Biography
Biography: Dina Shokry
Abstract
Most of the new released drug compounds are formulated as orally administered drugs due to the convenience of the oral administration route. However, the properties of some compounds could be incompatible with oral administration. In fact, major fi nancial losses were suff ered by pharmaceutical industry because some new drugs were discovered to have poor bioavailability aft er their oral administration when tested in later clinical stage of development. Th erefore, drugs with poor aqueous solubility and oral bioavailability that are considered poor candidates should be spotted as soon as possible before reaching fi nal clinical stages of development where the costs spent on research carried out in such stages for studying the
biopharmaceutical properties of the drug is signifi cantly high, it is even better to discover these properties before the drug is synthesized to save time and money. Over the past three decades, there has been growing interest in the prediction of the biopharmaceutical properties as aqueous solubility and intestinal permeability of new drug entities (NDE) that resulted in the development of a large number of experimental (in vitro and in situ) and mathematical models. In addition to being cost
effective and time saving, some of these models help in the determination of best drug candidates during drug discovery and
development stage. Drug intestinal permeability is one of the most important biopharmaceutical properties that are worth investigating and predicting using the previously mentioned models. In the spectroscopic and permeation methods, we
developed mathematical models generated for prediction of human intestinal absorption (HIA) through the determination
of the micelle/water partition coeffi cients (logKxm/a) for a series of 20 compounds using UV spectroscopy and also through
determination of the permeation constants (log Kp) of a number of drugs through gels made from bile salt saturated with
infi nite dose of these drugs. Prediction models with good predictability were developed using the obtained data from both
methods along with the reference absorption data and other physicochemical properties to develop prediction equations
through simple and multiple linear regression respectively. In another work, we developed a model using MLC method which
was proved successful for prediction of HIA.