CPSA Digest 2001

Proceedings -Tuesday, October 9, 2001

TuOA

Of Mice and Magnets:
Metabonomic Technology as a Tool for Rapid-Throughput Toxicity Evaluation

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Background:
The number of discovery compounds identified from high throughput screening as potential leads is rapidly increasing and these compounds proceed forward in the development cycle to ADME and toxicity screening. The toxicity tests in common use are feared to become the rate-limiting step in this lead evaluation process, as they are not high throughput. Metabonomics is a technology that explores the potential of combining 'state of the art' high-resolution NMR spectroscopy with multivariate statistical techniques. Recent advances in flow-through NMR hardware and pattern recognition software have made the possibility of "high throughput" in vivo toxicity assessment a practical possibility. Metabonomics technology was pioneered by Jeremy Nicholson, Elaine Holmes and John Lindon of Imperial College of Science, Technology and Medicine in London.

Premise:
The use of metabonomics for toxicity testing involves the elucidation of changes in metabolic patterns associated with drug toxicity based on the measurement of component profiles in biofluids (i.e. urine). NMR pattern recognition technology associates target organ toxicity with NMR spectral patterns and identifies novel surrogate markers of toxicity.

Understanding the significance of perturbed patterns of metabolites in biological systems may give insights into the mechanisms of drug toxicity. NMR spectroscopy of biofluids and cells provides a unique window on changes in endogenous metabolism caused by drugs and toxins. NMR gives information on organ and cell type-specific damage and identifies novel markers of toxicity. However, biological NMR spectra are extremely complex and much information can be lost even in rigorous statistical analysis of quantitative data as the essential diagnostic parameters are carried in the overall patterns of the spectra. Therefore, computer pattern recognition methods are used, such as non-linear mapping and artificial neural networks, to interrogate the vast metabolic databases on toxicological events generated by conventional biochemical and proton NMR spectroscopic methods. This approach allows a mathematical classification of toxicity based on a compression of disparate types of multidimensional metabolic data. New insights thus result into the modes and biochemical mechanisms of toxicity.

Value of the Technology
The advantages of metabonomics for pharmaceutical research and development include:

• Potential to obtain information on target organ identification, severity, onset, duration and reversal
• Potential for identifying novel biomarkers
• Non-invasive
• No a priori decisions about samples need be made
• No sample preparation necessary other than cold collection and dilution in deuterated buffer
• Complete time course data can readily be obtained
• Minimizes compound requirements
• Relatively fast analysis (200-300 samples/day)

Analysis
The sample collection and analysis procedure is as follows. Urine samples from rats, for example, are collected in a refrigerated compartment of a metabolism cage and preserved with sodium azide. The samples are placed onto a Biomek(R) robot (Beckman Coulter, Fullerton, CA) and aliquots are removed and placed into microplate wells. Deuterated buffer and (2,2',3,3'-deuterotrimethylsilylprprionic acid (TSP-a chemical shift reference standard) are added to wells and samples are frozen until analysis. When analyzed, a Gilson 215 autosampler injects samples onto a Varian Inova 600 shielded magnet NMR equipped with a 120 mL flow probe. Multivariate statistical analysis techniques are applied to the spectra obtained. Principal component analysis reduces spectra to a single point in multidimensional metabolic space. Principal component plots are generated.

NMR spectra have been shown to be reproducible from day to day and also from animal to animal. The technique can be used to determine vehicle effects, as well as drug toxicity effects. For example, NMR spectra of urine from rats dosed with corn oil and saline vehicles can be differentiated from urine of untreated rats. It is claimed that NMR data can be more consistent that histopathology data because temporal variation can be accounted for. Mouse urine can be used, as well as rat urine, and as little as 0.3 mL collected from a mouse can be useful to generate NMR spectra.

An application to the condition vasculitis was presented. Histopathology is presently the only way to diagnose vasculitis; a vessel is cut open and lesions are sought. A toxicity endpoint of a phosphodiesterase inhibitor under development is vasculitis; lesions were seen in 8 of 32 animals. By looking at the NMR spectra for these animals' urine, and subjecting the spectra to principal component analysis, the results became clearer that mild and severe lesions occurred and could be identified before histopathology.

Future
There are many remaining issues to be resolved before widespread utilization of this technology to rapid toxicity testing. Some of these issues include defining toxicity (What is an effect?), target organ predictability, biomarker identification and informatics. Future directions of the technology involve the following:

• Develop comprehensive metabonomic database
• COMET Consortium (3-Year project involving six pharmaceutical companies with oversight by Imperial College)
• Expand metabonomics applications to other species
• Evaluate crypoprobe technology for increased sensitivity or increased throughput
• Expand technology to novel targets: cardiac toxicity and adrenal toxicity
• "Grand Unification" of Genomic/Proteomic and Metabonomic technologies.

The objectives of the COMET Consortium are to generate a comprehensive database of NMR spectra of rat urine after treatment with various toxicants. Year 1 of the 3-year project looks at liver and kidney toxicants (60 compounds in the rat, 12 in mouse). Subsequent year targets are to be determined. The generation of predictive chemometric models is another goal of the consortium. The first priority is to generate predictive screening methodologies and second priority is to develop novel biomarkers and methods for identifying them. The six pharmaceutical companies involved in the COMET Consortium are Eli Lilly, DuPont Pharmaceuticals, Novo Nordis A/S, Pharmacia, Pfizer and Hoffman LaRoche.

Links
Imperial College of Science, Technology and Medicine
Exhibition Road, London SW7 2AZ Tel: +44 (0)20 7589 5111
E-mail: info@ic.ac.uk

Metabometrix Ltd is a development-stage company with a proprietary platform of metabonomics technology for generating, classifying and interpreting metabolic information obtained from biological fluids and tissues using NMR spectroscopy and advanced chemometric methodologies. Professor Jeremy Nicholson is Chief Scientist of Metabometrix Ltd.

Gene Logic Inc. (Gaithersburg, MD) has announced that it has invested in, and initiated research collaboration with, Metabometrix Ltd. as part of its ongoing efforts to accelerate the growth of the content component of its biological information products.

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