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Drug-induced phospholipidosis (PL) is a condition characterized by the accumulation of phospholipids and drug in lysosomes, and is found in a variety of tissue types. PL is frequently manifested in preclinical studies and may delay or prevent the development of pharmaceuticals. This report describes the construction of a database of PL findings in a variety of animal species and its use as a training data set for computational toxicology software. PL data and chemical structures were compiled from the published literature, existing pharmaceutical databases, and Food and Drug Administration (FDA) internal reports yielding a total of 583 compounds suitable for modeling. The database contained 190 (33%) positive drugs and 393 (77%) negative drugs, of which 39 were electron microscopy-confirmed negative compounds and 354 were classified as negatives due to the absence of positive reported data. Of the 190 positive findings, 76 were electron microscopy confirmed and 114 were considered positive based on other evidence. Quantitative structure-activity relationship (QSAR) models were constructed using two commercially available software programs, MC4PC and MDL-QSAR, and internal cross-validation (10 × 10%) experiments were performed to assess their predictive performance. Performance parameters for the MC4PC model were specificity 92%, sensitivity 50%, concordance 78%, positive predictivity 76%, and negative predictivity 78%. For MDL-QSAR, predictive performance was similar: specificity 80%, sensitivity 76%, concordance 79%, positive predictivity 65%, and negative predictivity 87%. By combining the output of the two QSAR programs, the overall predictive performance was vastly improved and sensitivity could be optimized to 81% without significant loss of specificity (79%). Many of the structural alerts and significant molecular descriptors obtained from the QSAR software were found to be associated with parts of active molecules known for their cationic amphiphilic drug (CAD) properties supporting the hypothesis that the endpoint of PL is statistically correlated with chemical structure. QSAR models can be useful tools for screening drug candidate molecules for potential PL. [ABSTRACT FROM AUTHOR]

An anonymous survey of pharmaceutical industry practices for immunotoxicology evaluation was conducted. This was in support of the development of the guideline on the preclinical evaluation of unintended modulation of the immune system for the International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use. The survey was conducted in two phases in 2003 and 2004. A total of 64 responses were received of which 45 were included in the formal evaluation. The remaining compounds were excluded because they were cytotoxic anti-neoplastic drugs (N = 7), or due to insufficient information (N = 12). The purpose of the survey was to gather data on the correlation between routine toxicology studies (RTS) and additional immunotoxicological studies (AIS). The results of the survey were evaluated by the Expert Working Group (EWG) and classified as to positive or negative findings in RTS and AIS. The results of the survey showed that for 27 of 45 compounds (60%), the RTS and AIS endpoints were in agreement. In 12 of 45 cases (27%), the RTS endpoints showed immune modulation not observed in the AIS assays. Finally for 6 of 45 drugs (13%) a response was seen with the AIS methods where no significant effect was observed in the RTS endpoints. Length of dosing and the number of tests evaluated were similar in all groups. The groups where RTS detected signs of immunosuppression were more likely to have been dosed at or above MTD. This data contributed to the consensus in the EWG that routine immune function testing as an initial screen for all new drugs is not required. Instead, a weight-of-evidence approach including RTS and other causes for concern is recommended to identify the need for additional immunotoxicity studies. [ABSTRACT FROM AUTHOR]

Hypersensitivity reactions to systemically administered drugs cannot be predicted using available preclinical models. This research is a collaborative project to evaluate the ability of the Lymph Node Proliferation Assay (LNPA) to predict systemic hypersensitivity caused by pharmaceuticals. The assay design is a modification of the Local Lymph Node Assay with the major modification being injection of the test substance subcutaneously to achieve a known systemic exposure to the drug. Fourteen compounds were evaluated in the LNPA. These were two clinically negative drugs (Metformin, phenobarbital), an assay positive control (streptozotocin), eight human hypersensitivity positive drugs (sulfamethoxazole, procainamide, clonidine, ofloxacin, nevirapine, abacavir, lamotrigine, zomepirac), and 3 investigational drugs (CM40874, CM40954 and CM40420), one of which caused hypersensitivity in primates. Hypersensitivity-positive drugs were classified as such based on at least two of three independent data sources: U.S. FDA postmarketing database, drug labeling information, and clinical trial data. All drugs were tested in multiple laboratories for a total of 2–12 evaluations per compound. The pure drug substance was used for testing if it could be obtained commercially, otherwise the marketed drug formulation was used. Neither of the negative control drugs showed a positive reaction in the test system. Four of the eight hypersensitivity positive drugs showed a mixed or positive reaction. Two of the three investigational compounds gave a positive response. A smaller number of LNPAs were run concurrently using footpad injection and evaluation of the popliteal lymph node and gave generally comparable results. Additional development may increase the reproducibility of the assay and facilitate detection of drugs that require metabolic activation to become allergenic, or drugs for which there is dose-limiting toxicity. The data suggest that this method might be useful as a first-line screen to identify candidate drugs that are more likely to cause a high prevalence of human drug hypersensitivity. [ABSTRACT FROM AUTHOR]