Pharmaceutical and medical device manufacturing: digitalisation opportunities
Connecting planning, execution, quality, traceability and equipment data for medicines, biological products, medical devices and other regulated health products into a single managed manufacturing system.
Digital maturity
medium
Skaitmenizacijos potencialas
88/100
Biggest challenge
Quality control is separated from the production process
Biggest opportunity
Deviation and CAPA investigation data platform
Pharmaceutical and medical product manufacturing digitalisation should begin with a clear economic problem and one traceable data chain, rather than a general goal to 'implement MES' or collect as many equipment signals as possible.
How pharmaceutical and medical device manufacturing works
The business area covers the manufacture of pharmaceuticals, biological products, medical devices and other regulated healthcare products—from raw materials and component preparation to production, quality assurance, packaging, warehousing and dispatch.
The importance of product and process versioning
These data areas – approved formulas, master production records, material batches, methods, equipment, electronic signatures, deviations and validation evidence – must be managed as valid information, not freely copied files.
The link between physical and digital processes
Systems must reflect the actual state of facilities, including production lines, clean rooms, laboratory equipment, environmental monitoring and serialisation systems, as well as materials, operator actions and time.
The economics of exceptions
The greatest losses in pharmaceutical and medical device manufacturing arise from defects, rejects, failures, changes and quality waiting time, not from the ideal standard cycle.
The need for traceability and accountability
Solutions must be based on primary data and comply with GMP, data integrity, electronic records, validation and patient safety requirements.
Market and technology context
The FDA advanced manufacturing programme in 2025–2026 continues to support the deployment of innovative pharmaceutical manufacturing technologies; at the same time, risk-based quality management, model reliability and early regulatory dialogue are emphasised.
Product data and traceability pressureClients and oversight processes expect rapid provision of approved formulae, master batch records, material batches, methods, equipment, electronic signatures, deviations and validation evidence, and their linkage to actual production.
Skills shortageDigital instructions and decision history help retain material control, manufacturing, environmental and process monitoring, laboratory, release, packaging and serialisation knowledge within the organisation.
Raw material, energy and capacity costsManufacturing needs to see costs and losses at the level of product, batch and production line, clean room, laboratory equipment, environmental monitoring and serialisation system.
Advanced analytics maturityAI and forecasting become practical only when electronic batch record, laboratory results, deviations, CAPA and quality unit release decision are linked to reliable process context.
Typical value chain
01
Technology transfer and master data
Approved formulas, master records, methods, specifications, equipment and validation status.
02
Material and equipment readiness
Raw material release, equipment qualification, cleaning status and environmental conditions are verified.
03
Production execution is controlled
Operator actions, process parameters, electronic signatures and exceptions are recorded in an auditable environment.
04
Laboratory and deviations
Samples, results, unusual events and investigations are linked to a specific batch and process stage.
05
Batch review and release
The quality unit evaluates the complete record, deviations, CAPA and specification compliance.
06
Changes and continuous verification
Changes to process, system or method are managed through risk assessment, validation and monitoring KPIs.
Digital maturity pathway
0
Fragmented product and production data
Approved formulae, master batch records, material batches, methods, equipment, electronic signatures, deviations and validation evidence are kept in spreadsheets, documents and separate systems, and actual execution is verified after shift or batch.
1
Basic business systems
ERP manages orders and inventory, but material control, manufacturing, environmental and process monitoring, laboratory, release, packaging and serialisation and quality facts remain on paper or in local tools.
2
Digitalised selected process
On one line or product family, the single-product deviation investigation process or one portion of the electronic batch record is digitalised with clear validation boundaries, but integrations and common classifiers are still limited.
3
Integrated product and execution chain Typical current situation
Approved product and process information is linked to the plan, operator work, quality results and actual cost. Key managed areas: approved formulas, master batch records, material batches, methods, equipment, electronic signatures, deviations and validation evidence.
4
Data-driven manufacturing Siektina
Planning, quality and maintenance in pharmaceutical and medical device manufacturing rely on real-time exceptions, root cause analysis and reliable line and product KPIs.
