“In five years, doctors will have an AI tool at their disposal to make diagnoses.”
The healthcare sector has always been at the forefront of research and innovation applied to improving people's quality of life. Digital solutions and disruptive technologies such as big data and artificial intelligence hold a particularly transformative potential for a less visible area of medicine: rare diseases.Photo: Román Latorre García, General Director of Sobi Iberia. Credit: Sobi.
By Elena Astorga
There is no universal consensus on the definition of a rare disease. In the European Union, a rare disease is identified as one that affects fewer than five persons per 10,000 inhabitants. In the United States, disorders affecting fewer than 200,000 people in the country are considered rare diseases. Beyond these conceptual differences, rare diseases have a low prevalence in common (although it is estimated that some 36 million people live with a rare disease in the EU, about 7% of the population), which makes it difficult to diagnose, treat and make visible the up to 7,000 diseases included in this category, which in Spain alone affect three million people.
Offering specific answers for this diverse group is the goal that drives the efforts of Sobi (or Swedish Orphan Biovitrum), a Swedish biopharmaceutical company with a presence in more than 30 countries and operations in more than 70. The company's strategy has for years embraced the digital transformation of medicine, developing products such as the Florio app for monitoring patients with hemophilia-a genetic disorder that prevents proper blood clotting, one of the company's major focuses-through its Munich-based subsidiary Florio GmbH, in charge of developing digital healthcare products.
"Healthcare is a sector where innovation is expected and deeply embedded in the DNA of most professionals," explains Román Latorre, CEO of Sobi Iberia. "We want to be part of these solutions and are working to integrate them into our approach to patient care." An industrial engineer by profession and with more than a decade's previous experience at the biotech company Novartis, Latorre took up the position in February 2023 and faces, among other challenges, the consolidation of the company as an innovative benchmark at a time of technological boom.
The healthcare sector is going through a period of digital transformation to improve the quality of patient care. What solutions have been implemented by Sobi to promote patient-centric or patient-centered care strategies?
Digitalization and technological innovation have greatly benefited the healthcare sector. Some of the most recent cases are telemedicine, wearable technology and IoT devices, remote patient care, the use of blockchain to decentralize databases and the incorporation of artificial intelligence to create portable medical monitoring devices.
These trends mean that all of us working in the sector need to adapt to the new demands of patients and the healthcare system itself. That is why we are developing applications for people with hemophilia or their caregivers, with which they can see their estimated levels of plasma factor concentrate, record bleeding, pain, wellbeing or physical activity, and which send reminders to the patient when it is close to the time to administer their treatment. In addition, healthcare professionals have access to a web-based control panel, where they can visualize everything in real time. With this, we seek to reduce uncertainty for patients and healthcare professionals, improve care and facilitate knowledge and self-management of the disease, empowering the patient to live a freer life.
What do you think are the barriers to driving a more digital and innovative pharmaceutical industry?
Pharmaceutical laboratories are highly regulated, making it difficult to rapidly implement new technologies and adopt digital practices in manufacturing, quality control, patient monitoring and drug delivery. Specific regulatory requirements and the lack of harmonization of regulations between and within countries complicate the standardization of digital systems across the industry.
In the specific case of Spain, the fact that healthcare competencies are delegated to the autonomous regions is an aspect to be considered in order to promote a more digital pharmaceutical industry. This makes it difficult to implement digital solutions and technologies on a large scale and to integrate data from different sources. If health information systems are not connected and do not share data effectively, it is difficult for pharmaceutical laboratories to harness the full potential of digital technology to improve patient outcomes and healthcare. Therefore, a joint effort and effective collaboration between healthcare providers, pharmaceutical laboratories, regulators and policy makers is required to address this barrier and improve interoperability and data integration in the healthcare system. Sometimes something as simple as a hospital firewall has stopped us from very interesting projects and initiatives.
Furthermore, at the European Union level, an additional complexity is the Data Protection Law. In Spain, most of the applications we have are anonymized, so we do not run the risk of having problems in this regard. However, if in the future we try to connect our tools with hospitals, we will have to find a way to ensure that the patient's data, if he or she so wishes, will be recorded in his or her clinical history in the National Health System.
What do you see as the potential benefits of digital solutions for capturing Real World Data (RWD) and Real World Evidence (RWE) in the industry and for society at large?
A lot of real world data and analysis (RWD) is currently available, but the generation of evidence based on this data (RWE) is still very complex as a result of the lack of homogeneity and quality of data sources and the increasing diversity of analysis models and algorithms.
In the industry RWE is used along the entire value chain, in clinical trial optimization, epidemiological evaluation, safety and risk/benefit assessment of therapy, outcome-based economic evaluation and in all kinds of commercial and business analyses. Health data from daily clinical practice can and should contribute to improving the overall healthcare system and are especially useful in the case of rare diseases.
In clinical trials, the use of RWD can accelerate the development of new drugs by optimizing the design of clinical trials, allowing virtual populations to be simulated more realistically before real patients. In addition, the use of RWD can favor, for example, in the case of more severe or low-prevalence diseases, the conduct of single-arm studies, providing a faster and less expensive alternative.
What opportunities do you see in the application of emerging technologies, such as artificial intelligence or telemedicine, in the approach to rare diseases?
The benefits of telemedicine are obvious, even before the pandemic, but its use remains more of an exception than a reality. In the case of rare diseases, the most obvious benefit is access to specialists more quickly and efficiently, something that can facilitate faster and more accurate diagnosis and more detailed follow-up. We have already implemented examples of telemedicine that allow physicians to perform remote consultations with specialists at referral centers, which helps to speed up the diagnosis of rare diseases. In addition, remote consultations in some cases allow diagnostic tests to be performed in real time, which can help initiate treatment more quickly.
Artificial intelligence has become one of the most fascinating fields of technology in just a few months. In March Bill Gates published an interesting letter with the title The age of artificial intelligence has begun, where he highlighted that the impact of AI will be as significant as the creation of the microprocessor, the PC, the internet and the cell phone; specifically highlighting the impact on health. There are already examples, especially striking in the area of oncology, where AI identifies patterns and relationships in patient data, improving diagnostic accuracy, in some cases by years. This new era is just beginning, and we are going to see incredible things: machine learning algorithms will help us detect patterns in symptoms and signs that today are difficult or impossible for human doctors to identify.
Regarding diagnosis, a point especially in need of improvement in the field of rare diseases (currently, the average in Spain is six years from the onset of symptoms), how can innovation help to identify disorders earlier?
In many cases, the delay in diagnosis may be due to a lack of knowledge on the part of the healthcare professional that the pathology exists or the difficulty of aggregating and interpreting the data collected. But revolutionary applications are already emerging, such as Glass.health, which allows clinicians to enter the data and, using AI, obtain a possible diagnosis. Much sooner than we think, these tools will accompany clinicians in their day-to-day lives. My prediction is that in the next five to ten years, every physician will have an artificial intelligence tool by his or her side that he or she will rely on for patient diagnosis.