Secure data transfer in biotech means getting sensitive files, such as sequencing runs, structures, screening results and proprietary compound data, between labs, partners and compute without anyone unauthorized being able to read, alter or intercept them, and being able to prove it afterward. That takes four things working together: encryption in transit and at rest, tight access control, an audit trail, and clear contracts that say who is responsible for what. The tool you pick matters less than whether those four are in place and documented.
This guide is written for R&D leads, IT and security staff, and project managers at biotech and pharma companies who are about to send data to a collaborator, a CRO or a computational partner. It covers what the main US rules and frameworks require, how to split duties with a cloud provider, and a checklist you can apply before the next transfer.
TL;DR
- Encrypt data in transit and at rest, and keep control of the encryption keys. Ownership of the keys decides who can actually read your files.
- Give each person and system access only to the specific resources they need, and log every access. NIST recommends a zero trust approach for genomic data.
- Regulated data brings regulated duties: HIPAA for patient-linked data, 21 CFR Part 11 for electronic records tied to FDA requirements.
- Using a cloud provider does not hand off your compliance duties. Write the split of responsibilities into the contract before any data moves.
- Before sharing proprietary sequences or compounds with a service partner, confirm the NDA, the access model and the deletion terms in writing.
Table of Contents
- What counts as sensitive data in a biotech transfer
- The rules that shape a US transfer
- What a secure transfer looks like, step by step
- Cloud bioinformatics: splitting the responsibility
- Sharing data with outside partners
- Our perspective
- Where our services fit
- A pre-transfer checklist
- FAQ
- Sources
What counts as sensitive data in a biotech transfer
Not every file carries the same risk, and treating them all the same either slows your science or leaves gaps. In practice, biotech teams move four broad kinds of data:
- Genomic and sequencing data. Large, long-lived and hard to anonymize. NIST describes genomic data as having properties that, in combination, make it different from most other data types, and as valuable to individuals, industry and government alike.
- Patient-linked data. Clinical, phenotype and sample metadata that may count as electronic protected health information (ePHI).
- Regulated records. Data that supports an FDA submission or must be kept under FDA rules.
- Proprietary discovery data. Target structures, compound libraries, screening hits, peptide and enzyme sequences, and optimization results. No regulator may care, but your competitive position depends on it.
The last category is the one teams most often under-protect. A virtual screening campaign or a protein design project can reveal your target, your chemistry and your strategy in a few files. Classify before you transfer: decide which bucket the data is in, because the bucket sets the rules.
The rules that shape a US transfer
Three sources do most of the work for US biotech teams. Which ones apply depends on your data.
HIPAA Security Rule
If your data includes ePHI, the HIPAA Security Rule requires administrative, physical and technical safeguards for ePHI that is created, received, maintained or transmitted electronically. Encryption of transmitted ePHI is an "addressable" specification: you assess the risk, and where transmission over the internet creates significant risk, encryption needs to be implemented. Addressable does not mean optional, and the risk analysis behind your decision should be written down.
HHS also publishes a technical safeguards guide that explains access control, audit controls, integrity and transmission security in plain terms. It is a good starting point for an internal review.
If you are choosing infrastructure for this kind of data, our buyer's guide to HIPAA compliant cloud providers goes deeper on what to ask vendors.
21 CFR Part 11
When records fall under FDA requirements, FDA's Part 11 guidance applies to electronic records that are created, modified, maintained, archived, retrieved or transmitted. Systems need procedures and controls, such as audit trails and logical security, that protect the authenticity, integrity and confidentiality of those records.
For transfers, this has a practical meaning: a file that arrives is not enough. You need to show it arrived unchanged, from whom, when, and who touched it. If your analysis pipelines produce records that fall under Part 11, see our 8 pipeline checks for 21 CFR Part 11 in bioinformatics.
NIST guidance for genomic data
NIST's Cybersecurity Framework is a voluntary approach to risk management, and NIST's work on genomic data applies it to biotechnology. The NIST report on cybersecurity of genomic data encourages stakeholders to adopt a Zero Trust Architecture (NIST SP 800-207). The idea: no implicit trust based on network location, and only authenticated users and assets can reach the specific resources they need for their mission. That limits both unauthorized exfiltration and lateral movement inside your network.
