Validity and validation of expert (Q)SAR systems.

At a recent workshop in Setubal (Portugal) principles were drafted to assess the suitability of (quantitative) structure-activity relationships ((Q)SARs) for assessing the hazards and risks of chemicals. In the present study we applied some of the Setubal principles to test the validity of three (Q)SAR expert systems and validate the results. These principles include a mechanistic basis, the availability of a training set and validation. ECOSAR, BIOWIN and DEREK for Windows have a mechanistic or empirical basis. ECOSAR has a training set for each QSAR. For half of the structural fragments the number of chemicals in the training set is >4. Based on structural fragments and log Kow, ECOSAR uses linear regression to predict ecotoxicity. Validating ECOSAR for three 'valid' classes results in predictivity of > or = 64%. BIOWIN uses (non-)linear regressions to predict the probability of biodegradability based on fragments and molecular weight. It has a large training set and predicts non-ready biodegradability well. DEREK for Windows predictions are supported by a mechanistic rationale and literature references. The structural alerts in this program have been developed with a training set of positive and negative toxicity data. However, to support the prediction only a limited number of chemicals in the training set is presented to the user. DEREK for Windows predicts effects by 'if-then' reasoning. The program predicts best for mutagenicity and carcinogenicity. Each structural fragment in ECOSAR and DEREK for Windows needs to be evaluated and validated separately.

External validation of EPIWIN biodegradation models.

The BIOWIN biodegradation models were evaluated for their suitability for regulatory purposes. BIOWIN includes the linear and non-linear BIODEG and MITI models for estimating the probability of rapid aerobic biodegradation and an expert survey model for primary and ultimate biodegradation estimation. Experimental biodegradation data for 110 newly notified substances were compared with the estimations of the different models. The models were applied separately and in combinations to determine which model(s) showed the best performance. The results of this study were compared with the results of other validation studies and other biodegradation models. The BIOWIN models predict not-readily biodegradable substances with high accuracy in contrast to ready biodegradability. In view of the high environmental concern of persistent chemicals and in view of the large number of not-readily biodegradable chemicals compared to the readily ones, a model is preferred that gives a minimum of false positives without a corresponding high percentage false negatives. A combination of the BIOWIN models (BIOWIN2 or BIOWIN6) showed the highest predictive value for not-readily biodegradability. However, the highest score for overall predictivity with lowest percentage false predictions was achieved by applying BIOWIN3 (pass level 2.75) and BIOWIN6.

(Q)SARs: gatekeepers against risk on chemicals?

ECOSAR and DEREKfW predictions for the (eco)toxicological effects of circa 70 substances were compared with experimental data for risk assessment purposes. These and other (quantitative) structure-activity relationships ((Q)SARs) programs will play an important role in future chemical policies, such as in the European Union and The Netherlands, to reduce animal testing and costs and to speed up the number of risk assessments for hazardous chemicals. The two programs, ECOSAR and DEREKfW, were selected because they are easy to use and transparent in their predictions. They predict to which chemical class a substance belongs and also predict some (eco)toxicological properties. ECOSAR categorised 87% of the chemicals correctly in chemical classes. With regard to predicting ecotoxicity, criteria were drawn up for the reliability of the QSARs provided by ECOSAR. Application of these criteria had the result that half of the regression lines from ECOSAR were considered unreliable beforehand. It turned out, however, that the "unreliable" regression lines predicted similar accurately as the "reliable" lines, although much less chemicals were available for validating the "unreliable" QSARs. The overall accurate prediction of toxicity by ECOSAR was 67%. DEREKfW categorised 90% of the chemicals correctly in chemical classes, while 10% of the structural fragments needed a more detailed description. The accuracy of prediction was around 60% for sensitisation, 75% for genotoxicity and carcinogenicity for a limited number of chemicals. Irritation and reproductive toxicity were predicted poorly. Finally, it should be stressed that regulators and industries need to agree on the acceptability criteria relating to false negative and false positive (Q)SAR predictions. This to prevent unnecessary animal testing when regulators do not sufficiently rely on (Q)SAR predictions or to prevent too much faith in (Q)SAR predictions which will then may cause an insufficient protection of man and the environment. Therefore, if the regulatory trend is that (Q)SARs have to be applied more and more systematically in the risk assessment process, their validity and the available tools have to be explored further.

Environmental risk limits for two phthalates, with special emphasis on endocrine disruptive properties.

Environmental risk limits (ERLs) are derived for di-n-butyl phthalate (DBP) and di(2-ethylhexyl) phthalate (DEHP). The ERLs are derived using data on (eco)toxicology and environmental chemistry. Endpoints used are survival, growth, and reproduction. The resulting ERLs in water are 10 and 0.19 microg/L for DBP and DEHP, respectively; in fresh soil and sediment with 10% organic matter the derived ERLs are respectively 0.7 and 1 mg/kg fresh wt. In The Netherlands, measured concentrations of DBP are seldom above the ERLs, while reported concentrations for DEHP are 3 to 20 times higher than the ERL. As phthalates as a group are commonly mentioned as chemicals with possible endocrine disruptive effects, in vivo and in vitro tests for a series of phthalates with endpoints related to endocrine disruption are reviewed. In vitro and in vivo tests give a similar distinction between phthalates that can or cannot act as endocrine disrupters. The significance of these tests for the derivation of ERLs is discussed. It is concluded that the ERLs derived will give sufficient protection against endocrine disruptive effects. There is no need to include additional data for DBP and DEHP, related to endpoints other than survival, growth, or reproduction, in the derivation of ERLs.

Distribution of aluminum phthalocyanine disulfonate in an oral squamous cell carcinoma model. In vivo fluorescence imaging compared with ex vivo analytical methods.

Photosensitizer-induced fluorescence is studied as a technique for the detection of cancer. Therefore we investigated the ability of a photosensitizer, aluminum phthalocyanine disulfonate (AIPcS2), to localize in tumor tissue. In vivo endoscopic fluorescence imaging, fluorescence microscopy, conventional spectrofluorometry and high performance liquid chromatograpy combined with diode laser-induced fluorescence (HPLC-Dio-LIF) were used. Squamous cell carcinomas were induced with 4-nitro-quinoline-1-oxide (4NQO) in the mucosa of the palate of the rat. In vivo fluorescence images, taken after injection of 1.5 mumol/kg AIPcS2 intravenously, showed that 4NQO-treated palates had higher fluorescence signals than normal palates. Areas displaying locally high amounts of AIPcS2 fluorescence (hot spots) were present only in 4NQO-treated rats 2-8 h but had disappeared 24 h after injection. However, HPLC-Dio-LIF showed that the relative AIPcS2 content was highest at 24/48 h in biopsies taken in the areas of the hot spots. Fluorescence microscopy revealed that AIPcS2 was present only between 2 and 8 h in the epithelial layer, while in biopsies the connective tissue contained large quantities of AIPcS2 at 24/48 h. In vivo fluorescence imaging appears to show mainly fluorescence from the epithelial layer and the ex vivo analytical techniques mainly show the connective tissue fluorescence. Care should be taken when interpreting data using one technique only.