ServiceNow Discovery for Life Sciences and Pharma

At a life sciences site, Discovery finds the laboratory, manufacturing and quality systems that are connected to the network and records their hosts, connections and observable configuration. The scan boundary is agreed with the validation owners before the first probe, so the scan does not change a validated system.

Laboratory Equipment and Scientific Infrastructure

Pharmaceutical and biotech research relies on sophisticated laboratory equipment: mass spectrometers, chromatography systems, sequencers, and thermal cyclers. Each instrument connects to data management systems, requires calibration, and must maintain regulatory compliance. Tracking equipment inventory, utilisation, and maintenance is essential.

Discovery maps laboratory equipment and connected systems. It identifies which instruments are installed at which facilities, their observable configuration, and the software and network connections each instrument reports through. When equipment maintenance is needed or performance degrades, Discovery provides history of that instrument’s configuration and use patterns, supporting troubleshooting and root cause analysis.

Clinical Trial and Patient Data Systems

Clinical research involves complex systems: electronic data capture systems for clinical trials, electronic patient records in clinical environments, and trial management systems. These systems must maintain data integrity, support regulatory audits, and protect patient privacy.

Discovery maps clinical systems, patient data repositories, trial management infrastructure, and connections between systems. This Discovery shows which hosts and connections hold clinical data, and the compliance owner checks access rules and configuration against the regulations separately like 21 CFR Part 11 for electronic records and the Common Rule for human subjects research. Discovery also identifies systems that should be segregated but aren’t, creating compliance risk.

Manufacturing and Batch Control Systems

Pharmaceutical manufacturing operates under strict regulations. Batch records must be maintained, equipment must be qualified, and environmental monitoring must track cleanroom conditions. Manufacturing execution systems coordinate production and track batch genealogy.

Discovery maps manufacturing infrastructure: manufacturing equipment, batch control systems, environmental monitoring systems, and data management infrastructure. It identifies which systems are connected, in what order product flows through equipment, and where batch data is recorded and archived. This supports regulatory compliance audits and helps investigate quality issues by tracing product through manufacturing steps.

Quality and Compliance Management Systems

Quality systems track deviations, corrective actions, change controls, and audit findings. A deviation might be detected in laboratory testing, triggering investigation and corrective action. Quality systems must integrate with manufacturing systems to investigate root causes affecting product.

Discovery maps quality and compliance infrastructure: quality management systems, document control systems, audit tracking systems, and investigations databases. This reveals how quality systems are connected and whether investigation data flows correctly from quality to manufacturing when issues are detected.

Regulatory Submission and Document Management

Bringing new drugs and treatments to market requires extensive regulatory documentation. Regulatory information management systems track drug development, clinical trial results, and manufacturing information required for regulatory submissions. Document control must ensure versions are managed and submission records are maintained.

Discovery maps regulatory information management systems, document control infrastructure, and submission databases. This supports audit trails required by regulators and helps investigators trace documentation for specific products or regulatory submissions.

Supply Chain and Material Tracking

Pharmaceutical supply chains are complex and regulated. Raw materials must be tracked from supplier through manufacturing to finished products. Supply chain disruptions impact clinical research and patient access to therapies.

Discovery maps supply chain infrastructure: material management systems, supplier quality systems, and logistics tracking. This reveals bottlenecks in material flow and supports traceability from raw material receipt through finished product distribution.

Common Discovery Challenges in Life Sciences

A frequent issue is isolated systems maintained by equipment vendors. Laboratory equipment manufacturers often maintain proprietary software for instrument operation and data management. Discovery works well for standard IT infrastructure but may miss vendor-maintained systems that don’t expose configuration via standard protocols.

Another challenge is the volume and complexity of documentation. Regulatory submissions include thousands of documents; quality systems maintain records spanning years. Discovery can identify document management infrastructure but cannot easily audit document completeness or compliance with retention requirements.

Legacy systems in regulated environments create a third challenge. Older laboratory information management systems or manufacturing execution systems may use proprietary protocols or closed architectures. Upgrading these systems is risky because of regulatory validation requirements, so they persist for years, complicating discovery and integration planning.

