Toxicity expert systems

There are software that use more approaches for the prediction of toxicity expert systems, QSAR, and read-across (http //www.insilico.eu/use-qsar.html). 

The earliest practical use of an expert system was made in the software named MYCIN for diagnosing a toxic poison from the symptoms of a patient and recommending the antidote (62). This type of activity is generally carried out by a human expert who processes information about a situation (in this case, symptoms of a patient), refers to the expert s experience and expert knowledge, and then recommends action (in this case, the antidote). 

As computing capabiUty has improved, the need for automated methods of determining connectivity indexes, as well as group compositions and other stmctural parameters, for existing databases of chemical species has increased in importance. New naming techniques, such as SMILES, have been proposed which can be easily translated to these indexes and parameters by computer algorithms. Discussions of the more recent work in this area are available (281,282). SMILES has been used to input Contaminant stmctures into an expert system for aquatic toxicity prediction by generating LSER parameter values (243,258). 

A number of commercial expert systems have been applied to screen drug libraries. For instance, DEREK, TOPKAT, MultiCASE, and many other systems all have possibilities in this regard. However, it should be noted that for broad screening only compounds with toxicity associated with them can be identified, and hence these are very crude measures of hazard assessment. The use of expert systems to screen libraries is fraught with dangers, not least that no performance statistics are available for these systems being used for such an application. It is also highly probable that the vast majority of predic-... 

A large variety of techniques are available to develop predictive models for toxicity. These range from relatively simple techniques to relate quantitative levels of potency with one or more descriptors to more multivariate techniques and ultimately the so-called expert systems that lead the user directly from an input of structure to a prediction. These are outlined briefly below. 

The need for rapidly accessible estimation of toxicity has led to the development of software and other algorithms that will generate estimations of toxicity, usually for organic compounds [79] such methodology is termed an expert system, which has been defined [34] as any formalised system, not necessarily computer-based, which enables a user to obtain rational predictions about the toxicity of chemicals. Essentially, expert systems fall into two classes— those relying on statistical approaches and those based on explicit rules derived from human knowledge. 

A Russian expert system, PASS (prediction of activity spectra for substances) [84], uses substructural descriptors called multilevel neighborhoods of atoms [85] to predict over 900 different pharmacological activities from molecular structure. These activities include a number of toxicity end points such as carcinogenicity, mutagenicity, teratogenicity, and embryotoxicity. The accuracy of prediction has been shown [86] to range from about 85% to over 90%. One-off predictions can be obtained free of charge on the PASS website [84]. 

Dearden JC, Barratt MD, Benigni R, Bristol DW, Combes RD, Cronin MTD et al. The development and validation of expert systems for predicting toxicity. ATE A 1997 25 223-52. 

Greene N, Judson PN, Langowski JJ, Marchant CA. Knowledge-based expert systems for toxicity and metabolism prediction DEREK, StAR and METEOR. SAR QSAR Environ Res 1999 10 299-314. 

Smithing MP, Darvas F. Hazardexpert an expert system for predicting chemical toxicity. In Finlay JW, Robinson SF, Armstrong DJ, editors, Food safety assessment. Washington DC American Chemical Society, 1992. p. 191-200. 

Guidelines for Safe Storage and Handling of High Toxic Hazard Materials Guidelines for Use of Vapor Cloud Dispersion Models Understanding Atmospheric Dispersion of Accidental Releases Expert Systems in Process Safety... 

Expert Systems attempt to formalize the knowledge of human experts, who assess the toxicity of a new compound, in a computer program [11],... 

Hewitt M, Ellison CM, Enoch SJ, Madden JC, Cronin MTD (2010) Integrating (Q)SAR models, expert systems and read-across approaches for the prediction of developmental toxicity. Reprod Toxicol 30(1) 147-160... 

Scott DR (1995) Empirical pattern recognition/expert system approach for classification and identification of toxic organic compounds from low resolution mass spectra. In Chemometrics in environmental chemistry - applications. Vol 2, part H (Vol ed J Einax), Springer, Berlin Heidelberg New York, p 25... 

DEREK Expert system for the prediction of toxicity (genotoxicity, carcinogenicity, skin sensitization, etc.)... 

A well-established specialized expert system with which the proposed expert system could be compared is the digitalis advisor of Szolovitz and Long Q ) which represents a well-understood clinical situation. It performs clinical functions beyond the scope of this proposed system, but it does do some things, like maintaining the blood level of the drug involved, and monitoring its toxicity, that this proposed system is concerned with and should perform adequately. 

A number of approaches are available or under development to predict metabolism, including expert systems such as MetabolExpert (Compudrug), Meteor (Lhasa), MetaFore [42] and the databases Metabolite (MDL) and Metabolism (Synopsys) [43]. Ultimately such programs may be linked to computer-aided toxicity prediction based on quantitative structure-toxicity relationships and expert systems for toxicity evaluation such as DEREK (Lhasa) (see also Chapter 8) [44]. 

An example of another approach is DEREK, a pnblicly available expert system designed to assist chemists and toxicologists in predicting toxicological hazards based on analysis of chemical strnctnre (see table 9.1). DEREK differs from other compnter methods for toxicity prediction in that it makes qnalitative rather than qnantitative predictions and does not rely on algebraic or statistical relationships. 

Chapter 19 The Use by Governmental Regulatory Agencies of Quantitative Structure-Activity Relationships and Expert Systems to Predict Toxicity Mark T.D. Cronin... 

In other areas of predictive toxicology and fate, progress has been steady, and spurred on in recent years by many of the legislative and commercial pressures mentioned in Table 1.1. Progress and interest in the prediction of human effects and pharmacokinetics has been complemented by advances in chemo-informatics. This has resulted in a large number of commercially available expert system approaches to toxicity prediction (see Chapter 9) and algorithms for the prediction of absorption, distribution, metabolism, and excretion (ADME see Chapters 10 and 11). 

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