Healthcare, medtech, and life sciences companies operate in a highly regulated and increasingly digital environment. Health data, digital products, cloud solutions, AI, and complex partnerships create legal intersections between data protection, technology, contracts, governance, and regulatory requirements. We help companies structure these issues from a legal perspective and integrate them into products, processes, contracts, and internal responsibilities.
A regulated environment creates legal intersections
Depending on the product, activity, and role, requirements related to data protection, contract law, and governance—as well as product-specific, research-related, or professional legal requirements—may be relevant in the healthcare and life sciences sectors. It is crucial to identify these intersections early on and align them with the business model, technology, and internal responsibilities.
Health data is particularly sensitive
Health data is considered particularly sensitive personal data. Digital health services, platforms, and data-driven products therefore raise questions early on regarding transparency, purpose limitation, data security, data processing on behalf of others, international data flows, and access rights.
External technology providers are becoming centralized
Cloud, SaaS, platform, and analytics services are increasingly becoming part of healthcare and life sciences processes. As a result, contract drafting, data protection, information security, audit rights, subcontractors, availability, and exit strategies are becoming more important.
Partnerships assign roles and responsibilities
Research institutions, hospitals, manufacturers, distributors, technology providers, and other partners often collaborate within complex structures. Contracts and governance must therefore clearly define responsibilities, data flows, rights to results, liability, and decision-making processes.
When it comes to apps, platforms, telemedicine, and other digital health offerings, the business model, user roles, data flows, and technical functions must be considered together. Of particular relevance are data protection, information security, contractual and liability issues, cloud usage, and any sector-specific regulatory requirements.
Health data is subject to special protection under Swiss data protection law. Companies should clarify what data is processed and for what purposes, who is the data controller or data processor, which third-party providers have access, and whether data is transferred abroad. If the data relates to the EU, the GDPR may also apply.
Healthcare and life sciences companies are increasingly using cloud infrastructure, SaaS products, platforms, and specialized technology providers. Key areas to review include data locations, subcontractors, information security, audit rights, availability, liability, business continuity, and exit strategies. For regulated activities, additional requirements regarding governance and oversight may apply.
AI can be used in diagnostics, research, product development, documentation, or operational processes. From a legal perspective, questions arise regarding the data set, transparency, human oversight, accountability, validation, and governance. Depending on the application, product-specific regulatory requirements may also be relevant.
Life sciences projects are often organized on the basis of a division of labor. Research institutions, manufacturers, distributors, hospitals, software providers, and other partners assume different roles. Contracts should clearly define responsibilities, data flows, intellectual property, usage and publication rights, quality, liability, and termination, in particular.
Clear lines of responsibility and internal policies help manage data protection, technology use, contracts, and regulatory interfaces in day-to-day operations. Depending on the organization, data protection policies, AI guidelines, approval processes, authority matrices, and documented control mechanisms may be useful.
Health data and critical digital systems underscore the importance of a structured response to security incidents. In the event of loss, misdelivery, or unauthorized access, technical containment measures, legal assessments, potential reporting and disclosure requirements, and internal decision-making processes must be coordinated.
The first step is to ask how the solution actually works, what services it provides, what data it processes, and what roles internal departments and external partners play.
Next, data flows, responsibilities, access rights, and relevant legal requirements are mapped out. This makes it possible to determine which data protection, contractual, governance, and regulatory issues are essential to the specific project.
Contracts with customers, partners, and cloud and technology providers should consistently define the scope of services, responsibilities, data access, intellectual property, liability, and termination.
Responsibilities, approvals, internal rules, and control processes should be structured in such a way that data protection, the use of AI and technology, and external providers can be appropriately managed during day-to-day operations.
New features, uses of data, partners, or markets may require a new legal assessment. Legal structures should therefore be designed in such a way that they can evolve alongside the product and business model.
Apps, platforms, telemedicine, and data-driven services are increasingly linking healthcare services with software and external infrastructures. As a result, data flows, user roles, contracts, and regulatory interfaces are becoming key design considerations.
AI systems can simultaneously impact data protection, governance, product requirements, and accountability. Clear lines of responsibility, robust data processes, and the question of how automated results are monitored and used are particularly important.
Healthcare and life sciences companies are increasingly turning to external platforms, laboratory service providers, SaaS providers, and cloud providers. In doing so, they must consider data protection, information security, regulatory responsibilities, audit rights, and exit scenarios as an integrated whole.
The further and secondary use of health data can offer scientific and economic opportunities. At the same time, there are increased requirements regarding data protection, transparency, access rights, purpose limitation, and governance. Depending on the context, research-related requirements may also be relevant.
Increasing digitalization is heightening reliance on IT systems and external providers. Security incidents can therefore raise issues related to data protection, contracts, business continuity, internal governance, and communication all at once.
When it comes to digital health solutions, we don't view data in isolation, but rather in conjunction with technology, contracts, business models, and internal organization.
Digital health products can only be meaningfully evaluated from a legal perspective if their technical and operational functioning is also understood.
Data protection, contract law, technology, governance, and sector-specific requirements may all be relevant at the same time. We map out these intersections early on and tailor our legal support to the specific project.
When multiple parties are involved, economic interests, data flows, responsibilities, and decision-making processes must align. We help map out these structures in clear contracts and processes.
Clear responsibilities, approvals, and internal rules lay the foundation for integrating new technologies, data uses, and external providers into existing structures in a controlled manner.
Legal requirements must be able to be translated into products, processes, contracts, and responsibilities. In doing so, we prioritize the issues that are actually relevant to the specific business model and risk profile.
