figure 22: Respondent’s Primary Supplier for Northern Blot Analysis
• 97 Figure 23: Respondent’s Primary Supplier for Transcriptome Studies via Short Read Sequencing
• 103 Figure 24: Respondent Satisfaction with Current Gene Expression Profiling Methods
• 107 Figure 25: Percentage of Respondents That Have Switched Suppliers in the Last Six Months
• 111 Figure 26: Most Important Features of Products for Gene Expression Profiling Experiments
• 117 Figure 27: Respondent’s Primary Downstream Application for Differentia l Gene Expression Studies Using Multiplex PCR
• 119 Figure 28: Respondent’s Primary Downstream Application for Microarray-Based Gene Expression Studies
• 121 Figure 29: Respondent’s Primary Downstream Application for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 123 Figure 30: Respondent’s Primary Downstream Application for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 125 Figure 31: Respondent’s Primary Downstream Application for Northern Blot Analysis
• 127 Figure 32: Respondent’s Primary Downstream Application for Transcriptome Studies via Short Read Sequencing
• 133 Figure 33: Types of Analyses Performed by Respondents for Differential Gene Expression Studies Using Multiplex PCR
• 135 Figure 34: Types of Analyses Performed by Respondents for Microarray-Based Gene Expression Studies
• 137 Figure 35: Types of Analyses Performed by Respondents for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 139 Figure 36: Types of Analyses Performed by Respondents for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 141 Figure 37: Types of Analyses Performed by Respondents for Northern Blot Analysis
• 143 Figure 38: Types of Analyses Performed by Respondents for Transcriptome Studies via Short Read Sequencing

• 34 Table 1: Respondent’s Areas of Expertise/Specialization (Values for Figure 4)
• 40 Table 2: Frequency of Performance of Various Techniques
• 41 Table 3: Frequency of Co-Performance of Various Life Science Techniques
• 48 Table 4: Frequency of Performance of Gene Expression Profiling Methods
• 65 Table 5: Frequency of Co-Performance of Life Science Techniques with Gene Expression Profiling Methods
• 66 Table 6: Frequency of Co-Performance of Gene Expression Profiling Methods with Life Science Techniques
• 67 Table 7: Frequency of Co-Performance of Gene Expression Profiling Methods
• 70 Table 8: Median and Average Monthly Throughput for Gene Expression Profiling Products
• 71 Table 9: Percentage of Respondents Processing Various Numbers of Expression Profiling Samples Per Month
• 72 Table 10: Highest Throughput Users: Comparison to 2008 Life Science Dashboard
• 74 Table 11: Projected Growth in the Performance of Various Gene Expression Profiling Techniques
• 77 Table 12: Median and Average Price Per Prep for Gene Expression Profiling Products
• 79 Table 13: Estimated Market Size for Gene Expression Profiling Products
• 99 Table 14: Market Share Leaders for Gene Expression Profiling Products
• 100 Table 15: Number of Mentions as Primary Supplier for Methods with Low Numbers of Respondents
• 104 Table 16: Percentage of Respondents Satisfied with Various Gene Expression Profiling Products and Reasons for Dissatisfaction
• 105 Table 17: Respondent’s Interest in Switching to a New Supplier for Gene Expression Profiling Systems: Comparison to 2008 Dashboard
• 108 Table 18: Previous Suppliers for Respondents That Have Switched Supplier for Gene Expression Profiling Methods Over the Last Six Months
• 112 Table 19: Most Important Features of Products for Gene Expression Profiling Experiments – Comparison to 2007 Gene Expression Profiling Dashboard
• 129 Table 20: Respondent’s Primary Application After Various Gene Expression Profiling Methods
• 130 Table 21: Number of Mentions of Primary Downstream Applications for Methods with Low Numbers of Respondents
• 145 Table 22: Types of Analyses Performed by Respondents Using Various Gene Expression Profiling Methods
• 146 Table 23: Number of Mentions of Types of Analyses Performed for Methods with Low Numbers of Respondents

Available upon request