Mario Geysen

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Education

B. Sc. Chemistry, University of Melbourne, Australia.

M. Sc. Science (Chemical engineering), University College London, UK. Dip.

Biochemical Engineering, University College London, UK.

Ph. D. Microbiology, University of Melbourne, Australia

Combinatorial Sciences

 

Principle Research Interests

Combinatorial chemistry is best described as the intersection of many disciplines namely, chemistry, robotics, instrumentation, computer science, and engineering. It focuses on the use of very large numbers, either of the chemical entities themselves or of the number of trials (experiments), carried out in parallel to answer questions faster and more comprehensively than can be achieved by the more conventional sequential experimentation protocols. Another way of looking at combinatorial techniques is to think of a complex problem as a very large search space of all possible solutions, and where experimentation is carried out to generate many of these solutions with an adequate coverage of this space to rapidly determine an acceptable solution to the designated problem. The combinatorial procedure can readily be broken down into a number of well-defined steps, namely:
· Analysis of the problem and the definition of the appropriate search space.
· Design of the experimental protocol for the generation of candidate solutions.
· Use of robotics to carry out the required number of synthetic steps.
· Measurement (assay) of each outcome (compound/protocol) in terms of the problem at hand.
· Analysis of both the positive and negative data obtained, to gain the greatest insight into the properties and or characteristics of successful solutions to the problem.

In recent years combinatorial techniques are being applied to chemistry related endeavors other than to its original application, that of drug discovery. My research interests are centered on the demonstration and development of technologies applicable to any problem with a numerically large solution space.

Drug discovery by synthesis and testing of chemical libraries

The combinatorial sciences group will maintain a state of the art automated synthesis and testing facility allowing the rapid chemical optimization of synthetic procedures, library synthesis, and testing of the resulting chemical entities for biological activity against a panel of biological targets. Procedures for these activities will be based on recently reduced to practice technologies resulting from extensive research and development undertaken by GlaxoSmithKline, one of the worlds largest pharmaceutical companies.

Combinatorial optimization of multi-step solid-phase chemical synthesis

Traditional optimization of chemical procedures is sequential and assumes independence between the steps of a multi-step synthetic procedure. This is clearly achievable by the separation of intermediates away from components, which may interfere in subsequent steps of the synthesis. Solid-phase synthesis on the other hand precludes any separation of the products accumulated on the solid-phase throughout the synthesis procedure. This presents a very different challenge to the chemist, particularly for synthesis requiring a larger number of individual steps. Optimization in this context requires 'choosing' a synthetic sequence from the combinatorial derived number of possible combinations of carrying out each individual step. This initially appears to represent a largely intractable problem however, using analytical constructs technology we at GlaxoSmithKline have been able to analyze the outcome of > 50,000 synthetic trials of a single chemical procedure in a matter of weeks.

Discovery of novel chemistries and/or synthetic procedures

Limitations in high throughput chemical analysis preclude the systematic exploration of all possible reactions/conversions of functional groups under all possible reaction conditions. The same technology described above also lends itself to a 'Monty Carlo' type exploration of chemical reaction space for novel reaction outcomes or of novel chemical strategies for known chemical outcomes. One of the benefits of this combinatorial approach to chemical synthesis is that each experiment provides not only a comprehensive assessment of the use of different solvents, reagents, and reaction conditions, but also data which enumerates important mechanistic effects on the reaction itself.

Combinatorial discovery of catalysts and substrate SAR

Recently, combinatorial techniques have been applied to the discovery of novel catalysts for carrying out chemical transformations. These techniques have been largely uni-directional i.e., either a library of candidate catalysts is evaluated sequentially against a small set of substrates or, a library of candidate substrates is evaluated against a small set of potential catalysts. A recent theoretical proposal addresses this limitation and suggests a practical method which should allow the evaluation in a single step of the combinatorial outcomes from contacting a library of catalysts with a library of substrates.

Generation of important databases and enumeration of rules for complex processes

At a time where scientists increasingly rely on computers to 'virtually' evaluate experimental possibilities as a precursor to designing experiments, it is often the case that the 'rules' underpinning the algorithms used are themselves not well validated by experimental data. As a general statement, the larger the database from which the rules are derived, the better and more broadly applicable the rules themselves. At present there exists many opportunities, using high throughput, automated technologies, to systematically carry out and enumerate large numbers of experimental outcomes designed to comprehensively explore complex relationships. The resulting database then in turn can be analyzed for the governing rules and relationships that apply to the applicable problem, thereby providing better algorithms for use by the scientific community.

 

   
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The Geysen Lab at the University of Virginia

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