The same report points to Cybersecurity Framework Profiles tailored to a mission such as R&D or manufacturing, so that controls are standardized and upgrades go first to the highest-value data environments. NIST has also published a draft community profile for genomic data cybersecurity and privacy, worth reading if you want a ready structure for your own profile.
What a secure transfer looks like, step by step
The following sequence works for most project handoffs, whether you send data to a CRO, a core facility or a computational partner.
- Classify the data. Decide whether it holds ePHI, Part 11 records, or proprietary discovery data. Write the classification on the transfer request.
- Minimize. Send only what the work needs. A docking campaign needs the target structure and the library, not your whole program folder. De-identify or strip metadata when you can.
- Choose an encrypted channel. Use a protocol that encrypts in transit, and encrypt files at rest on both ends. Avoid email attachments and consumer file-sharing links for anything sensitive.
- Authenticate every person. Individual accounts, multifactor authentication and no shared logins. Shared credentials destroy your audit trail.
- Grant least access. Give access to the specific folder or dataset, for a set period. This is the zero trust principle applied to a single project.
- Verify integrity. Compare checksums before and after transfer so you can show the files were not altered or truncated.
- Log and review. Keep a record of who accessed what and when, and look at it. Logs nobody reads do not protect you.
- Close out. At project end, revoke access, return or delete data as the contract says, and document the deletion.
Who holds the keys
Encryption is only as strong as control of the keys. If a provider stores your data encrypted but holds the keys, they can in principle decrypt it. If you hold the keys, the provider sees only ciphertext. For proprietary compounds and sequences, that is a meaningful difference, so ask directly where keys are generated, who holds them, and how they are rotated and destroyed.
Do not forget the instruments
Sequencers and other lab instruments are networked devices, and they often run older software. Securing the files in transit is not enough if the instrument that produces them sits on the same flat network as everything else. Segment instruments from the wider corporate network so a compromised device cannot become a path to your data stores. NIST's genomic data workflow threat modeling work is a useful reference for mapping where data and threats meet in a sequencing workflow.
Cloud bioinformatics: splitting the responsibility
Most computational work now runs in the cloud, and that raises the question every security reviewer asks: if the provider hosts the data, who is responsible for protecting it?
The short answer is both of you, and the contract must say how. HHS guidance on HIPAA and cloud computing explains that when a covered entity engages a cloud provider to create, receive, maintain or transmit ePHI on its behalf, the provider is a business associate under HIPAA. That holds even where the provider only stores encrypted data and cannot see it. In those "no-view" arrangements, responsibilities are shared. The customer typically manages user authentication, while the provider manages infrastructure-level protections. The exact division belongs in a Business Associate Agreement and in both parties' risk management plans.
Even outside HIPAA, the same logic helps. Ask any platform or provider to show you, in writing, how it handles authentication, encryption, incident response and data handling. Public trust pages are a reasonable first filter: this platform's published security page is one example of the kind of disclosure you can ask a vendor to match, though a web page never replaces a signed agreement.
A practical split looks like this:
| Area | Typically you | Typically the provider |
|---|---|---|
| User accounts and MFA | Set up, review, remove | Offer the controls |
| Encryption keys | Decide who holds them | Support your key model |
| Infrastructure security | Verify through documentation | Operate and patch |
| Access logs | Review them | Produce and retain them |
| Incident notification | Define the timeline in contract | Follow it |
| Data deletion | Request and confirm | Perform and attest |
Treat this table as a starting framework for your own contract review, not as a standard. Your agreement decides who does what.
Containers need their own attention
Bioinformatics pipelines often run in containers such as Docker images and Kubernetes pods. NIST notes that generic security tools can miss vulnerabilities in containerized genomic analysis environments, which also drives false positives, so teams need security approaches that understand container orchestration and the data flows of a pipeline. If your analysis partner runs containerized workflows, ask how images are built, scanned and updated, and where intermediate data lands.
