Towards Automated Reasoning for Drug Discovery and Pharmaceutical Business Intelligence

Many workers involved in drug discovery will have some early familiarity with the principles of quantum mechanics as applied in chemistry. Certainly those involved in computational chemistry, and particularly molecular modeling, will do so. This familiarity will however be in regard to the algebraic systems based on the imaginary number i that is required for wave mechanics and hence study of molecular properties. This does not exhaust the scope of quantum mechanics, and following an argument by Dirac, the larger picture including more flavors of imaginary number should be applicable to all aspects of human thought where numbers are involved. This includes probabilistic semantics and the construction of probabilistic networks that not only capture knowledge, but perform inference of a more general value to the pharmaceutical industry.