HealthyData.Science is an independent directory of AI tools for healthcare and life sciences, designed for regulated organisations in pharma, medtech, CROs, and healthcare providers.
Our goal is to help decision‑makers understand what a tool does, how it fits into regulated workflows, and where further due diligence is required – not to declare a single “best” product.
We treat every listing as a decision‑support asset, not marketing collateral.
This policy explains how we source, verify, and present information so that you can assess AI tools with appropriate confidence and scepticism.
What we do
Curate AI tools relevant to healthcare, life sciences, and adjacent regulated domains.
Summarise what the tool does, who it is for, and where it typically fits in the value chain (e.g., evidence synthesis, pharmacovigilance, lab automation, R&D, clinical trials).
Highlight key architectural, integration, and governance features that matter for buyers in regulated environments.
Link to primary sources and vendor documentation wherever possible.
What we do not do
We do not provide legal, regulatory, or clinical advice.
We do not perform full technical audits, cybersecurity testing, or formal validation of claims.
We do not guarantee that any tool is compliant, safe, or suitable for a specific use case in your organisation.
We do not replace your internal or external due diligence, including regulatory, quality, and procurement reviews.
We strongly recommend that you treat HealthyData.Science as one input into a broader evaluation process that includes your legal, regulatory, QA, and IT stakeholders.
Discovery and inclusion
We add tools to the directory when they meet all of the following criteria:
They use AI or advanced analytics in a way that is material to the product.
They are relevant to healthcare, life sciences, or adjacent regulated domains (e.g., pharma, medtech, CROs, public health, regulated digital health).
They have a public presence (website, documentation, or publications) sufficient for us to describe their capabilities with reasonable confidence.
Listing workflow
For each tool we:
Collect public information from the vendor’s site and documentation.
Cross‑check claims against additional sources where possible (e.g., publications, regulatory databases, client case studies).
Classify the tool into one or more categories and sub‑categories aligned with healthcare and life sciences workflows.
Apply our “Three Walls of Friction” lens (data governance, integrations, and real‑world KPIs) to identify what we can and cannot verify.
Add a “Last reviewed” date and maintain an internal review cadence.
We apply a consistent evaluation framework to every listing. This framework is not a formal certification, but it makes our reasoning explicit so you can calibrate your own trust.
4.1 Data governance and safety
We look for:
How the tool handles data ingestion, storage, and processing (including PHI, PII, and sensitive scientific data).
Whether the vendor describes controls such as access management, encryption, audit trails, and data residency.
Whether there is any indication of alignment with relevant frameworks (e.g., GDPR, HIPAA, GxP, ISO standards), as stated by the vendor.
Where the vendor provides concrete details, we summarise them. Where they do not, we indicate that the information is not available or not verified.
4.2 Integration into regulated workflows
We assess:
Typical integration points (e.g., EHR, CTMS, LIMS, safety databases, document management, data lakes).
Whether the vendor discloses supported standards or APIs.
How the tool is positioned for use in regulated contexts (e.g., MDR/IVDR‑regulated devices, GxP environments, safety‑critical decision support).
We focus on clarity: where integrations and positioning are vague, we say so and flag this as an additional due‑diligence area.
4.3 Real‑world usage and KPIs
We look for:
Named customers or sectors (when publicly disclosed).
Case studies, benchmarks, or outcomes that are backed by data.
Evidence of deployment in regulated environments (e.g., clinical trials, PV operations, GMP labs).
We do not extrapolate; if we cannot find credible evidence, we avoid implying it. Instead, we highlight the absence of public evidence and encourage direct discussions with the vendor.
Many tools in the directory operate in or adjacent to regulated domains (e.g., EU AI Act, MDR/IVDR, FDA frameworks, GxP). We treat regulatory information with particular caution.
When a vendor explicitly states a regulatory status (e.g., “CE‑marked medical device”, “FDA‑cleared”), we repeat this information and clearly attribute it to the vendor.
Where possible, we link to public records (e.g., regulatory databases) or published documentation.
We do not infer regulatory status from marketing language, nor do we label tools as “compliant” on our own authority.
We will never present a tool as “approved”, “compliant”, or “certified” without a clear and verifiable basis, and we will always encourage buyers to confirm regulatory status through official channels.
To avoid blurring the line between marketing claims and independent assessment, we distinguish between:
Vendor‑supplied information
Content directly sourced from vendor websites, product sheets, or materials they provide.
Marked in listings as “Vendor‑supplied” where it is descriptive or promotional.
Independently derived information
Our own classifications (e.g., which part of the value chain the tool supports, category placement).
Our commentary on likely use cases, fit, or risk considerations, based on public information and industry context.
Where we combine vendor content with our own interpretation, we make that explicit. Where important information is missing or unclear, we say so rather than filling gaps with assumptions.
HealthyData.Science may offer paid services such as enhanced listings, sponsored content, or affiliate partnerships. These relationships never change our underlying evaluation framework.
Any sponsored or enhanced content is clearly labelled as such.
Paid relationships do not guarantee inclusion in the directory, nor do they exempt tools from our standard editorial process.
We do not sell rankings or “best tool” labels.
If a commercial relationship could reasonably be perceived as a conflict of interest, we will disclose it in the relevant listing or page.
AI tools and regulations change quickly, especially in healthcare and life sciences. To maintain trust:
Each listing shows a “Last reviewed” date indicating when we last verified its core information.
High‑impact tools (e.g., widely used in clinical, PV, or GxP contexts) are prioritised for more frequent review where possible.
When we make significant changes (e.g., regulatory status updates, major repositioning), we aim to reflect this in the listing and, where appropriate, in our blog or LinkedIn content.
We cannot guarantee real‑time updates, so we strongly encourage buyers to treat our information as a starting point and confirm critical details directly with vendors.
Trust improves when errors are acknowledged and corrected transparently.
If you spot an inaccuracy or missing context, we welcome corrections via our contact form or email.
Where your feedback leads to a material change in a listing, we will update the entry and, where appropriate, note that a correction was made.
We may ask for supporting references or documentation before making changes to critical fields (e.g., regulatory status).
Over time, this feedback loop helps the directory remain a more reliable resource for the community.
HealthyData.Science is primarily intended for:
Decision‑makers in pharma, biotech, medtech, and healthcare (e.g., R&D, clinical, PV, quality, IT, and digital teams).
Evaluators and implementers of AI solutions in regulated environments.
Researchers and consultants working at the intersection of AI, regulation, and evidence.
Our content is not designed for patients or the general public, and it should not be used as medical advice.
If you are in a clinical or regulatory role, please treat our content as a high‑level guide and always apply your organisation’s policies, regulatory obligations, and professional judgement.
To make responsible use of HealthyData.Science:
Treat our listings as a structured overview and a list of questions to take into deeper evaluation.
Use our categorisation and commentary to shortlist tools, then engage your internal stakeholders (e.g., regulatory, QA, IT) before piloting or procuring.
Where a tool appears promising but key information is missing, regard that as a prompt for additional due diligence – not as a green light.
If you need more context on how to interpret a listing in your specific setting, consider using our contact channels; while we cannot give legal or clinical advice, we may be able to point you to relevant resources.
