Future-ready research and innovation for health

Future-ready research and innovation for health

Our research and development (R&D) builds state‑of‑the‑art expertise in agile, AI‑driven solutions, next‑generation data platforms, and digital compliance accelerators: delivering innovation, safety, and compliance in highly regulated industries.

Explore our innovation areas

Pioneering the future of regulated digital health, MedTech and pharma

Global healthcare is evolving rapidly under the pressure of advancing technology, shifting regulations, and changing market needs.

Our vision is to anticipate these shifts and turn them into opportunities. We build innovations that are safe, adaptable, and truly ready for the realities of highly regulated environments.

By harnessing digitalisation, AI, and cloud technologies, we aim to make healthcare delivery safer, more efficient, and more personalised for patients, professionals, and partners worldwide.

Our R&D focus: Three strategic innovation pillars

RegProof® framework for compliant digital innovation

We are evolving our RegProof® framework for faster, more reliable delivery of regulated digital solutions. Our R&D focuses on integrating agile methods, automated quality processes, and real‑time compliance monitoring, which enables organisations to innovate without slowing down. The work includes developing lifecycle models, tooling, and best practices that keep pace with changing standards and industry needs.
Trusted cloud infrastructure & secure data for healthcare

We are designing the next generation of secure, compliant cloud ecosystems that unite healthcare application development and operation with Trusted Research Environments (TREs) for collaborative, privacy‑protected data use. Building on our industry cloud for health foundations, our R&D explores regulatory compliance for cross‑border health data processing, scalable multi‑cloud deployments, and the Medical Device’s Digital Environment (MDDE) as a model for enabling regulated applications in dynamic, change‑controlled environments.
Compliance-driven AI for healthcare innovation

We are developing compliant, transparent AI systems that healthcare professionals, patients, and regulators can trust. Our R&D focuses on methods for creating such systems in a constantly evolving regulatory landscape, combining privacy‑preserving techniques like federated learning with real‑time compliance monitoring. We also explore AI‑augmented product development, enhancing the entire lifecycle, from initial design to operation and beyond, to accelerate the delivery of safe, regulation‑ready AI solutions.

Delivering innovation – Current research projects

Our international collaborations turn emerging ideas into tested, solutions. The projects bring together research institutions, industry leaders, and healthcare providers to address pressing challenges in digital health.

UNCAN‑CONNECT

Building a federated cancer research data platform across Europe

The project builds a secure, decentralised network to connect cancer research data across borders, enabling collaboration while preserving privacy. Read more about UNCAN-CONNECT.

PROFIT

Optimising hospital workflows through AI and data innovation

The project combines AI, secure data integration, and smart orchestration to optimise hospital operations, reduce staff workload, and improve care quality. Read more about PROFIT.

Secur‑e‑Health

Enabling trusted remote health monitoring and integration

The project delivers secure, interoperable solutions for remote cardiac monitoring and data exchange between providers. Read more about Secur-e-Health.

