If the success rate percentage of therapies is taken as the ratio of Number of Patients cured to the Number of Patients dosed, the success rate graph will have more of out-rangers than that of the normalization curve. Of course the selected and utilized sample space will be majors to contribute, but the result integers would also be a matter fact of type of disease or disorder and the therapeutic molecule tried. When studies are carried out with complex disease like cancer or the metabolic disorders, the results always seek an interpretation based on the disease condition like stages and the possible outcomes. To generate a more bio-curate analysis, the results are studied with respect to a specific or significant pathway against which the drug or the therapeutic molecule is developed; the nature and type of molecule too accounts.
Most of the time it happens that a specific pathway is not traced within the physio-biological system, the most simulating pathway is now developed utilizing the neural networks program connecting the pathway analysis tools with the databases. The patient outcome research has its value at this interpretable point and help selecting the molecule and the associated clinical experiment design.
This therapeutic success rates will be incomplete with the discussion inclusion of survivor ratio. Is the survivor ration same as therapeutic ratio in any respect? Yes, in a good way it can be. But the importance of the outcomes matters here; the difference can be understood if you speak in regard to some disease. “I was cured” & I survived” the couple words within the special sign has its own importance.Tags: metabolic disorders, Neural Networks