The challenge

The challenge, objective of the project, was to activate a new method of collaboration between the world of research and innovation, with a view to Open Innovation and sharing of knowledge, through the systemisation of the various regional market players operating in the field of oncology, in order to favor an innovative process of better quality for the health system.

To achieve this, the aim was to create a regional trial hub for the early identification of tumors, characterization of the resistance profile and the creation of alternative therapies for patients who do not respond to conventional therapies.

Three technological trajectories identified by the research project presented:

1. Development of innovative personalized therapeutic approaches for the prophylaxis and / or treatment of oncological diseases;
2. Development of non-invasive approaches for the assessment of risk factors through environmental sensors;
3. Development of digital solutions for fast and accurate diagnostics.

Technology transfer processes require proactivity and collaboration between all the actors involved: researchers, research centers, industrial partners and other key stakeholders. This central aspect requires structured skills and an integrated approach, for this reason we wanted to establish a multidisciplinary network that includes both the main Campania centers of excellence in the field of life science, and the skills necessary for the realization of the project. and for the activation of technology transfer processes.

The main activities that the platform set out to carry out were:

• identification of metabolic biomarkers associated with a specific type of drug-resistant tumor and identification of the related biochemical pathways in order to highlight new potential pharmacological targets;  
• development of early and preventive diagnostic methods based on metabolomics studies aimed at the creation of biosensors and diagnostic kits. This activity will be integrated and supported by data relating to the clustering of tumors carried out through anatomopathological, clinical and genetic analyzes of the samples from patients affected by the tumor pathologies of interest;
• remote monitoring of patients affected by the oncological pathologies of interest, in order to make the collection of diagnostic and environmental information more effective and meaningful, while improving the quality of life and significantly reducing hospitalization costs;
• development of early and preventive diagnostic methods using, on a large scale, biological samples in order to be able to evaluate the possible etiopathogenetic action towards the oncological pathology of environmental and food pollutants;
• development of digital solutions to favor the reproducibility of the information and information content present within the biological samples collected and the diagnostic data acquired.

In this scenario, ICT technologies could constitute a very powerful integration tool, capable of favoring not only the collection and analysis of diagnostic-health data, but also that of promoting social relations, the exchange of experiences and the consequent possibilities. enrichment in terms of the ability to create new knowledge on an inferential basis from such interactions. Connections between patients, study groups, participants in special programs and trials were also considered vital for this purpose. Social media were also considered because they are able to play an essential role in this integration logic to establish good connections between peers in the context of homogeneous patient groups from the point of view of collected data, pathology and therapy.

The entire life cycle that was to characterize the initiative therefore passed through the constant analysis of the state of the cancer patient and the surrounding environment or of patients at risk due to familiarity or territoriality, as well as for the definition of monitoring paths and protocols and possible treatment plans, through the constant collection of clinical and non-clinical parameters, the elaboration of these parameters and the intervention in case of sentinel events. The collection of the patient’s diagnostic data must be carried out, as much as possible, by remote monitoring, with the use of wireless devices (sensors) selected according to the different medical needs (e.g. sphygmomanometer, thermometer, holter, blood analysis) or environmental control (e.g. sensors for detecting air and water quality, presence of toxic gases,radioactivity etc.) connected to a collection service center through modern technologies for mobile internetworking (WiFi, 3G, LTE). From the Service Center, such data can be automatically transmitted to the analysis and study groups for their monitoring and interpretation. This can take place through an interface where the doctors and scholars concerned can view the data of each patient, create diagnostic hypotheses and correlations between risk factors, establishing the frequency of sample collection campaigns, and identifying times and methods for any therapeutic actions and drug administration. With the intention of not depersonalizing the process of studying and collecting information and diagnostic evidence,the scholars of the Service Center will be able to communicate in case of need with the users involved in the campaigns. Each communication will allow the data collected to be updated and further information useful for clinical evaluation to be transferred.

All the previous actions, assisted by health personnel, are accompanied by the automatic retrieval of statistical information regarding the elements collected, as well as the effectiveness of any actions carried out in the context of the campaigns. All the data collected will contribute to an “automated” evaluation process of the patient’s health status and can trigger alarms (sentinel events) which are taken over and managed by the service center. The service center will then be able to classify the alerts and make the most appropriate analysis involving the organization in charge of patient care.

The large amount of data (definable as HealthCare Big Data) collected from all patients, will represent an opportunity to create a space for the exchange of information, discoveries, therapeutic interpretations starting from technologies and tools of big data analytics, which will become essential tools for:

• carry out predictive analyzes, applying models that can lead to a better understanding of patients’ needs;
• improve the quality of treatments;
• educate and encourage the adoption of healthier lifestyles;
• identify environmental and / or family risk factors;
• ensure better cooperation between patients, professionals, companies and investors in HealthCare.

