Manipulating In-House Designed Drug Databases For The Prediction of pH-Dependent Aqueous Drug Solubility.

Chemical, pharmacokinetic, and pharmacodynamics properties are available in the package inserts of every Food and Drug Administration (FDA) approved prescription drug, including all available chemotherapy drugs. These inserts follow a specific format imposed by the FDA. Whether chemotherapy drugs are administered via the parenteral route or alimentary tract, a significant factor affecting their bioavailability, elimination and consequently the drug's effectiveness and potency, is its state of aqueous solubility. Water solubility has always lent itself poorly to the different predictive and experimental measures employed in the determination of a useful quantitative assessment. In this project, we first built a chemical structure based searchable database for 85 FDA approved chemotherapy drugs and then used Bio-Rad's KnowItAll® Informatics suite to focus on the drugs pH-dependent water solubility prediction. We compared the predicted values for water solubility to the available values reported in the drug inserts, testing the practical utility and the predictive ability of our model in reporting such a clinically relevant, underreported pharmacokinetic parameter. A relational cancer drug database (MySQL) was created to further facilitate analysis and/or prediction of a chemotherapy compound's missing pharmacokinetic properties.

A Database Developed with Information Extracted from Chemotherapy Drug Package Inserts to Enhance Future Prescriptions.

Package inserts of Food and Drug Administration (FDA) approved prescription drugs, including chemotherapy drugs, must follow a specific format imposed by the FDA. These inserts are created by unrelated pharmaceutical companies and as a result tend to be very different in the way the required information is reported. Chemical and pharmacokinetic properties including absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) are crucial elements to a prescribing information packet and are often missing from the reported data. This undergraduate research project analyzes the information packets of 85 randomly chosen chemically diverse chemotherapy drugs for four parameters important to patient care; viz, volume of distribution (VD), elimination half-life (t1/2), bioavailability, and water solubility. The prescribing information from the package inserts of each was analyzed in detail and pertinent information was consequently tabulated into a database using a commercial informatics platform. Then using a substructure search-tool, sixty-five chemotherapy drugs containing a carbonyl group in their chemical structure were selected and as hypothesized, it was found that many of these packets were significantly lacking in the reporting of the four parameters of interest. To further enhance this cataloged data, a freely available online database was consequently developed (http://annotation.dbi.udel.edu/CancerDB/) with the intention that the chemical, biological, and clinical community will now add some of the missing parameters.

Deficiencies in the reporting of VD and t(1/2) in the FDA approved chemotherapy drug inserts.

Since its release in 2006, the US Food and Drug Administration (FDA) final improved format for prescription drug labeling has revamped the comprehensiveness of drug inserts, including chemotherapy drugs. The chemotherapy drug "packets", retrieved via the FDA website and other accredited drug information reporting agencies such as the Physician Drug Reference (PDR), are practically the only available unbiased summary of information. One objective is to impartially evaluate the reporting of useful pharmacokinetic parameters, in particular, Volume of Distribution (V(D)) and elimination half-life (t(1/2)), in randomly selected FDA approved chemotherapy drug inserts. The web-accessible portable document format (PDF) files for 30 randomly selected chemotherapy drugs are subjected to detailed search and the two parameters of interest are tabulated. The knowledge of the two parameters is essential in directing patient care as well as for clinical research and since the completeness of the core FDA recommendations has been found deficient, a detailed explanation of the impact of such deficiencies is provided.