An in silico clinical trial platform based on systems biology approaches

Jorba Argemí, Guillem

An in silico clinical trial platform based on systems biology approaches

Document Type

Doctoral thesis
Published Version

Author

Jorba Argemí, Guillem

Director

Oliva Miguel, Baldomero
Manuel Mas, Jose

Publication Date

2023-04-13

Pages

246 p.

License

Citation

Jorba Argemí, G. An in silico clinical trial platform based on systems biology approaches. Universitat Pompeu Fabra; 2023. handle: http://hdl.handle.net/10803/688163

This citation was generated automatically.

Doctoral program

Programa de doctorat en Biomedicina

Abstract

El procés de descobriment i desenvolupament de fàrmacs (DDD) és costós tant econòmic com temporalment, i el qual resulta en nivells d'èxit molt reduïts. Una gran quantitat de compostos son analitzats i molts descartats en cada estadi mentre que, ja en fases d'assaigs clínics, només un 10% d'aquests acaben aprovats per les agències reguladores. Tot i que existeix un gran ventall d’eines bioinformàtiques per les fases inicials del DDD, poques opcions estan disponibles en fases posteriors, on s’hi inverteix una gran quantitat de temps i diners. Aquest fet és bàsicament degut a la complexitat existent en la parametrització d’assaigs clínics, on hi intervenen humans i fàrmacs, i on múltiples eines s’haurien de fusionar per simular la realitat. En aquesta tesi, descric una nova metodologia per realitzar assaigs clínics in silico (ISCTs), basats en biologia de sistemes, amb l’objectiu d'assistir en el procés de desenvolupament de fàrmacs. Aquesta eina usa pacients virtuals, pel que ajudarà també a moure’s cap a una medicina personalitzada o individualitzada.
Drug discovery and development (DDD) is a time consuming and expensive process with low rates of success. A big amount of drug candidates are tested and discarded in each phase and, in clinical trial phases, only about 10% of those are finally approved by regulatory agencies. While many bioinformatic tools are available at early stages of DDD, few options have been approved for posterior phases, where most investment and time is required. This is mainly because of the complexity inherent in clinical trials setting, where human cohorts are being tested with a drug, meaning that multiple tools must be merged in order to fully match reality, or have enough predictability. In this thesis, I describe a novel methodology to undergo in silico Clinial Trials (ISCTs), based on a Systems Biology approach, with the aim of assisting drug development process. It uses virtual patient populations, which will also help shifting towards individualized, personalized medicine.

Keywords

assaig clínic in silico, farmacologia de sistemes quantitativa, biologia de sistemes, pacients virtuals, in silico Clinical Trial (ISCT), quantitative systems pharmacology (QSP), systems biology, virtual patients (VPs)