See what we’ve been doing – Publications and thesis works

Research articles

Linjama A, Granlund T. Continuous Deployment Adoption: Insights From a Public Sector Implementation. Journal of Software: Evolution and Process 38, no. 1 (2026): e70080.
Sirin O, Sami MA, Granlund T, Rasku J, Zhang Z, Abrahamsson P. Enhancing regulation-adherent requirement engineering with contextual AI: an industrial study. In: Product-focused software process improvement. Springer Nature Switzerland; 2026. p. 69–85.
Virkkunen S, Granlund T, Kaikkonen R. Implementing a Cost-Efficient and Interoperable Health Data Infrastructure: A Multi-Region Finnish Case Study. Studies in Health Technology and Informatics. 2025 Oct 2;332:113-7. DOI: 10.3233/SHTI251507.
Setälä M, Jafri I, Peltonen L-M. Combining Generative AI and Speech-based Solutions to Support Nurses. In: WORK2025 Abstract Book; 2025 Aug 20-22; Turku, Finland. Turku: University of Turku; 2025. p. Abstract 19.05. ISBN 978-952-02-0265-1 (e-book).
Virkkunen S, Granlund T, Kaikkonen R. Data Literacy in Healthcare: The Key to Effective AI and Improved Care. In: WORK2025 Abstract Book; 2025 Aug 20-22; Turku, Finland. Turku: University of Turku; 2025. p. Abstract 7.14. ISBN 978-952-02-0265-1 (e-book).
Setälä M, Peltonen R, Peltonen L-M. GenAI-assisted Personalized Care Pathway After Coronary Angioplasty. In: WORK2025 Abstract Book; 2025 Aug 20-22; Turku, Finland. Turku: University of Turku; 2025. p. Abstract 19.04. ISBN 978-952-02-0265-1 (e-book).
Kaari S, Granlund T, Kaikkonen R. Towards Integrated and Intelligently Summarized Health Data. In: WORK2025 Abstract Book; 2025 Aug 20-22; Turku, Finland. Turku: University of Turku; 2025. p. Abstract 19.27. ISBN 978-952-02-0265-1 (e-book).
Paloniemi T, Setälä M, Mikkonen T. Porting an LLM based Application from ChatGPT to an On-Premise Environment. In: 2025 IEEE/ACM 22nd International Conference on Software and Systems Reuse (ICSR); 2025. p. 78-83. DOI: 10.1109/ICSR66718.2025.00014.
Chen B, Tackman J, Setälä M, Poranen T, Zhang Z. Integrating Access Control with Retrieval-Augmented Generation: A Proof of Concept for Managing Sensitive Patient Profiles. In: Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing (SAC ’25); 2025. New York: Association for Computing Machinery; 2025. p. 915-9. DOI: 10.1145/3672608.3707848.
Linjama A, Granlund T. Adopting Continuous Deployment in a Public Administration Project: An Industrial Case Study. In: Product-Focused Software Process Improvement. Springer Nature Switzerland; 2025. p. 84-99.
Granlund T, Stirbu V, Mikkonen T. Toward a Regulatory-Compliant Lifecycle for Artificial-Intelligence-Based Medical Devices in the European Union: Industry Perspectives. Computer. 2024 Sep;57(9):24-34. DOI: 10.1109/MC.2024.3414368.
Granlund T, Stirbu V, Mikkonen T. Medical Software Needs Calm Compliance. IEEE Software. 2022 Jan;39(1):19-28. DOI: 10.1109/MS.2021.3117292.
Stirbu V, Granlund T, Mikkonen T. Continuous Design Control for Machine Learning in Certified Medical Systems. Software Quality Journal. 2022;31(2):307-33. DOI: 10.1007/s11219-022-09601-5.
Limingoja L, Antila K, Jormanainen V, Röntynen J, Jägerroos V, Soininen L, et al. Impact of a Conformité Européenne (CE) Certification-Marked Medical Software Sensor on COVID-19 Pandemic Progression Prediction: Register-Based Study Using Machine Learning Methods. JMIR Form Res. 2022 Mar 17;6(3):e35181. DOI: 10.2196/35181.
Toivakka H, Granlund T, Poranen T, Zhang Z. Towards RegOps: A DevOps Pipeline for Medical Device Software. In: Product-Focused Software Process Improvement. Springer International Publishing. 2021. p. 290-306.
Granlund T, Stirbu V, Mikkonen T. Towards Regulatory-Compliant MLOps: Oravizio’s Journey from a Machine Learning Experiment to a Deployed Certified Medical Product. SN Comput Sci. 2021;2(5):342. DOI: 10.1007/s42979-021-00726-1.
Stirbu V, Granlund T, Helén J, Mikkonen T. Extending SOUP to ML Models When Designing Certified Medical Systems. In: 2021 IEEE/ACM 3rd International Workshop on Software Engineering for Healthcare (SEH); 2021. p. 32-5. DOI: 10.1109/SEH52539.2021.00013.
Granlund T, Kopponen A, Stirbu V, Myllyaho L, Mikkonen T. MLOps Challenges in Multi-Organization Setup: Experiences from Two Real-World Cases. In: 2021 IEEE/ACM 1st Workshop on AI Engineering – Software Engineering for AI (WAIN); 2021. p. 82-8. DOI: 10.1109/WAIN52551.2021.00019.
Granlund T, Vedenpää J, Stirbu V, Mikkonen T. On Medical Device Cybersecurity Compliance in EU. In: 2021 IEEE/ACM 3rd International Workshop on Software Engineering for Healthcare (SEH); 2021. p. 20-3. DOI: 10.1109/SEH52539.2021.00011.
Granlund T, Mikkonen T, Stirbu V. On Medical Device Software CE Compliance and Conformity Assessment. In: 2020 IEEE International Conference on Software Architecture Companion (ICSA-C); 2020. p. 185-91. DOI: 10.1109/ICSA-C50368.2020.00040.

