The kidneys, heart and lungs are vital organ systems evaluated as part of acute or chronic toxicity assessments. New methodologies are being developed to predict these adverse effects based on in vitro and in silico approaches. This paper reviews the current state of the art in predicting these organ toxicities. It outlines the biological basis, processes and endpoints for kidney toxicity, pulmonary toxicity, respiratory irritation and sensitization as well as functional and structural cardiac toxicities. The review also covers current experimental approaches, including off-target panels from secondary pharmacology batteries. Current in silico approaches for prediction of these effects and mechanisms are described as well as obstacles to the use of in silico methods. Ultimately, a commonly accepted protocol for performing such assessment would be a valuable resource to expand the use of such approaches across different regulatory and industrial applications. However, a number of factors impede their widespread deployment including a lack of a comprehensive mechanistic understanding, limited in vitro testing approaches and limited in vivo databases suitable for modeling, a limited understanding of how to incorporate absorption, distribution, metabolism, and excretion (ADME) considerations into the overall process, a lack of in silico models designed to predict a safe dose and an accepted framework for organizing the key characteristics of these organ toxicants.

Hepatotoxicity is one of the most frequently observed adverse effects resulting from exposure to a xenobiotic. For example, in pharmaceutical research and development it is one of the major reasons for drug withdrawals, clinical failures, and discontinuation of drug candidates. The development of faster and cheaper methods to assess hepatotoxicity that are both more sustainable and more informative is critically needed. The biological mechanisms and processes underpinning hepatotoxicity are summarized and experimental approaches to support the prediction of hepatotoxicity are described, including toxicokinetic considerations. The paper describes the increasingly important role of in silico approaches and highlights challenges to the adoption of these methods including the lack of a commonly agreed upon protocol for performing such an assessment and the need for in silico solutions that take dose into consideration. A proposed framework for the integration of in silico and experimental information is provided along with a case study describing how computational methods have been used to successfully respond to a regulatory question concerning non-genotoxic impurities in chemically synthesized pharmaceuticals.

Despite wide spread vaccination, the public health burden of pertussis remains substantial. Current acellular pertussis vaccines comprise upto five Bordetella pertussis (Bp) antigens. Performing an ELISA to quantify antibody for each antigen is laborious and challenging to apply to pediatric samples where serum volume may be limited. We developed a microsphere based multiplex antibody capture assay (MMACA) to quantify antibodies to five pertussis antigens; pertussis toxin, pertactin, filamentous hemagglutinin and fimbrial antigens 2/3, and adenylate cyclase toxin in a single reaction (5-plex) with a calibrated reference standard, QC reagents and SAS((R)) based data analysis program. The goodness of fit (R(2)) of the standard curves for five analytes was >/=0.99, LLOQ 0.04-0.15 IU or AU/mL, accuracy 1.9%-23.8% (%E), dilutional linearity slopes 0.93-1.02 and regression coefficients r(2)=0.91-0.99. MMACA had acceptable precision within a median CV of 16.0%-22.8%. Critical reagents, antigen conjugated microsphere and reporter antibody exhibited acceptable (<12.3%) lot-lot variation. MMACA can be completed in <3h, requires low serum volume (5muL/multiplex assay) and has fast data turnaround time (<1min). MMACA has been successfully developed and validated as a sensitive, specific, robust and rugged method suitable for simultaneous quantification of anti-Bp antibodies in serum, plasma and DBS.

To improve surge testing capability for a response to a release of Bacillus anthracis, the CDC anti-Protective Antigen (PA) IgG Enzyme-Linked Immunosorbent Assay (ELISA) was re-designed into a high throughput screening format. The following assay performance parameters were evaluated: goodness of fit (measured as the mean reference standard r2), accuracy (measured as percent error), precision (measured as coefficient of variance (CV)), lower limit of detection (LLOD), lower limit of quantification (LLOQ), dilutional linearity, diagnostic sensitivity (DSN) and diagnostic specificity (DSP). The paired sets of data for each sample were evaluated by Concordance Correlation Coefficient (CCC) analysis. The goodness of fit was 0.999; percent error between the expected and observed concentration for each sample ranged from -4.6% to 14.4%. The coefficient of variance ranged from 9.0% to 21.2%. The assay LLOQ was 2.6 mug/mL. The regression analysis results for dilutional linearity data were r2 = 0.952, slope = 1.02 and intercept = -0.03. CCC between assays was 0.974 for the median concentration of serum samples. The accuracy and precision components of CCC were 0.997 and 0.977, respectively. This high throughput screening assay is precise, accurate, sensitive and specific. Anti-PA IgG concentrations determined using two different assays proved high levels of agreement. The method will improve surge testing capability 18-fold from 4 to 72 sera per assay plate.