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International Conference of the Italian Association for Artificial Intelligence

AIxIA 2021: AIxIA 2021 – Advances in Artificial Intelligence pp 638–654Cite as

A Comparative Study of AI Search Methods for Personalised Cancer Therapy Synthesis in COPASI

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13196))

Abstract

In recent years, optimisation methods in precision medicine have gained much attention thanks to their ability to tackle relevant problems arising from clinical practice effectively. One of the most compelling challenges in this area is designing computational methods for personalising pharmacological treatments, especially for high-impact diseases, due to the large potential impact on the whole healthcare field. In this work, we address the problem of computing safe and effective personalised therapies for Colorectal Cancer (CRC), one of the deadliest forms of tumour for adult humans. We exploit a recent System Biology Markup Language (SBML) mechanistic model of the tumour growth and of the immune response to two drugs and define a simulation-based, non-linear, constrained optimisation problem for automatically synthesising personalised therapies for any given virtual patient. We present a methodology, proposed in our earlier work, that uses a single tool, namely COPASI, to define and solve the optimisation problem. We extend our previous experimental evaluation of the approach by comparing all optimisation algorithms provided by COPASI and performing an in-depth analysis of the results, which provides new and practical insights on the ability of the different algorithms to solve the problem.

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Acknowledgements

This work was partially supported by: Italian Ministry of University and Research under grant “Dipartimenti di eccellenza 2018–2022” of the Department of Computer Science of Sapienza University of Rome. INdAM “GNCS Project 2020”; Sapienza University projects RG11816436BD4F21, RG11916B892E54DB, RP11916B8665242F; Lazio POR FESR projects E84G20000150006, F83G17000830007.

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  1. Computer Science Department, Sapienza University of Rome, via Salaria 113, 00198, Rome, Italy

    Marco Esposito & Leonardo Picchiami

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  1. Marco Esposito
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  2. Leonardo Picchiami
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Correspondence to Marco Esposito .

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Editors and Affiliations

  1. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Stefania Bandini

  2. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Francesca Gasparini

  3. Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genova, Italy

    Viviana Mascardi

  4. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Matteo Palmonari

  5. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Giuseppe Vizzari

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Esposito, M., Picchiami, L. (2022). A Comparative Study of AI Search Methods for Personalised Cancer Therapy Synthesis in COPASI. In: Bandini, S., Gasparini, F., Mascardi, V., Palmonari, M., Vizzari, G. (eds) AIxIA 2021 – Advances in Artificial Intelligence. AIxIA 2021. Lecture Notes in Computer Science(), vol 13196. Springer, Cham. https://doi.org/10.1007/978-3-031-08421-8_44

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