SubscribeRational Design and QSPR
Avantium has embraced Rational Design for the efficient screening of large libraries of reagents, solvents and catalysts. This cost-effective approach combines the advantages of molecular modeling, statistical design of experiments and multivariate statistics.
The development of QSPRs (Quantitative Structure-Property Relationships) is core to the Rational Design methodology. The underlying assumption in QSPR is that it is possible to predict the properties or performance of compounds by knowing their molecular structures.
Candidate molecules are first characterized by molecular 'descriptors' that quantify their physio-chemical properties. These descriptors are subsequently analyzed using statistical techniques to facilitate the systematic exploration of the available chemical diversity and select an optimal subset of compounds for testing.
Once experimental response data has been obtained (e.g. rate, yield or enantio-selectivity), a QSPR model can be generated to relate differences in the molecular descriptors to differences in the responses. Such a model can subsequently be used to predict the performance of compounds that have not been tested.
This approach allows large libraries of reagents, solvents and catalysts to be virtually screened, while only those molecules that are predicted to perform well need to be synthesized and tested.
Avantium has successfully applied Rational Design and QSPR techniques to:
- Enantiomeric excess and rate prediction in asymmetric catalytic reactions
- E-value and rate prediction for biocatalysts
- Formulation additive optimization
- Physical property and solubility prediction
- and a variety of other applications ...
Avantium is keen to discuss the use of Rational Design and QSPR for the optimization of any product or process or the possibility of integrating our modeling expertise with the High-throughput Experimentation capabilities of our customers.
Kinetic Modelling
Rapid parallel testing in continuous operation allows the simultaneous exploration of catalyst and process variables. The data from batch experiments and continuous flow experiments can be used to develop kinetic models and response surface models to describe the catalyst performance on the basis of mechanistic and empirical models, respectively, as a function of process conditions.
While conventionally kinetic modeling is regarded as a method to optimize process operation, when applied as part of a catalyst development program, kinetic modeling provides insight in the reaction mechanism in relation to the catalyst composition and can be a useful means to direct the scope of the program.
A typical kinetic program at Avantium entails the study of a mechanism by use of different feed compositions (concentrations and components) and space velocities and study of internal and external mass transfer effects.
Avantium offers experience in kinetic model development for batch processes and continuous processes. For fixed bed testing Avantium has developed a kinetic fitting tool Flowkin that utilizes the data from the Nanoflow equipment to derive complete mechanistic models.
Flowkin provides correlations that allow flexible reaction model definition (including adsorption type reactions), account for non-equimolar gas phase reactions (e.g. expanding reactions) and sequential automated fitting of various mechanisms with initial guess variations.
The ideality of the Nanoflow systems (isothermal conditions, plug flow conditions, limited pressure drop, ability to test small particles) allows the derivation of intrinsic kinetics of catalysts. However, observed kinetics that include particle size effects can also be derived on the basis of measurements with extruded particles.
Avantium can also utilize parallel testing and kinetic fitting to efficiently and rapidly derive the most likely mechanism of catalyst deactivation, which can form the basis for the development of accelerated deactivation test procedures.