This process of technological evolution will accompany doctors in their daily work by reducing the costs of seeking information, training and updating, increasing the dissemination of knowledge available to health professionals who implement therapies and treatments, improving the effectiveness of the same for the benefit. of public health on the regional territory. In fact, the massive archiving of clinical histories, of data relating to diagnoses, for the use of communities of doctors who share their personal daily contributions could help to refine the diagnosis process, which in any case would continue to be completed by a single professional to whom the patient relies, but with the help of virtual teams of which the single professional can be part.

The realization of the identified technological paradigm will have a twofold objective: on the one hand, the complex of industrial research, experimental development and innovation actions will be aimed at enhancing the results of the basic research carried out by the project partners, on the other hand processes of enhancement of research aimed at activating technology transfer paths for industry. In fact, in addition to allowing the development of bio-markers capable of identifying the different types of cancer in the preclinical phase, the creation of the technological platform will generate a series of repercussions on the regional and national territory identified in:      

• creation of a post processing system capable of highlighting Tumor and Hot Zone Markers in the images acquired in the Pathological Anatomy Laboratory, which allow the pathologist to focus only on specific areas of interest and not on the entire image;
• possibility of automatic reporting, through the use of certified algorithms that do not require supervision by the anatomopathologist;
• Decision Support System systems, to support medical staff on reporting through the use of machine learning algorithms for identifying patterns;
• reproducibility and sharing of the information content relating to the samples, to allow specialist Second Opinion consultations also to specialists located in distributed territorial structures;
• systems to support the work of the pathologist, through integration with distributed systems (for example: RIS, PACS, LIS, CCE, previous reports, sample collection videos).

The main beneficiaries of the collaborative platform, also structured in accordance with the logic of self-organizing evolution of social media, will mainly be the Campania players, but in a perspective of globalization and internationalization, the collaborative platform created will lend itself to being a national reference point for oncological experimentation .

Finally, we want to highlight that the aggregation that participated in the regional tender captures an unsatisfied need that characterizes the criticality of the research system in the Campania region: the difficulties and shortcomings for the technological transfer of scientific research products. This network will invest part of the resources that will be acquired to improve the perspectives of translational research and allow easier use in care pathways.
The aim to be achieved is to build a technology lab that becomes a regional structure capable of attracting large companies (including the pharmaceutical industry) to Campania research products.

The solution

Thanks to the research conducted in the Departments of Computer Science and Medicine of the University of Salerno (UNISA), assisted by a team of specialists from two Campania companies, a web platform was created available to the healthcare world, research and stakeholders. , which collects information, suggests evaluations based on the data acquired according to the canons of “Machine Learning” and compares diagnostic images thanks to specially developed algorithms.

The development of this platform is the result of the SICED “System Innovation for Cancer Early Diagnosis” Project co-financed by the POR CAMPANIA FESR 2014-2020. 

The Departments of Computer Science and Medicine of the University of Salerno, Bollino IT SpA and the leader Nabacom Srl have developed and tested artificial intelligence algorithms based on data obtained from genetic datasets of patients with pancreatic cancer. The platform will allow the insertion of clinical / diagnostic data of patients obtained from various sources and, as the knowledge, in terms of potentially analysable data / observations increases, it will be possible to retrain the model by identifying formulas / relationships that are gradually more precise and discriminating. .

The SICED project using innovative diagnostic techniques and enabling technologies 4.0 represents an opportunity for regional, national and international research and innovation. It is a space to share and exchange information, discoveries, therapeutic interpretations, well supported by technologies and tools for predictive analysis in full compliance with the most modern security and privacy standards.

The platform does not replace the human operator but by reducing the amount of data to be analyzed it assists medical-health realities. Furthermore, thanks to open innovation and the collaborative network,  we wanted to highlight the new model of doing research and innovation. The new organizational and technological challenges must be oriented towards a greater understanding of patients’ needs, the quality of treatments, educating and encouraging the adoption of healthier lifestyles by identifying environmental and / or family risk factors, and, last but not least , they must be able to ensure better cooperation between patients, professionals, companies and investors in HealthCare.

The data obtained by the SICED initiative – processed and made usable through 4.0 solutions – will contribute to improving the effectiveness of clinical-assistance surveillance paths in the population at risk and to innovate the current reference landscape.

For further information, consult the project website or contact the project manager, Eng. Silvio Gallo silvio.gallo@nabacom.it or the scientific contact, Prof. Francesco Palmieri fpalmieri@unisa.it.