Sharing data with outside partners
The riskiest moment is often not the transfer itself but the relationship around it. Before any file moves to a CRO, CDMO, consultant or computational service provider:
- Put a confidentiality agreement in place that covers your sequences, structures, compounds and results, and what happens to derived data. Our guide to U.S. biotech NDA requirements covers five common gaps.
- Define who may see what. Name the individuals or roles, not just the company.
- Agree on communication rules. Which channels carry data, which carry only status updates, and who approves exceptions. Our contract checklist for collaborative research communication can help you draft this.
- Plan the exit. Return, deletion and certification of deletion should be in the contract from day one.
For procurement teams, we also outline three must-haves for secure external collaborations.
Our perspective
We work on the computational side of drug discovery and protein engineering, which means clients send us the data that defines their programs: target structures, compound sets, protein and peptide sequences. From that vantage point, a few things stand out.
First, security failures in collaborations are rarely exotic. They are an unencrypted email, a shared login, a folder nobody closed after the project ended. The fix is process, agreed at the start of the engagement rather than improvised during it.
Second, security and good science pull the same way. A project with a defined data scope, named people and a clear communication plan is also a project that runs faster, because nobody waits on a question about who may see what.
Third, a provider should be able to explain its controls to you in plain language, and you should expect to. Our security and confidentiality page sets out how we approach it, and we keep clients informed with clear updates throughout a project. If a partner cannot tell you how your data is handled from intake to deletion, treat that as an answer.
— Hooman
Where our services fit
If you are planning a computational project and want data handling agreed before anything moves, we can scope it with you. We provide virtual screening and hit-to-lead optimization, protein engineering and chimeric protein design, enzyme optimization and peptide design, each tailored to the project and supported by confidential workflow practices. Start with a conversation through our main site and tell us what data the project involves.
A pre-transfer checklist
Use this before each new project or new partner.
- Data classified: ePHI, Part 11 record, proprietary discovery data, or a mix
- Minimum necessary dataset defined
- Encrypted channel and encryption at rest confirmed on both ends
- Key ownership and rotation understood
- Individual accounts with MFA, no shared credentials
- Access limited by dataset and time period
- Checksums planned for integrity verification
- Audit logs enabled and an owner assigned to review them
- NDA, and where relevant a BAA, signed
- Responsibilities for cloud and infrastructure written into the contract
- Instruments and pipeline environments segmented and scanned
- Deletion and return terms defined, with confirmation required
If you cannot tick a line, that is not a reason to stop every project. It is a reason to write down the risk, assign an owner and decide knowingly.
FAQ
What is secure data transfer?
It is the movement of data between people, systems or organizations in a way that keeps it confidential, unaltered and traceable. In practice that means encryption in transit and at rest, authenticated users, limited access and logs. In regulated settings you must also be able to show those controls worked.
Does encrypting my files satisfy HIPAA?
Not by itself. Under the HIPAA Security Rule, encryption of transmitted ePHI is addressable, so you decide based on a documented risk analysis, and the rule also requires administrative, physical and technical safeguards more broadly. If a cloud provider handles your ePHI, a Business Associate Agreement is needed even when the data is encrypted. Ask your compliance officer or counsel to confirm how this applies to your data.
Is a cloud provider responsible for protecting my data?
Partly. Infrastructure-level protection usually sits with the provider, while user authentication and how you configure access usually sit with you. HHS guidance says this division should be defined in the agreement and supported by both parties' risk management plans.
What should I check before sending proprietary sequences or compounds to a service partner?
Confirm a signed confidentiality agreement, the named people with access, how data is encrypted and who holds the keys, how communications are handled, and what happens to your data at project end. Put the answers in the contract rather than relying on a verbal assurance.
Sources
- NIST IR 8432, Cybersecurity of Genomic Data
- NIST IR 8467 second public draft, Genomic Data Cybersecurity and Privacy Frameworks Community Profile
- NCCoE Genomic Data Project Update
- HHS, Summary of the HIPAA Security Rule
- HHS, HIPAA Security Series #4, Technical Safeguards
- HHS, Guidance on HIPAA and Cloud Computing
- FDA, Part 11, Electronic Records; Electronic Signatures, Scope and Application