5
Adaptive and closed-loop manufacturing
The system in pharmaceutical and medical device manufacturing automatically adjusts permissible solutions based on product, process and equipment status, whilst AI recommendations are audited and measured.
Key conclusion
Pharmaceutical and medical product manufacturing has very high digitalisation potential, but value is created not by yet another separate system, but by reliable connection between product version, plan, actual execution and quality.
Recommended starting point – a single product deviation investigation process or one part of an electronic batch record with clear validation boundaries. Such scope allows measuring results without involving all lines and integrations at once.
Related digitalisation topics
Manufacturing execution systemAdvanced production planningManufacturing traceabilityPredictive equipment maintenance
Problemos
Most common digitalisation challenges
The largest gaps occur when master formulae, master production records, material batches, methods, equipment status, electronic signatures, deviations and validation evidence are managed in separate systems. Raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation processes then fail to provide a single reliable actual history, meaning that plan, execution status and quality decisions reflect different situations.
Quality control is separated from the production process
Critical
Electronic batch record data, laboratory results, deviations, CAPA and release decisions are not consistently linked to a specific product or batch version, operation, equipment and cause of deviation.
Consequences
Quality decision-making takes longer, root cause is harder to establish, and batch review delays, repeated deviations, record corrections, additional investigations and validation change duration may recur in other orders.
Weak batch and component traceability
Critical
It is not always possible to quickly reconstruct the complete chain: formula, material batches, equipment, methods, electronic signatures, deviations and validation evidence.
Consequences
In pharmaceutical and medical device manufacturing, during a customer enquiry, audit, non-conformance or recall, it takes a long time to determine the affected scope and required action.
The electronic batch record is not seamless
Critical
Manufacturing, equipment, environmental, laboratory, materials and deviation records are collected in multiple validated and non-validated systems.
Consequences
Batch review is lengthy, data integrity risk is high and it is difficult to automate release.
Fragmented production master data
High
Master formulae, master production records, material batches, methods, equipment status, electronic signatures, deviations and validation evidence are stored in different systems, files or employee-prepared spreadsheets, meaning there is no single valid product and production version.
Consequences
Changes to raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation processes arrive at different times, increasing manual checks and the risk of manufacturing based on outdated information.
Planning does not reflect actual production constraints
High
Plans do not always take into account validated equipment status, cleaning campaigns, material release, laboratory and qualified staff capacity and the actual status of work already started.
Consequences
Priorities are changed at the last minute, increasing waiting time, work in progress and the proportion of delayed orders in pharmaceutical and medical device manufacturing.
Production execution data is captured with a delay
High
In the process of investigating a deviation or electronic batch record for a selected product, operation start and finish, quantities produced, material consumption, stoppages and reasons for deviations are recorded with a delay or in multiple locations.
Consequences
Planners and responsible personnel see too late that the process of investigating a deviation or electronic batch record for a selected product has deviated from plan, losing time for correction.
Deviation investigations rely on manual data collection
High
The investigator manually collects process, equipment, laboratory, materials and previous event data.
Consequences
Investigations take a long time, root causes are determined inconsistently and batch release is delayed.
System and model validation is slow and document-intensive
High
Requirements, risks, tests, evidence, changes and periodic reviews are managed with a large volume of manual documentation.
Consequences
Technology deployment is slow and the cost of documenting changes is high.
Monitoring is mostly reactive
Medium
Data on production line, cleanroom, laboratory equipment, environmental monitoring and serialisation system uptime, failures, condition signals, spare parts and maintenance work is not aligned with actual load and production schedule.
Consequences
Unplanned stoppages disrupt the deviation investigation or electronic batch record process for the selected product, whilst maintenance and spare parts needs are managed on an urgent basis.
