Solving the Individual Human Data (IHD) Challenge: Enabling Responsible Data Reuse
in Life Sciences
Author: Mike Tatarnikov, CDO
Category: Innovation & Technology
Format: Whitepaper
Estimated read time: ~12 min
Basel, Switzerland – November 19, 2025
In Life Sciences, using Individual Human Data (IHD) is essential for research, but many teams still struggle to manage it. Consent rules vary, many organisations still rely on paper based forms, and researchers often need to check access rights manually. ownership of clinical assets changes hands, datasets can become fragmented or formatted inconsistently, which makes reuse harder than it should be.
Overcoming the Challenges of Reusing Individual Human Data
In our new whitepaper, Mike Tatarnikov, Chief Data Officer at MIGx, describes a clear way to address these issues. He outlines four elements that together support responsible reuse of clinical data: classifying datasets, providing a place to access them, explaining how decisions are made, and preparing or anonymising data when needed.
A Marketplace for Clinical Data
The paper then illustrates how a marketplace can bring these ideas together. Researchers can look for datasets using metadata, request access, and receive data in a form that matches the approved use.
From there, the marketplace grants access automatically when possible or routes it for review when needed, and it logs all activity to support compliance. When consent limits how data may be used, the marketplace provides only a suitable subset. It also limits access in time and revokes it once the approved work is complete.
What You’ll Discover
- Why using and reusing Individual Human Data (IHD) is difficult today, from consent rules to fragmented clinical datasets.
- The four elements of the proposed solution: a classifier, a data marketplace, an explainer, and a data curator/anonymiser.
- How a marketplace lets researchers search for datasets using metadata and request access under clear legal and ethical conditions.
- How time limited, logged access and curated data products can support compliance and help shorten study cycles from months to days.
By addressing these challenges directly, organisations can move from scattered, inconsistent clinical data toward a more controlled environment where research becomes easier and more efficient.
📥 Submit Form below and receive Whitepaper PDF via email and and discover how responsible data reuse can make research more efficient while remaining fully compliant.
Ready to Transform Your Clinical Data Reuse?
Submit Form below and receive Whitepaper PDF Download via Email and discover how responsible data reuse can make research more efficient while remaining fully compliant.
FAQs
What is Individual Human Data (IHD) reuse in Life Sciences?
Individual Human Data (IHD) reuse refers to the use and reuse of human clinical data in Life Sciences research and clinical trial operations. It plays an important role in activities such as patient targeting, stratification, and trial outcome simulation, and can support more efficient study designs when used appropriately.
What is consent-aware access to clinical data?
Consent-aware access means access decisions reflect the consent conditions attached to a dataset, including any site-specific restrictions. In practice, requests are evaluated against the intended purpose of analysis, the jurisdiction of the dataset, and the legal and ethical conditions that apply before access is granted.
How does a clinical data marketplace support data reuse?
A clinical data marketplace supports data reuse by helping researchers discover, request, and use datasets through detailed metadata and integrated approval workflows. Researchers can search using study-level and participant-level attributes, initiate access requests directly through the platform, and receive time-limited access to data delivered in a format matched to the approved purpose.
What are explainable access decisions in clinical data governance?
Explainable access decisions are approvals or denials that come with a clear rationale. They matter because compliant environments require transparency and accountability, and because a clear explanation supports a traceable audit history of how classification and access decisions were made.
Why is rare disease data harder to anonymise?
Rare disease data is harder to anonymise because patient populations are very small, which increases the risk of re-identification even without direct identifiers. Combinations of demographic and clinical details can still make individuals identifiable, which is why stronger privacy techniques may be needed to balance data utility with protection.
