New technologies in medicine: time to prepare

The technological revolution involving artificial intelligence, big data, machine learning and robotics is posed to deeply change healthcare and biomedical research, and things are changing fast. In this rapidly evolving scenario, researchers and health professionals need to acquire new skills and knowledge.

In less than a generation, technological innovations redesigned from scratch almost every aspect of peoples’ lives. Biomedicine and healthcare are quickly going the same way. Convergence between genomics, biosensors, electronic medical records, robotics, apps and wearable systems, all integrated by artificial intelligence (AI) infrastructures, offers the opportunity to provide personalized and more efficient healthcare. At the same time, AI is starting to have a deep impact on researchers’ work, and, according to projections, it will have a leading role in drug discovery processes in the coming years.

Pharmaceutical industry comes into play

After years of what can basically be described as a sceptic approach, the pharmaceutical industry is aggressively jumping into the sector of big data analysis and artificial intelligence. The primary objective on one hand is the identification of new biological targets and new compounds, while on the other hand is the prediction of potential toxicity and the optimization of clinical trials. Frost & Sullivan’s recent analysis shows how AI-based solutions in pharmaceutical industry will generate $2.199 billion in revenues by 2022.

Behind this change of attitude there is the possibility of producing and accessing much more information than can actually be used for discovering  and developing of new drugs: an overwhelming amount of structured and non-structured data, deriving from different sources such as population screening, genomic sequencing, metabolomics and transcriptomics, clinical studies and experiments, social networks, and health databases. They are today available to researchers, but their size and complexity make extremely difficult to manage them in order to spot patterns, detect anomalies and derive useful insights to generate new hypotheses. Thanks to the possibilities offered by big data analysis, machine learning and AI scientists can concentrate on creative thinking.

New skills, new culture

According to this emerging scenario, in hospitals or in research labs, both health professionals and scientists will have to learn new ways to work and to acquire new skills. The work environment will more and more include data collection through digital systems, governance and security of health data, use of remote monitoring systems and robotic equipment. In order to understand and govern these processes, future health professionals and researchers not only have to acquire basic information about artificial intelligence, robotics and bioinformatics, but they will also have to learn how to tackle problems in an agile, flexible and interdisciplinary way. These needs have been recently highlighted in the FEAM European Biomedical Policy Forum.

Michel Goldman ESMH Scientist“You have to start early” – says professor Michel Goldman, founder of the Institute for Interdisciplinary Innovation in Healthcare (I3H) and former Executive Director of the Innovative Medicines Initiative (IMI) “That’s why I think we should educate master students and PhD students. And if you anticipate what the future healthcare will be, with precision medicine, artificial intelligence and the other innovations we are seeing at the horizon, it’s essential that students are trained and educated to go across disciplines”.

But it is not only a matter of adequate training. It is the entire landscape of research and healthcare that should start changing. “Interdisciplinarity – continues Goldman – is still a problem when you apply for grants, or for new positions. Maybe they will say “ah, you are not focused enough”. Well, we are trying to explain to policymakers and stakeholders that they should do more to support people who are ready to go interdisciplinary. That is still a challenge”.

Hear the voice of citizens

How will patients, and citizens in general, react to AI systems scanning your x-ray exams, advising your doctor, even making diagnosis; wearable devices monitoring your health; robots performing biopsies? In the great debate about new technologies in medicine, their voice is almost missing. A 2018 survey conducted in USA and EU shows mixed feelings, with 63% of European patients defining themselves “very” or “somewhat” excited by the introduction of AI in healthcare. At the same time, in a separate question, 57% are “very” or “somewhat” concerned.

“When it comes to the use of Artificial Intelligence in the healthcare sector, policymakers need to ensure the focus is kept on patients and their needs”, writes MEP Tiemo Wölken (S&D, DE), member of STOA and of the European Parliament Committee on Legal Affairs  in an article published on The Parliament Magazine.

Renate Heinisch ESMH Scientist“First you must educate people who are involved in the healthcare systems, doctors and nurses” – says Renate Heinisch, pharmacist, former vice-chair of Science and Technology Options Assessment (STOA) panel and now member of the European Economic and Social Committee.

Building trust is also key. Personal data, especially in the health sector, will not only be stored, but they will also be processed by AI capable of profiling citizens and taking decisions affecting their life. Regarding this issue, in January 2019, the Consultative Committee of the Convention for the Protection of Individuals with regard to the Processing of Personal Data (Convention 108) published the Guidelines on Artificial Intelligence and Data Protection. The guidelines aim to assist policy makers, developers, manufacturers and providers in decision making processes, ensuring that AI technologies will be strongly grounded on fundamental rights. Moreover, some months later, the EU Guidelines on Ethics in AI were released.

“It is crucial that the highest level of transparency, data security and data privacy is guaranteed, and this is where policymakers can play a key role. – writes MEP Tiemo Wölken – It is our responsibility to establish a framework that fosters trust, safeguards data privacy and sees to it that data ownership remains with the patient. Furthermore, it needs to be clear who is accountable and who is liable for any damage or unexpected outcome. AI and robotics still present many complex new challenges, and therefore new laws and principles are needed. This will be one of the main challenges we need to tackle in this new legislative term”.

Check one of the Scientific Foresight Projects realised during the 8th legislative term, here :

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