bacampicillin and Drug-Related-Side-Effects-and-Adverse-Reactions

Two methods of assessing adverse drug effects-an open-ended question versus a checklist-were compared in a clinical study involving 515 patients being treated with bacampicillin for gonorrhea. Results indicate that adverse reactions are reported more frequently if a checklist is used. However, it was also observed that more serious side effects are usually reported in response to an open-ended question rather than a checklist. Thus it was concluded that the optimal procedure for assessing adverse reactions is to record responses to both an open-ended question and a checklist.

Topics: Ampicillin; Anti-Bacterial Agents; Clinical Trials as Topic; Drug-Related Side Effects and Adverse Reactions; Humans; Surveys and Questionnaires

The FDA's Spontaneous Reporting System (SRS) database contains over 1.5 million adverse drug reaction (ADR) reports for 8620 drugs/biologics that are listed for 1191 Coding Symbols for Thesaurus of Adverse Reaction (COSTAR) terms of adverse effects. We have linked the trade names of the drugs to 1861 generic names and retrieved molecular structures for each chemical to obtain a set of 1515 organic chemicals that are suitable for modeling with commercially available QSAR software packages. ADR report data for 631 of these compounds were extracted and pooled for the first five years that each drug was marketed. Patient exposure was estimated during this period using pharmaceutical shipping units obtained from IMS Health. Significant drug effects were identified using a Reporting Index (RI), where RI = (# ADR reports / # shipping units) x 1,000,000. MCASE/MC4PC software was used to identify the optimal conditions for defining a significant adverse effect finding. Results suggest that a significant effect in our database is characterized by > or = 4 ADR reports and > or = 20,000 shipping units during five years of marketing, and an RI > or = 4.0. Furthermore, for a test chemical to be evaluated as active it must contain a statistically significant molecular structural alert, called a decision alert, in two or more toxicologically related endpoints. We also report the use of a composite module, which pools observations from two or more toxicologically related COSTAR term endpoints to provide signal enhancement for detecting adverse effects.

Topics: Adverse Drug Reaction Reporting Systems; Artificial Intelligence; Computers; Databases, Factual; Drug Prescriptions; Drug-Related Side Effects and Adverse Reactions; Endpoint Determination; Models, Molecular; Quantitative Structure-Activity Relationship; Software; United States; United States Food and Drug Administration