Checklist for Life Sciences Discovery

• Map laboratory equipment and connected data management systems
• Identify calibration schedules and maintenance records for instruments
• Audit clinical trial and patient data systems for segregation and access controls
• Map manufacturing equipment, batch control systems, and environmental monitoring
• Verify that quality systems integrate with manufacturing systems for deviation investigation
• Audit regulatory information management and document control systems
• Trace material flow from supplier through manufacturing to finished product
• Create exclusion lists for vendor-maintained systems requiring custom integration or API access

Setting the scan boundary before the first probe leaves the network

Discovery is useful in a laboratory only when it finds what is actually there without changing what it finds. The boundary of the first scan is therefore a validation and safety decision as much as an IT one. Some instruments have controllers with very limited capacity, and a burst of probes can freeze a sequencer mid-run. Some manufacturing systems were qualified in a configuration that an active scan could alter. The site should decide which segments may be probed actively, which may be observed passively, and which stay out of scope entirely, and record that decision before a credential is entered anywhere. The discovery overview explains what the tool records once that boundary is in place.

Sequence for a first scope that the lab will accept

1. Walk the site with the equipment owners and mark each network segment with its validation status and its tolerance for probing. A planning note on choosing a first discovery scope covers the related questions of authority and evidence.
2. Write the exclusion list in plain terms, including the reason for each exclusion, and get the owner’s signature on it.
3. Create a dedicated credential set for the first scan, limited to read-only commands, with a named owner and an expiry review.
4. Run a small first pass against one non-critical segment, and compare the results with the walk-down list.
5. Review the gaps. Anything Discovery missed is either a vendor-maintained system needing a manual record or a scope problem to fix.
6. Widen the scope one segment at a time, keeping a log of what each pass changed or disturbed.

Credential governance in a validated environment

A discovery credential that can read a laboratory data server is an access path into a system that holds regulated records. Treat it accordingly, following the credential governance approach for scanning. Store credentials in a vault rather than a configuration record, restrict who can view them, and tie each credential to the systems it may touch. When a credential is rotated, the change should appear in the change record, because a rotation that breaks the scan is also a change to a validated system’s access. Review the credential list on a fixed schedule and remove those for systems that have been retired.

Finding the systems discovery cannot see

Vendor-maintained laboratory software is often a blind spot. Where the gap sits between discovered hosts and the services they carry, the discovery and service mapping work is the place to design the mapping. Some instrument suites run their own database and expose little through standard protocols. Discovery will show the host, but not the instrument configuration that matters for a validated process. The practical response is a short list of exceptions, each with an owner, a record maintained by hand or through the vendor’s interface, and a review at each change. Without that list, the database looks complete while the highest-risk systems are missing from it.

How to tell discovery is producing usable records

• Scan results for a segment match the walk-down list within an agreed tolerance, and each gap is explained rather than ignored.
• Each discovered host has an owner, and the owner can confirm its purpose within a short review.
• Duplicate records from discovery and from the laboratory system are caught by reconciliation rather than by a user noticing a strange count.
• No scan has triggered an alarm, a recalibration request or a controller reset that the site had to explain afterwards.

When discovery should wait

If the site has not yet agreed which systems are validated, or if the walk-down has never been done, a scan will produce a large list of hosts with no meaning. In that case build the inventory by hand for the regulated segments first, then use discovery to confirm and extend it. Starting with a broad scan on a site that has no exclusion list is a common reason first runs cause incidents.

Questions about discovery in laboratories and plants

Can discovery run during a production campaign?

Only on segments the owner has agreed can be probed at that time, and the scheduling rules for that are set in the discovery schedule definition. For anything on a production or instrument network, the default answer during a campaign should be no, with the scan rescheduled to a planned window.

Should discovery map the contents of clinical databases?

No. Mapping the hosts, the connections and the hosting arrangements answers the configuration question. Reading contents adds privacy exposure and rarely improves the record. Where content matters, the owner should supply it under the agreed data handling rules.

How often should the exclusion list be reviewed?

Review it at each significant change to the laboratory or manufacturing network, and whenever a new instrument is added. An exclusion list written once and never reviewed becomes a blind spot.

What is the difference between discovery and a manual inventory?

Discovery finds what is connected and reports its observable configuration. A manual inventory records what the owner knows about a system, including what cannot be observed. In a regulated environment you usually need both, with the discovered view checked against the manual one.