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. 2023 Dec:148:104546.
doi: 10.1016/j.jbi.2023.104546. Epub 2023 Nov 19.

A new computational workflow to guide personalized drug therapy

Simone Pernice  1 , Alessandro Maglione  2 , Dora Tortarolo  3 , Roberta Sirovich  4 , Marinella Clerico  2 , Simona Rolla  5 , Marco Beccuti  1 , Francesca Cordero  1
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Free article

A new computational workflow to guide personalized drug therapy

Simone Pernice et al. J Biomed Inform. 2023 Dec.
Free article

Abstract

Objective: Computational models are at the forefront of the pursuit of personalized medicine thanks to their descriptive and predictive abilities. In the presence of complex and heterogeneous data, patient stratification is a prerequisite for effective precision medicine, since disease development is often driven by individual variability and unpredictable environmental events. Herein, we present GreatNectorworkflow as a valuable tool for (i) the analysis and clustering of patient-derived longitudinal data, and (ii) the simulation of the resulting model of patient-specific disease dynamics.

Methods: GreatNectoris designed by combining an analytic strategy composed of CONNECTOR, a data-driven framework for the inspection of longitudinal data, and an unsupervised methodology to stratify the subjects with GreatMod, a quantitative modeling framework based on the Petri Net formalism and its generalizations.

Results: To illustrate GreatNectorcapabilities, we exploited longitudinal data of four immune cell populations collected from Multiple Sclerosis patients. Our main results report that the T-cell dynamics after alemtuzumab treatment separate non-responders versus responders patients, and the patients in the non-responders group are characterized by an increase of the Th17 concentration around 36 months.

Conclusion: GreatNectoranalysis was able to stratify individual patients into three model meta-patients whose dynamics suggested insight into patient-tailored interventions.

Keywords: Computational models; Longitudinal data; Multiple Sclerosis.

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Conflict of interest statement

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Francesca Cordero reports financial support was provided by Horizon Europe. Marco Beccuti reports financial support was provided by CRT Foundation.

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