Optimized treatment for every patient according to their unique situation promises huge improvements in healthcare. To reach this next level in personalized healthcare requires the aggregation, processing and analysis of large amounts of health data. For this to happen, even closer collaboration between the many players in the healthcare system is paramount.
scienceindustries | Head Biotechnology
As every human is an individual, so every disease has unique aspects in each patient. Previously, treatments were derived from experiences with large groups of patients and therefore reflected an average approach that was suitable for a majority, but not all.
More stratified approaches, taking into account factors such as age, sex, and health status, have made it possible to better fit treatments to the needs of individual patients. But for a truly personalized healthcare approach, molecular health markers for the individual have to be analyzed using huge collections of population health data as a background.
Roche, with its headquarters in Basel, Switzerland, is the world's largest biotech company, with 17 biopharmaceuticals on the market, and the global leader in cancer treatments. At the same time, the company is the leading provider of in vitro diagnostics.
This combination of competencies, together with strong partnerships that focus on the use of medical data to generate knowledge for the treatment of patients, has also made Roche a frontrunner in personalized healthcare.
For this, the combination of expertise in genomics and clinical data analysis was essential. In 2018, Roche merged with Foundation Medicine, a US company focusing on molecular information in oncology. By genomic profiling a patient's tumor genome, the company identifies clinically relevant alterations, thus providing a service akin to SOPHiA GENETICS in Lausanne.
This genetic information is then combined with the world’s most up-to-date published cancer literature database to match patient’s genomic profiles with the best-known treatment option to support clinical decision-making.
Foundation Medicine's genomic database, one of the world's largest with information from more than 350,000 patients, is also used to match patients to clinical trials. The aim is to improve drug development and to support basic cancer research by sharing anonymized data with research institutions. In Switzerland, this service is offered in collaboration with the University Hospital Zurich.
In a complementary approach, Roche acquired US healthcare technology and services company Flatiron Health in 2018. Flatiron collects clinical data about oncology cases, treatments and outcomes in a massive database. This currently comprises more than 2.4 million patient records, derived from a close collaboration with a large network of cancer treatment and research centers. Information is extracted not only from electronic medical records, but also from unstructured data, like laboratory and imaging results.
The application of high-powered data analytics to this huge and highly representative clinical data set makes it possible to generate real-world evidence about treatment outcomes, suggesting better treatment options and facilitating clinical trials especially for rare cancers. The de-identified data are used by cancer researchers worldwide to advance treatments.
The availability of Foundation Medicine's genomic profile data and Flatiron's clinical data sets under the common roof of the Roche Group now allows what some have described as the Holy Grail of cancer research: the combination of genomic and clinical data into a clinico-genomic database (CGDB) to understand what drives disease. This allows a much better prediction of individual patient's developments, and a better selection of treatment options based on real-life experience from comparable cases.
The CGDB also helps to bring precision medicine faster to patients. Using traditional approaches, it was almost impossible to set up clinical trials for the treatment of very rare cancer types due to the limited number of patients and lack of a suitable control group. The CGDB helps to quickly identify patients for the experimental arm of the study, and provides data for the control group, thereby supporting the development of novel treatments and more efficient clinical trials.
For Roche, the integration of diagnostics, (bio)-pharmaceuticals and big data analysis is an important building block of the company's personalized medicine strategy. But the beneficiaries of these activities form a much larger group.
The close collaboration and the sharing of de-identified data between medical institutions, regulators, healthcare companies and scientists supports basic research, the development of better and more targeted active substances and diagnostics, and the optimization and adaptation of therapies for the benefit of patients all over the world. Similar approaches with a strong focus on big data are also used by other players and will provide new opportunities for healthcare biotechnology companies.
In Switzerland, the Swiss Personalized Health Network (SPHN) has been working since 2017 to promote the development of personalized medicine and personalized health. The result is a national collaboration of unprecedented scale, involving 35 hospitals, research institutions and other organizations.
The main focus until 2020 is on building the necessary infrastructure to enable nationwide use and exchange of health data for research. Funded with CHF 68 million, the SPHN is working on the development of a national health data infrastructure and cutting-edge IT systems (BioMedIT). In the next funding period (2021 – 2024), the network will extend its activities and collaborations, possibly including public-private partnerships.
While the huge potential of personalized healthcare is obvious, several obstacles slow down its development. The digital infrastructure for the collection and aggregation of health data is still only weakly developed.
A major challenge is Switzerland's pronounced regionalism and the sovereignty of the cantonal competencies in the health care sector. This makes collaborations on a national scale difficult.
In fact, a recent international comparison of healthcare digital strategies by the Bertelsmann Foundation (#SmartHealthSystems, 2019) ranks Switzerland 14th out of the 17 evaluated countries for the digital health index.
The index captures national-level healthcare system digitalization on the basis of 34 indicators relating to strategy, technical implementation status, maturity, and the degree to which integrated health-data exchange is actually taking place. For the sub-index - actual use of data - Switzerland is ranked even lower at 16.
Despite several ongoing initiatives, actual progress and implementation is slow. For example, the introduction of the electronic patient record (EPR) system - a personal collection of treatment-related documents - has been plagued by delays and technical difficulties and will be only partially operable in 2020, starting in April.
Obviously, a concerted effort by all stakeholders is required to move Switzerland forward in the field of digital health and personalized healthcare. To take full advantage of new therapies made possible by personalized healthcare approaches, adjustments to the registration process by Swissmedic, the Swiss regulatory authority for therapeutic products, are required.
These should take into account the special properties of personalized medicines that distinguish them from more traditional products; such as the possibility of targeting only small patient groups. Also, new models for pricing and reimbursements for personalized drugs and diagnostic procedures have to be developed.
‘The application of high-powered data analytics ... makes it possible to generate real-world evidence about treatment outcomes, suggesting better treatment options and facilitating clinical trials’ In Switzerland, the Swiss Personalized Health Network (SPHN) has been working since 2017 to promote the development of personalized medicine and personalized health. The result is a national collaboration of unprecedented scale, involving 35 hospitals, research institutions and other organizations.