Innovative and digital health technologies
TKP 2021-2025
The research was funded by the National Research, Development and Innovation Fund (TKP2021-NKTA-36).
Nowadays, the development and market entry of innovative digital medical devices (DMD) can only be successful if they offer real (added) value to users compared to existing alternatives and if there is scientific evidence to demonstrate their (clinical) efficacy, safety, social and economic benefits.
The research is divided into two subprojects:
Prof. Levente Kovács DSc, Head of Subproject I, Rector, Physiological Controls Research Center (PHYSCON, physcon.uni-obuda.hu), University Research and Innovation Center (URIC)
Dániel András Drexler PhD, Principal Investigator of Subproject I, Physiological Controls Research Center (PHYSCON, physcon.uni-obuda.hu), University Research and Innovation Center (URIC)
The research addresses two major public health challenges: cancer treatment and diabetes.
There is significant potential in personalizing cancer therapy (Tasks 1 and 2), with benefits including:
- improved overall survival;
- enhanced quality of life for patients;
- reduced treatment costs;
- lower risk of resistance development;
- and fewer side effects.
Our research center has been working on this topic for over a decade, supported by an ERC grant from the European Union and a Competence Center grant. In these projects, we successfully demonstrated the concept through animal experiments.
Personalized treatment requires a mathematical model that accurately describes the effect of the drug on the tumor in a given patient. We are developing algorithms to construct and individualize this model (Task 1). While the model structure is based on previous research, the newly developed algorithms estimate patient-specific parameters and identify the model accordingly.
Once the mathematical model is identified, it can be used to optimize therapy. The optimal treatment (Task 2) is computed based on the patient-specific model (from Task 1), resulting in a fully individualized protocol. We are developing multiple optimization algorithms using different approaches, as various scenarios may require different strategies. These algorithms are tested with in silico experiments.
The development of physiological control algorithms (Task 3) differs from therapy optimization in terms of injection frequency. While cancer therapy may involve infrequent dosing (e.g., twice per week), physiological regulation in diabetes requires more frequent — sometimes continuous — intervention. We focus on designing control algorithms for artificial pancreas systems, aimed at compensating for external disturbances such as meals and physical activity. These algorithms are intended to improve the quality of life for people living with diabetes.
Prof. Márta Péntek DSc, Head of Subproject II, Health Economics Research Centre (HECON), University Research and Innovation Centre (URIC)
The aim of the research is to develop a methodology for measuring the health and socio-economic gains of digital medical devices (DMDs) in order to support scientifically and economically successful domestic DMD development. In the first two years of our subproject (2022, 2023), we have focused on the first three research objectives out of the five technical tasks outlined in the proposals:
- Is DMD clinically effective and safe? How much more effective and safer than existing DMDs? Literature evidence search and analysis, automated literature search;
- What is the outcome of DMDs from the perspective of patients, users? Outcome measurement, patients’ user skills, knowledge, attitudes and preferences
- How can digital data from DMDs be used for medical decision-making?
Further goal related to research objectives 4 and 5:
- cost-effectiveness analysis, health technology assessment
- measuring innovation performance and competitiveness of DMDs
Why our research is useful…
… for developers of digital medical devices?
- They help to provide a systematic overview of existing DMD developments,
- a systematic literature analysis and evaluation of the effectiveness and safety of comparator DMDs in the field,
- the design of the DMD clinical trials to be developed and
- measuring and communicating results in a way that can be directly used to evaluate new technology and inform social inclusion decision-making.
… for doctors?
- It uses accepted methods of evidence-based medicine to provide sound information about DMDs, to help understand the value of DMD outcomes from the patient’s perspective, and to use digital DMD data for clinical decision making.
… for patients?
- The methods developed as a result of our research provide an opportunity to take into account patient concerns in DMD development (patient preferences, device acceptability, usability) and to speed up the process of development, approval and social security certification of new devices, thereby improving awareness and access to DMD devices.
… the funder, the health policy makers?
- Our methodological developments will better measure the individual and societal benefits of DMDs, thereby supporting clinically and health-economically sound decision-making.