Opportunities
Greatest digitalisation opportunities
Deviation and CAPA investigation data platformVery high impactAutomatically collect related records, similar events and process context for the investigator.Faster and more consistent investigations
Electronic batch record and review by exceptionVery high impactConnect all critical batch data and automatically highlight only non-conformances and incomplete approvals.Faster release and data integrity
Digital validation lifecycleHigh impactLink requirements, risks, tests, evidence, changes and periodic reviews.Faster compliant technology deployment
Integrated quality and traceabilityVery high impactLink specification, batch, process parameters, checks, deviations and final product.Less waste and faster investigations
Integrated manufacturing execution managementVery high impactIn a selected flow, link formula, material batches, equipment, methods, electronic signatures, deviations and validation evidence with actual quantities, stoppages, deviation root causes and responsible worker actions.Performance and delivery reliability
Constraint-based planning and replanningVery high impactPlan according to actual capacities, changeovers, materials, tools, quality and deadlines.Capacity utilisation and shorter cycle
Data-driven equipment maintenanceHigh impactConnect failures, sensors, operating hours, spare parts and maintenance schedules.Less downtime
Energy, yield and waste optimisationHigh impactMeasure energy, material consumption and batch review waiting time, repeated deviations, record corrections, additional investigations and validation change duration at product, batch or serial unit level, so that the causes of losses are visible where they occur.Cost and sustainability
Biggest opportunity
Deviation and CAPA investigation data platform
The greatest near-term opportunity is a single-product deviation investigation process or one electronic batch record section with clear validation boundaries.
Higher utilisation of equipment and labour capacity
Less scrap and unplanned downtime
Shorter production cycle
Better traceability of batches and components
Potential business impact
Capacity utilisationA more accurate plan and real-time execution status of validated equipment condition, cleaning campaigns, material release, laboratory and qualified staff capacity reduces waiting and urgent priority changes.
Quality and yieldQuality status becomes visible during the process as the following data and decisions are linked: electronic batch record, laboratory results, deviations, CAPA and quality unit release decision. This reduces late scrap, rework and raw material losses.
Delivery reliabilityOrder deadline is assessed based on actual raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation and material status, rather than periodic reporting.
Traceability and riskA reliable chain between approved formula, master batch records, material batches, methods, equipment, electronic signatures, deviations and validation evidence enables faster response to audit, complaint or recall scenarios.
Scale and knowledge preservationDigital instructions and decision history in pharmaceutical and medical device manufacturing reduce dependency on individual specialists' memory.
Sprendimai
How to solve these problems
Solution directions linked to specific business area problems they address.
Problema
Manufacturing execution data collected late
→
Sprendimo kryptis
Manufacturing execution system (MES)
Manages raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation tasks, validated product version, actual quantities, time, materials, stoppages and exceptions in one selected flow.
Problema
Planning does not reflect actual production constraints
Priorities are changed at the last minute, increasing waiting time, work in progress and the proportion of delayed orders in pharmaceutical and medical device manufacturing.
→
Sprendimo kryptis
Manufacturing execution system (MES)
Manages raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation tasks, validated product version, actual quantities, time, materials, stoppages and exceptions in one selected flow.
Problema
Planning does not reflect actual production constraints
Priorities are changed at the last minute, increasing waiting time, work in progress and the proportion of delayed orders in pharmaceutical and medical device manufacturing.
→
Sprendimo kryptis
Advanced planning and scheduling system
Creates and adjusts the plan according to validated equipment status, cleaning campaigns, material release, laboratory and qualified employee capacity, actual material status and current production exceptions.
Problema
Quality control separated from production process
→
Sprendimo kryptis
Quality and traceability platform
Links electronic batch record, laboratory results, deviations, CAPA and quality unit release decision to approved product version, actual materials, operations, equipment and final product.
Problema
Weak batch and component traceability
In pharmaceutical and medical device manufacturing, during a customer enquiry, audit, non-conformance or recall, it takes a long time to determine the affected scope and required action.
→
Sprendimo kryptis
Quality and traceability platform
Links electronic batch record, laboratory results, deviations, CAPA and quality unit release decision to approved product version, actual materials, operations, equipment and final product.
