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Kinetic Exponent Network Analysis

Project description

A closer look at complex chemical networks

Europe faces a critical need to re-shore the synthesis of active pharmaceutical ingredients (APIs) to ensure safety and availability of essential medicines. Current industry methods often avoid complex chemical reaction networks (CRNs) due to their intricate behaviour and the effort required to understand them. Innovations in process intensification and continuous flow reactors promise more efficient, scalable, cost-effective production but also involve complex CRNs. With the support of the Marie Skłodowska-Curie Actions programme, the KENA project will develop Kinetic Exponent Network Analysis, a theoretical foundation linking CRN structure to mathematical properties of its experimental kinetic data. This provides a general method to extract CRN structure from experimental kinetic data, enabling optimising chemical conversion and selectivity, enhancing efficient API production in Europe.

Objective

Significant efforts are underway in Europe to re-shore the synthesis of active chemical ingredients (API’s) to ensure the safety and availability of medicine for its citizens. This goes hand in hand with innovations and process intensification. For example, doing multiple chemical reaction steps in one go, and/or by using continuous flow reactors that are more energy and solvent efficient, with a smaller footprint, scalable (by numbering-up), and cheaper to build and maintain. A key issue, however, of doing multiple reactions at once is that different reactants and products can react, thus forming a chemical reaction network (CRN). While CRN’s are ubiquitous in biological systems, they are mostly avoided in industry due to their complex behavior and effort needed to understand and quantify them. In this project, I propose a new method to analyse experimental kinetic data in order to directly determine the structure of the CRN. To this end, I will develop Kinetic Exponent Network Analysis (KENA) to study CRN’s that are of high interest for academia as well as industry. The change in concentration at early times can be described with power laws, from which the network connectivity of species population and thus the CRN structure can be deduced. KENA could then optimize the chemical conversion and selectivity of the desired products in CRN’s, contributing to efficient API re-implementation in Europe.

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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(opens in new window) HORIZON-MSCA-2023-PF-01

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Coordinator

FUNDACION IMDEA NANOCIENCIA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 181 152,96
Address
CALLE FARADAY 9 CIUDAD UNIVERSITARIA DE CANTOBLANCO
28049 Madrid
Spain

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Comunidad de Madrid Comunidad de Madrid Madrid
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