Applied Data Research Release: Regional Factors Driven by Genetic Diversity Add Complexity to Autoimmune Disease Drug Development
Published: Jul 25, 2008
Perhaps more than any other disease segment, autoimmune conditions and the companies that market treatments for them are benefiting from the potential for expanded indications. A typical strategy for many drug candidates is to initially target a larger, well-defined segment such as Rheumatoid Arthritis and then pursue secondary indications – for example – Lupus or Psoriasis, once the brand has been launched and established. Such a strategy requires resources and risks that can strain all but the largest players, making alliances highly attractive. Because of the individual genetic variability underlying the incidence and severity of autoimmune symptoms, regional variations in the market for autoimmune therapeutics can be significant. This variability is compounded by differences in treatment protocols and cultural factors, which combine to make alliance partnerships with regional players of increased importance.
The dynamics of therapeutic intellectual property is another factor fostering alliance activity in the autoimmune sector. Because antibody technology forms the basis for much of the current generation of autoimmune disease treatment technology, mid-to-large pharma companies are increasingly in-licensing therapeutic candidates from smaller specialty laboratories, often at the pre-clinical stage. More information is also available at http://www.applieddata.org/Autoimmune_Disease.htm
About Applied Data Applied Data Research is a healthcare therapeutics consulting firm focused on medical market strategies, product commercialization, venture development, and market research. We assist medical market participants in achieving their business objectives through the creation of detailed business development strategies, product commercialization programs, and comprehensive market and technology research and analysis.
Greg Stone Voice: 603-595-6225 Fax: 603-804-0466 www.applieddata.org
Source: Applied Data Research