Problema
Maintenance mostly reactive
→
Sprendimo kryptis
Equipment maintenance and reliability system
Manages equipment register covering production line, clean room, laboratory equipment, environmental monitoring and serialisation systems, planned maintenance, failures, spare parts and status signals with production context.
Recommended digital solutions
The solution portfolio must be formed around a single product deviation investigation process or one part of the electronic batch record with clear validation boundaries, rather than from a pre-selected technology or a whole factory transformation.
Manufacturing execution system (MES)
Manages raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation tasks, validated product version, actual quantities, time, materials, stoppages and exceptions in one selected flow.
Advanced planning and scheduling system
Creates and adjusts the plan according to validated equipment status, cleaning campaigns, material release, laboratory and qualified employee capacity, actual material status and current production exceptions.
Quality and traceability platform
Links electronic batch record, laboratory results, deviations, CAPA and quality unit release decision to approved product version, actual materials, operations, equipment and final product.
Equipment maintenance and reliability system
Manages equipment register covering production line, clean room, laboratory equipment, environmental monitoring and serialisation systems, planned maintenance, failures, spare parts and status signals with production context.
Production master data and change management
Manages master data set and its versions, release, validity and change impact on production. Key areas: approved formulas, master batch records, material batches, methods, equipment, electronic signatures, deviations and validation evidence.
Electronic batch record and review platform
Connects formulation, materials, equipment, operators, process parameters, environment, laboratory, deviations and electronic signatures.
Deviation, CAPA and quality events management system
Manages event registration, related data collection, root cause analysis, actions, effectiveness verification and trends.
The data set in these areas – approved formulae, master batch records, material batches, methods, equipment, electronic signatures, deviations and validation evidence – has multiple versions or is frequently corrected manually
Raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation facts are recorded after the shift or batch
For a quality investigation, it is difficult to link the electronic batch record, laboratory results, deviations, CAPA and quality unit release decision to a specific batch, product or equipment
The costs of scrap, downtime, waiting or non-traceability in pharmaceutical and medical device manufacturing are significant
A clear scenario can be selected: a deviation investigation process for a single product or a portion of the electronic batch record with clear validation boundaries
Reikia atsargumo
It is unclear which problem has the greatest business impact
There are no approved product and process versions
Equipment data is collected without product or batch context
The first version is planned for the entire factory at once
Recommended first version
The first version is a single product deviation investigation process or one part of an electronic batch record with clear validation boundaries. It must include approved master data, one real execution flow, a quality decision and a measurable economic result.
Approved work order and product version
The user receives only valid approved formulae, master production records, material batches, methods, equipment, electronic signatures, deviations and validation evidence, and a clear operation and quality task.
Actual execution recording
Quantities, time, materials used, raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation status, stoppages and exceptions are recorded.
Integrated quality and traceability control
Quality data and decisions—electronic batch record, laboratory results, deviations, CAPA and quality unit release decision—are linked to product, batch, equipment and operation.
Exceptions and results dashboard
Managers see not a general report, but delayed, missing or risky single product deviation investigation process or one part of an electronic batch record with clear validation boundaries statuses.
Kam pirmiausiaProduction operators or process executors · Shift or production managers · Planners and technologists · Quality specialists · Maintenance or engineering team
What not to include in the first versionEntire factory and all products scope · Full integration of all legacy equipment · Complex autonomous AI optimisation · Historical data cleaning without a clear use scenario
Investment priorities
Data platform for deviations and CAPA investigationsStart with a single product deviation investigation process or one part of the electronic batch record with clear validation boundaries and measure the economic result before scaling up.
Electronic batch record and review by exceptionConnect quality information – electronic batch record, laboratory results, deviations, CAPA and quality unit release decision – with the actual product, batch and process history.
Digital validation lifecycleOnly after stabilising the first flow, expand planning, production line, cleanroom, laboratory equipment, environmental monitoring and serialisation system integrations and advanced analytics.
