Biotechnology - Genomic and Proteomics/Data, narratives and tools produced by the BGP field: Difference between revisions

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**Plasmid
**Plasmid
*** Big players:
*** Big players:
==Dynamics of the Biotech field defined by (Pisano pp. 82)==
# actors (start-ups, established companies, labs, customers)
# institutional arrangements
# rules
All these have changed over time (Pisano pp. 84)
<br>
*'''first generation
** product: large molecules
*** using rDNA and Mab to discover new drugs (Pisano pp. 84)
*** Use single genetic engineering technic to develop a variety of products (Pisano pp. 87)
*** Some of these products would be licensed to pharma companies for production. Some hoped to develop their product vertically, from concept to market
** dynamic: FIPCO
*** smaller projects operated independent of the pharma companies
*** deals with pharma companies to fund large ($300m+) projects (Pisano pp. 86)
*** e.g. Genentech
*** kept extremely close link to universities (Pisano pp. 85)
*'''Second generation'''
** product:
*** novel recombinant proteins - proteins never used in clinical testing but suspected to have positive effects (Pisano pp. 88)
*** monoclonal anitbodies (Mab) - supposed to be able to bind to specific unhealthy cells without harming healthy cells. Were a clinical and financial disappointment (Pisano pp. 88)
*** more willing than first generation companies to look at individual molecules (Pisano pp. 90)
*** In general, these products would be licensed to pharma companies for production
** dynamic:
*** Hope that biotech drugs, because formed from natural human proteins, would be less risky than drugs produced in other fields. When did not happen, money began to dry up (Pisano pp. 90)
*** Companies had to focus more narrowly - hopes often rested on a single project
*** Less hope of becoming fully-integrated pharma companies themselves. Increasingly getting their funding from established pharma firms (Pisano pp. 91)
*'''Third generation'''
** product
*** two groups (Pisano pp. 92):<br/> (1) developing processes for genomics research, licensing their discoveries to other companies<br/> (2) working directly on genomics research through government grants
** dynamic
*** Human Genome Project creates cultural shift – less laborious testing of individual hypotheses, more effort to develop large amounts of data and product (Pisano pp. 92)


==Navigation==
==Navigation==
[[Bibliography for Item 3 in BGP]]<br>
[[Bibliography for Item 3 in BGP]]<br>
[[Biotechnology_-_Genomic_and_Proteomics]]
[[Biotechnology_-_Genomic_and_Proteomics]]

Revision as of 19:35, 14 April 2009

Answer the questions:

  1. Define what kind of data, narratives and tools constitute the outputs of the field and its dynamics (e.g.: data in science may get better if open once it receives annotations and can be improved by other scientist).


Data

File:FundDataMap.jpg

  • Foundational Data
    • Big players:
  • Observational Data
    • Big Players:

Narratives

  • Papers
    • Big players:

Elsevier

PubMed

Nature

Springer

BioMedCentral

Public Library of Science

Wiley Blackwell

Thomson Reuters Science

  • Ontologies
    • Big players:

US National Center for Biomedical Ontology

Science Commons

Open Biomedical Ontologies

Gene Ontology

  • Annotations
    • Big players:

Gene Ontology Annotation

Distributed Annotation System

Gene Wiki

Tools

  • Biological materials, such as:
    • Steam cells
      • Big players:
    • Mice
      • Big players:
    • Plasmid
      • Big players:

Navigation

Bibliography for Item 3 in BGP
Biotechnology_-_Genomic_and_Proteomics