The evolution of clinical practice, between artificial intelligence and Real World Data


It was discussed at TheBigDate together with the leading Italian experts in digital health and high tech applications for medical scientific research: this is how the way of doing research and clinical practice change between wearable devices, big health data, application frontiers and ethical issues

(foto: Luke Chesser/Unsplash)

What can be done, in practice, to make the most of the potential of the digital health and the data collected by real world? This is the question that was at the heart of TheBigDate, the online event promoted by Pfizer Italy and dedicated to the evolution of clinical practice through the potential of cutting-edge technologies. From which, however, it emerged first of all that to have the most advanced hardware and software solutions it is necessary but not sufficient: there are questions behind the paradigm shift in medicine cultural, of method, normative, ethical and naturally – scientific.

“An interesting and contemporary perspective is to equip machines with the ability to perceive the world, he began Fabio Moioli, Microsoft Italy Consulting Services director. “A perceptive capacity that finds application in the context of safety, but with concrete and already operational examples for the blind people, who need to be socially involved and can do so thanks to special glasses that transform visual information into words to be heard.

During TheBigDate he also talked about how the same technology, developed in the United Kingdom, is used for example in oncology for image recognition, employing the great ability of artificial intelligence to detect correlations and to do forecasts based on statistics. With the idea of ​​human-machine complementarity: “If I show an exam to both an algorithm and a doctor, the result is better than if only the doctor or only the algorithm saw it, since human beings and machines think differently and commit different errorsMoioli continued.

And looking a little further, we arrived at the most futuristic perspectives: on the one hand the quantum computing applied to healthcare big data, on the other hand the use of synthetic dna as a solution for data archiving, up to and including the evolution of role of the doctor, with the aforementioned complementarity between people and artificial intelligence that allows healthcare personnel to have more time to devote to empathic relationship with patients.

The challenge, also reiterated by Giovanni Corrao of the University of Milano-Bicocca, it seems to be that of harmonize science and technology, clinical practice with today’s wide availability of data. “Today we have about 7 thousand innovative drugs developing”, has explained, “And the normal length of the approval process of a decade or so is plenty resized, with drugs registered after small phase 1 and 2 studies, and skipping phase 3. The implication of all this is that the importance of clinical practice data, ie referring to when the drug is on the market, it is getting bigger “.

However, it is not a question of finding alternatives to evidence based medicine based on randomized scientific studies, but to complete this model with the approach of precision medicine, which goes beyond the evaluation of the single therapy and also includes an eye on expenses, pointing towards the paradigm of the so-called value based medicine. “It is no longer a question of whether a single drug or treatment is effective, but whether the whole therapeutic path whether or not it is suitable for the patient’s well-being “Corrao added. To do this, the answer is real-world data, what we generate by leaving fingerprints in the healthcare system, to be managed through huge, well-constructed databases.

Data that, more recently, are starting to arrive through special high-tech devices. From an impromptu survey conducted among participating doctors, for example, it emerged that in one third of cases they take advantage of health app, but also of smartwatch in one case out of 7, of sensoristica IoT in an equivalent way, and also of smart bracelets, and so on. Even if, as Corrao concluded, “The important thing is that science is good science, that the clinic is good clinic, while the tools are of relative importance because they are constantly changing “.

Established that artificial intelligence allows to collect, analyze and process a whole series of information that usually did not enter the databases, including images, written texts and much more, one of the key points today is in the structuring and characterization of the data itself. “The effort is to make the data fit the paradigma Fair, acronym for Findable, Accessible, Interoperable and Reusable “, has explained Riccardo Bellazzi of the University of Pavia. “To make good use of artificial intelligence we need to understand what we are putting into our data, and we can only do it if we model the cure process in the correct way, thinking about which algorithms to use and what type of evidence derive from it “.

In other words, given that artificial intelligence relies on large data collections, it is the very process of collection and the data culture to make the difference, given that today it can include a series of unstructured information. “The ultimate goal of the whole process is to build a system that learns from our data, in order to extract knowledge and then move from knowledge toaction. And that’s what needs to be kept in mind when talking about Fairness, he added.

In addition to being large data sources, the digital health they also have great potential like health opportunities, because they promote healthy lifestyles and foster, through the data they collect, the medical research. “Many devices can passively collect our physiological data, and the challenge is to relate them to the clinical outcomes of patients”, he said Eugenio Santoro, director of the Medical Informatics Laboratory at the Irccs Pharmacological Research Institute Mario Negri.

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(foto: Pixabay)

The fields of application already concrete are numerous: from the studies that measure the sleep quality and the correlation with its duration up to those evaluating the joint mobility, comparing the data collected by the monitoring devices with what the patients themselves declare about their state of health. “Real world data studies performed using digital health tools enroll patients in much shorter times, can enjoy data collected from different sources and with regularity, improving the accuracy of the studies e reducing costs, he added. “And in future studies, randomization will increasingly take place using social media systems, with drugs shipped home, data based on outcome reported by patients and also analyzed through artificial intelligence systems “.

However, one of the critical points reiterated is that, if data is needed to carry out the analyzes, in Italy these come from 21 different systems (between regions and autonomous provinces), which speak little to each other and are not interoperable right easily accessible. “It is a situation that has emerged strongly even with the health emergency”, concluded Santoro, “and first of all we need to redesign our electronic health record from a clinical point of view “.

“There are two paths that go in parallel”, he added Daniela Scaramuccia at IBM, “On the one hand we need to improve the way we collect data, and we expect the National recovery and resilience plan give a strong push in this sense, but in parallel we cannot throw away the enormous amount of data we already have and which are structured in silos “. The great advantage we have today, as it has emerged, is that artificial intelligence allows us to process this data, bypassing that phase of manual work which made them unusable in the past.

In a broader sense, however, when it comes to the evolution of clinical practice and real world data, the issues of Balance, for example between artificial intelligence, ethics and regulations. “We need algorithms that are free of bias and that they are explainable and understandable, but above all we need agreement and harmony between stakeholders and regulatory bodies, and that we continue to deal with these issues “, concluded Scaramuccia. Finally, taking care of a further fundamental point of balance: that between the possibility of doing Research e i rights individual, between the usability of data to allow scientific advancements and the confidentiality and privacy of people.

(Ref Pfizer code: PP-ONC-ITA-0461)


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