Prediction uncertainty assessment of chromatography models using Bayesian inference.

Mechanistic modeling of chromatography has been around in academia for decades and has gained increased support in pharmaceutical companies in recent years. Despite the large number of published successful applications, process development in the pharmaceutical industry today still does not fully benefit from a systematic mechanistic model-based approach. The hesitation on the part of industry to systematically apply mechanistic models can often be attributed to the absence of a general approach for determining if a model is qualified to support decision making in process development.

[The art of medicine].

Not too long ago, obtaining a patient's history and performing a physical examination was the beginning of every doctor-patient interaction. Today, impressing technical methods--extending the human "diagnostic horizon" to an unbelievable level of astonishing perception--are easily available in most places. So the question comes up whether clinical findings still have relevance in common medical practice.