Key implementation conditions
Clear primary data system
There must be agreement on which system stores the valid information in areas such as approved formulas, master production records, material batches, methods, equipment, electronic signatures, deviations and validation evidence, and how changes reach production.
IT and production automation boundaries
Production lines, clean rooms, laboratory equipment, environmental monitoring and serialisation systems integration must be designed without compromising the security of control networks, equipment warranties and production continuity.
Contextual actual data
Every measurement or operator action in pharmaceutical and medical products manufacturing must be linked to product, batch, operation, facility and time; a signal archive alone creates no value.
Workstation, not an additional report
The operator or specialist must receive only the information required for their decision, and recording must be incorporated into the raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation workflow.
Managed change and accountability
Process owners must approve decisions concerning versions, exceptions and GMP, data integrity, electronic records, validation and patient safety requirements; the technology team cannot define business rules alone.
Recommended implementation sequence
01
Economic challenges and boundary selection
Select a single product deviation investigation process or a clearly bounded part of the electronic batch record and agree on which loss and KPIs the first version should impact.
Baseline KPIs and economic hypothesis
Selected product family or line
Process owners and decision boundaries
02
Master data and identifier preparation
Organise approved formulae, master production records, material batches, methods, equipment states, electronic signatures, deviations and validation evidence, and define uniform product, batch or serial number, operation and equipment identifiers.
Approved data owners
Versioning and validity rules
Integration and audit requirements
03
One seamless digital process
Implement a single product deviation investigation process or a clearly bounded part of the electronic batch record from approved initial information to actual result, quality decision and audit history.
Operator or specialist workstation
Actual data recording
Quality, status and exception management
04
Usage stabilisation
Launch the solution in the selected product deviation investigation or electronic batch record process, eliminate parallel records and verify data and KPI reliability.
Training and work standard
Data quality monitoring
Measured impact on KPIs
05
Expansion and advanced analytics
Only after stable use expand the solution to other product groups, batch records and laboratory processes and connect more advanced analytics or AI scenarios.
Repeatable implementation model
Portfolio or factory analytics
Forecasting and optimisation scenarios
Change measurement KPIs
Manufacturing plan execution on time% of orders or operations
Measure what proportion of planned orders or operations are executed on time when the plan accounts for validated equipment status, cleaning campaigns, material release, laboratory and qualified staff capacity.
First-time-right production proportion% of units or batches
Measure the proportion of production for which electronic batch record data, laboratory results, deviations, CAPA and release decisions are confirmed without correction, rework or additional investigation.
Unplanned downtime durationhrs
Assess the reliability of critical production lines, clean rooms, laboratory equipment, environmental monitoring and serialisation systems and the outcome of response to unplanned stoppage.
Proportion of fully traceable batches or units% of production
Measure whether formula, material batches, equipment, methods, electronic signatures, deviations and validation evidence are linked in a single reliable history.
Manufacturing cycle timehrs or days
Measure the time from production start to finished and quality-released product for a selected product's deviation investigation or electronic batch record process.
Actual and planned cost variance% or € per unit
Assess whether actual labour time, materials, scrap, energy and other direct costs are reliably attributed to formula, material batches, equipment, methods, electronic signatures, deviations and validation evidence.
Deviation investigation and batch review durationdays
Measure the time from deviation registration to completion of confirmed root cause, CAPA and batch review.
Key risks
Digitalising an undefined processIf the rules and exceptions applicable to raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation processes are unclear, the system will only cement different employee practices.Kaip suvaldyti Before development, observe actual work, describe the most common exceptions and confirm decision rights.
Product and production versions do not matchApproved formulae, batch records, material batches, methods, equipment statuses, electronic signatures, deviations and validation evidence can be changed at different times, so production risks receiving invalid or mutually inconsistent information.Kaip suvaldyti Pharmaceutical and medical device manufacturing use identical identifiers, effective dates and approval statuses; an unapproved version must not be transferred to production.
