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Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins

Sinisi Stefano, Alimguzhin Vadim, Mancini Toni, Tronci Enrico, Mari Federico, Leeners Brigitte

Fundamenta Informaticae

2020

Vol. 174, nr 3/4

283--310

In Silico Clinical Trials (ISCT), i.e. clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine. In this paper we present methods and an algorithm that, by means of extensive computer simulation-based experimental campaigns (ISCT) guided by intelligent search, optimise a pharmacological treatment for an individual patient (precision medicine). We show the effectiveness of our approach on a case study involving a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction in humans.

Network Controllability Analysis of Three Multiple-myeloma Patient Genetic Mutation Datasets

Sanchez Martin Jose Angel, Petre Ion

Fundamenta Informaticae

2020

Vol. 175, nr 1-4

281--299

Network controllability focuses on the concept of driving the dynamical system associated to a directed network of interactions from an arbitrary initial state to an arbitrary final state, through a well-chosen set of input functions applied in a minimal number of so-called input nodes. In earlier studies we and other groups demonstrated the potential of applying this concept in medicine. A directed network of interactions may be built around the main known drivers of the disease being studied, and then analysed to identify combinations of drug targets controlling survivability-essential genes in the network. This paper takes the next step and focuses on patient data. We demonstrate that comprehensive protein-protein interaction networks can be built around patient genetic data, and that network controllability can be used to identify possible personalised drug combinations. We discuss the algorithmic methods that can be used to construct and analyse these networks.

Personalized precision medicine

Konieczny Leszek, Roterman Irena

Bio-Algorithms and Med-Systems

2019

Vol. 15, no. 4

art. no. 20190047

Along with the development of modern science, medical knowledge and therapy become more and more precise and personal as a consequence. Genetics and immunology participate in the progress in particular. They open the way to molecular knowledge, allowing precise interpretation of pathology in individual cases followed by finding proper therapy. However, the large-scale improvement of medical efficacy seems to be achieved with the development of screening tests that, being not invasive and cheap, may allow for personal repeatable use and early revealing of threatening diseases.