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Triple Analysis: Breast Cancer, Melanoma and Peptides

  • June 2013
  • -
  • Bioseeker
  • -
  • 3949 pages

This triple analysis focuses on cancer drug development strategies in both Breast Cancer and Melanoma and by the compound strategy of Peptides. Each of these three individual parts is evaluated according to standardized criteria in a five pillar pipeline drug assessment methodology to compare drug development strategies in oncology. This makes it easy to find and compare analysis not only within one single cancer focus area but also between different areas.

Below is a short synopsis of each part included in this report:

Part I: Breast Cancer
The breast cancer drug report part comprises defined and up to date development strategies for 470 drugs within the portfolio of 247 companies world-wide, from Ceased to Marketed. The report extensively analyses their 234 identified drug targets, organized into 223 drug target strategies, and assesses them in breast cancer drug development.
This part is based on the following publication:
Commercializing Breast Cancer Drugs: The Faster Route to Consider Your Options and Position of Others

Part II: Melanoma
The melanoma drug report part comprises defined and up to date development strategies for 282 drugs within the portfolio of 164 companies world-wide, from Ceased to Marketed. The report extensively analyses their 226 identified drug targets, organized into 187 drug target strategies, and assesses them in melanoma.
This part is based on the following publication:
Melanoma Drug Development Analysis: From First-in-Class to Best-in-Class?

Part III: Peptides
The peptide drug report part comprises defined and up to date development strategies for 171 drugs in oncology within the portfolio of 114 companies world-wide, from Ceased to Marketed. The report extensively analyses their 132 identified drug targets, organized into 109 drug target strategies, and assesses them in 62 cancer indications.
This part is based on the following publication:
Cancer Peptides: From First-in-Class to Best-in-Class?

The report is written for you to understand and assess the impact of competitor entry and corresponding changes to development strategies for your own portfolio products. It helps teams to maximize molecule value by selecting optimal development plans and manage risk and uncertainty. The report serves as an external commercial advocate for pharmaceutical companies’ pipeline and portfolio planning (PPP) in cancer by:

* Providing you with competitive input to the R&D organization to guide development of early product ideas and ensure efforts are aligned with business objectives

* Assisting you to make informed decisions in selecting cancer indications that are known to be appropriate for your drug’s properties

* Analyzing, correlating and integrating valuable data sources in order to provide accurate data for valuation of pipeline, in-licensing and new business opportunities

* Providing you with commercial analytic support for due diligence on in-licensing and acquisition opportunities

* Supporting development of integrative molecule, pathway and disease area strategies

* Integrating knowledge for you to consider the therapeutic target for the highest therapeutic outcome and return on investment

This report provides systems, analytical and strategic support both internally to PPP and to stakeholders across your own organization. The report will also be an important part of creating and implementing a market development plan for cancer drugs to insure that the optimal market conditions exist by the time the products are commercialized.

Table Of Contents

Triple Analysis: Breast Cancer, Melanoma and Peptides
Key Topics Covered:

Part I: Breast Cancer
5.1 The Scope of this Report 32
6 Consider the Therapeutic Target Among Breast Cancer Drugs for the Highest Therapeutic Outcome and Return on Investment (234 Drug Targets) 36-522
7 Emerging New Products to Established Ones: Drug Target Strategies of Breast Cancer Drugs by their Highest Stage of Development (223 Drug Target Strategies and 470 Drugs) 523-797
8 Compound Strategies at Work: Competitive Benchmarking of Breast Cancer Drugs by Compound Strategy (8 Compound Strategies) 798-850
9 Pipeline and Portfolio Planning: Competitive Benchmarking of the Breast Cancer Drug Pipeline by Investigator (247 Investigators and 470 Drugs) 851-1723
10 Disclaimer 1724
Figures: Includes 8 Figures
Tables: Includes 309 Tables
Total Number of Pages: 1,755

Part II: Melanoma
5.1 The Scope of this Report 26
6 Consider the Therapeutic Target Among Melanoma Drugs for the Highest Therapeutic Outcome and Return on Investment (226 Drug Targets) 30-467
7 First-in-Class and Me-too Analysis of Melanoma Drugs (187 Drug Target Strategies and 282 Drugs) 468-677
8 Is First-in-Class the Best-in-Class? 488-678
9 Compound Strategies at Work: Competitive Benchmarking of Melanoma Drugs by Compound Strategy (7 Compound Strategies) 679-710
10 The Competition Through Close Mechanistic Approximation of Melanoma Drugs 711
11 Pipeline and Portfolio Planning: Competitive Benchmarking of the Melanoma Drug Pipeline by Company (164 Companies and 282 Drugs) 716-1165
12 Disclaimer 1166
Figures: Includes 5 Figures
Tables: Includes 222 Tables
Total Number of Pages: 1,181

Part III: Peptides
5.1 The Scope of this Report 27
6 Consider the Therapeutic Target Among Peptide Drugs in Cancer for the Highest Therapeutic Outcome and Return on Investment (132 Drug Targets) 31-252
7 First-in-Class and Me-too Analysis of Peptide Drugs in Cancer (109 Drug Target Strategies and 171 Drugs) 253-267
8 Is First-in-Class the Best-in-Class? (109 Drug Target Strategies and 171 Drugs) 268-387
9 The Competition through Close Mechanistic Approximation of Peptide Drugs in Cancer 388
10 Selecting Indication for Peptide Drugs in Oncology ( 62 Cancer Indications) 391-475
11 Pipeline and Portfolio Planning: Competitive Benchmarking of the Cancer Peptide Drug Pipeline by Investigator (114 Investigators and 171 Drugs) 476-1001
12 Disclaimer 1002
Figures: Includes 5 Figures
Tables: Includes 232 Tables
Total Number of Pages: 1,013

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