Other publications

Lähteenmäki J (editor), Ahola P, Baraian A, Förger K, Granlund T, Hopia J, Kaikkonen R, Mikkonen T, Niemirepo T, Pajula J, Partanen J, Pellinen T, Stirbu V, Torhola M. Agile and holistic medical software development: final report of AHMED project. 2023.
Granlund T, Vedenpää J, Heikkinen S. Foundations of medical device software cybersecurity compliance. White paper. Solita, 2022 (2nd edition).

Thesis

Sirin A. O. Enhancing Regulation-Adherent Requirement Engineering with Contextual AI – An Empirical Study. Master’s Thesis, Faculty of Information Technology and Communication Sciences. Tampere University, 2025.
Peltonen R. RAG-chatbottien kehittäminen terveydenhuoltoon : Tapaustutkimuksena HeartWise-tekoälychatbot. Kandidaattitutkielma, Faculty of Information Technology and Communication Sciences. Tampere University, 2025.
Karppila I. Orchestrating Patient Journeys with Healthcare Data in the EHDS. Bachelor’s Thesis, Faculty of Management and Business. Tampere University, 2025.
Ojanen M. ISO 13485:2016 vaatimustenmukaisuus lääkinnällisten ohjelmistojen IT-palvelutuotannossa. Diplomityö, School of Engineering Science. LUT University, 2024.
Etim V. Leveraging Generative AI in Enhancing Product Owner Responsibilities in the Post-Market Phase of Medical Device Software. Master’s Thesis, Faculty of Information Technology and Communication Sciences. Tampere University, 2024.
Chen B. An Exploration of Using Retrieval-Augmented Generation With Access Control. Master’s Thesis, Faculty of Information Technology and Communication Sciences. Tampere University, 2024.
Mikkonen V. Adjusting design methodology to meet the medical software regulations: Insights from Service and UX Designers. Master’s Thesis. Faculty of Information Technology and Communication Sciences. Tampere University, 2024
Linjama A. Jatkuvan käyttöönoton toteuttaminen julkishallinnon hankkeessa: Tapaustutkimus. Diplomityö, Master’s Programme in Computer, Communication and Information Sciences. Aalto-yliopisto, 2023.
Lylynen L. Terveydenhuollon tekoälysovelluksen kehitysprojekti, käyttöönotto ja käyttöön vaikuttavat tekijät : case Oravizio. Master’s Thesis. Master’s Degree Programme in Well-Being Technology, Tampere University of Applied Sciences, 2022.

Want to hear more? – Contact us!

Tuomas Granlund RegOps Development Director, R&D Portfolio Manager, Solita Health

[email protected]
Risto Kaikkonen Director, Solita Health

[email protected] +358 415 368 745
Manu Setälä Head of Research, Solita

[email protected] +358 505 577 910

Future-ready research and innovation for health