Equipment data collected without contextA high volume of signals from production lines, cleanrooms, laboratory equipment, environmental monitoring and serialisation systems does not help explain the outcome if the data are not linked to the product, batch or serial number, operation and specific time.Kaip suvaldyti Assign in advance to data from production lines, cleanrooms, laboratory equipment, environmental monitoring and serialisation systems a specific solution, KPI, responsible person and product, batch or serial number context.
First version covers too muchAn attempt to immediately cover all lines, products and GMP, data integrity, electronic records, validation and patient safety scenarios delays actual use and makes it difficult to evaluate the outcome.Kaip suvaldyti Limit the first version to one product deviation investigation process or a clearly bounded part of the electronic batch record.
Users bypass the systemIf the new workplace slows down raw material control, production, environmental and process monitoring, laboratory, release, packaging and serialisation processes or does not help resolve exceptions, employees will continue to fill in paper or spreadsheets after the fact.Kaip suvaldyti Design the workplace together with production, quality assurance, laboratory, validation, engineering and IT teams, measure registration time and remove duplicate forms only after stable go-live.
Inovacijos
Digital innovation in the business area
Advanced technologies in pharmaceutical and medical device manufacturing must be based on reliable product, batch and process data; otherwise they merely automate unclear decision-making logic.
Exception-based batch review
Relevant
The system automatically highlights missing, out-of-specification or mutually inconsistent records.
How it is applied The quality specialist reviews high-risk areas rather than the entire uniform volume of documentation.
What value can be created
Faster release
Less manual review
What is needed for this to work
Controlled electronic data
Approved rules
Medium-termPilot projects
Source-based deviation investigation assistant
Relevant
AI collects related batches, equipment signals, laboratory results and previous events.
How it is applied Used to accelerate investigator work whilst preserving references to original records.
What value can be created
Faster investigation
More consistent analysis
What is needed for this to work
Controlled access
Structured cause categories
Medium-termPilot projects
Advanced process analytics
Relevant
Process and laboratory data are used to assess the state of critical quality attributes.
How it is applied Suitable for processes with sufficient reliable historical data and clear control limits.
What value can be created
Earlier deviation detection
More stable process
What is needed for this to work
Validated data flows
Risk-based model management
Medium-termPilot projects
Digital validation evidence management
Relevant
Requirements, risks, tests, deviations and approvals are linked in a single auditable chain.
How it is applied Helps manage frequent system changes without growing documentation chaos.
What value can be created
Shorter change cycle
Better traceability
What is needed for this to work
Clear system inventory
Validated lifecycle
Medium-termPilot projects
D.U.K.
Frequently asked questions
Where is the safest place to start pharmaceutical manufacturing digitalisation?
Often a safer start is not a full electronic batch record, but one clear problem: deviation investigation data collection, equipment logs or a selected section of the batch record. The scope must be manageable and agreed in advance with the validation strategy.
How does an electronic batch record differ from a scanned PDF?
An electronic batch record controls data, sequence, permissible values, electronic signatures, audit history and exceptions. A scanned document merely replaces the medium, but does not create a controlled process.
Is MES essential for every pharmaceutical manufacturer?
Not always. The solution depends on product risk, batch volumes, existing systems and review costs. In some cases, LIMS, QMS, electronic logs or a deviation investigation platform create more value first.
How should data integrity be managed across multiple systems?
Clear primary data sources, synchronised time, immutable audit history, controlled access and documented data transfer are required. A report must not replace the primary record.
Where can AI be used without compromising quality accountability?
AI can help search for previous deviations, group signals and prepare source-based investigation material. The final cause, CAPA and batch release must remain the decisions of responsible specialists.
Which KPIs demonstrate the benefit of digitalisation?
Key indicators include batch review time, deviation investigation duration, number of record corrections, waiting time between manufacturing and release, proportion of repeated deviations and validation change cycle.
Next step
Shorten deviation investigation without losing control
An assessment should be made of whether it is best to begin the first stage with a deviation investigation process for a single product or a clearly bounded section of the electronic batch record, and what change in quality, time, cost or traceability can be reliably measured.
