9 real-life Business Process Automation examples in Healthcare and Life Sciences
9 real-life Business Process Automation examples in Healthcare and Life Sciences
Automation within healthcare and life sciences needs to account for patient safety, clinical quality, privacy, and heavily regulated records.
The examples in hospitals and clinics show that the best automations remove duplicate data entry, claims handling friction, and document-processing burden across fragmented systems, freeing clinicians and administrators to focus on care while improving accuracy, turnaround times, and compliance.
Business function
Industry
Genentech Automating Drug Research and BioMarker Validation
Genentech has developed an advanced generative AI system, known as the gRED Research Agent, which empowers scientists to automate the arduous process of drug research and biomarker validation, transforming tasks that previously took weeks into operations completed in minutes.
Use Case
Automating Drug Research
Tools
gRED Research Agent & Claude
Input
Complex scientific queries (e.g. identifying cell surface receptors in specific diseases) and vast data sources including PubMed journals and internal proprietary repositories.
Process
The system utilises autonomous agents to decompose complex research tasks into dynamic, multi-step workflows. By employing RAG, the agents search across multiple knowledge bases and Genentech's internal APIs, adapting their approach based on information gathered at each stage to synthesise high-level findings.
Output
Synthesised scientific findings accompanied by cited summaries and data-driven insights.
Outcome
Expected automation of over 43,000 hours of manual effort in biomarker validation, significantly reducing time-to-target identification and accelerating the delivery of new medicines to patients.
Sanofi implemented the Icertis Contract Intelligence platform to govern all procurement and buy-side contracts globally, replacing fragmented processes with a unified system that provides visibility into contract cycle times, obligations, and compliance across its entire supplier base.
Use Case
AI Contract Lifecycle Management for Procurement
Tools
Internal Tools & Icertis
Input
Global procurement contracts, supplier agreements, compliance obligations and approval workflow data across Sanofi's worldwide operations
Process
The Icertis platform applies AI to extract, classify, and standardise contract data and automates contract generation and approval workflows
Output
Centralised global contract repository with standardised templates with automated contract generation, approval, and execution workflows
Outcome
Improved global visibility into procurement contract performance with measurably faster contract cycle times.
Pharma and Biotech
Procurement
Novo Nordisk's AI-automated clinical study report drafting
Novo Nordisk uses Claude to automate the drafting of clinical study reports, compressing a process that traditionally required around 50 medical writers working for 15 weeks into minutes of machine generation followed by review by just three human experts.
Use Case
AI-Generated Regulatory Clinical Documentation
Tools
Claude
Input
Structured clinical trial data, statistical analysis outputs, and past clinical study report examples provided as context to the AI model.
Process
Claude ingests structured medical data and historical report examples to produce high-quality draft clinical study report content, which is then reviewed and refined by a small team of regulatory experts.
Output
Near-complete draft clinical study reports ready for expert review, covering the required regulatory narrative, tables and summaries for submission.
Outcome
An operation requiring over 50 person-months is compressed to minutes of machine time plus a few hours of human oversight, potentially saving weeks per regulatory submission cycle.
Pharma and Biotech
Product
Moorfields Eye Hospital's RETFound AI foundation model for eye disease
Moorfields Eye Hospital and UCL develop RETFound, the first AI foundation model in ophthalmology, trained on 1.6 million retinal scans from the NHS, enabling rapid automated diagnosis of sight-threatening eye diseases and prediction of systemic conditions including stroke and Parkinson's disease.
Use Case
AI-Powered Retinal Scan Diagnosis and Disease Prediction
Tools
RETFound
Input
1.6 million de-identified retinal optical coherence tomography scans from NHS patient records, along with clinical diagnoses and referral decisions.
Process
A self-supervised AI foundation model pre-trained on the NHS scan dataset is fine-tuned for specific diagnostic tasks, identifying disease markers across more than 50 eye conditions and systemic health indicators.
Output
Automated disease classification reports with referral urgency recommendations and systemic disease risk flags provided to clinical teams alongside patient scan images.
Outcome
RETFound matches world-leading expert accuracy for over 50 eye diseases, has been made freely available open-source globally and enables earlier detection of conditions affecting over 625,000 UK patients.
Hospitals and Clinics
Data
Pfizer's AI-accelerated clinical trial data quality and analysis
During the pivotal PAXLOVID clinical trials, Pfizer deployed AI and machine learning to automate quality checks and analyse large volumes of patient data, compressing timelines that had historically required weeks of manual effort.
Use Case
Automated Clinical Trial Data Quality Control
Tools
Internal Tools
Input
Structured and unstructured patient data from global trial sites, including electronic health records, adverse event reports and lab results across thousands of participants.
Process
ML models run automated quality-check routines across incoming trial datasets, flagging anomalies, inconsistencies, and protocol deviations for human review in near real time.
Output
Validated, analysis-ready clinical datasets with exception reports surfaced to trial statisticians and regulatory affairs teams.
Outcome
Pfizer's clinical teams performed essential quality checks and analysed trial data 50% faster than with previous methods, saving an estimated month of development time on the PAXLOVID programme.
Pharma and Biotech
Product
CareSource Automates Healthcare Document Processing with UiPath
CareSource, a US-based managed care organisation serving over two million members, used UiPath intelligent automation to redesign how it processed large volumes of critical healthcare documents including claims, prior authorisations, faxes, and invoices. The automation reduced manual intervention across its Claims, Utilisation Management, and Clinical Management teams.
Use Case
Automated document processing and claims management across healthcare operations
Tools
UiPath
Input
Incoming healthcare documents including claims, prior authorisation requests, faxes, and vendor invoices received by the C/UM/CM team
Process
UiPath robots extract and classify document data using AI-powered Document Understanding, automatically route claims and authorisation requests, process invoices, and update relevant systems — reducing or eliminating manual review steps
Output
Processed claims, approved prior authorisations, validated invoices, and updated clinical records delivered with reduced manual touchpoints and faster turnaround times
Outcome
Improved claim processing efficiency with reduced manual intervention; enhanced prior authorisation and invoice handling with fewer delays; transformed clinical operations with improved accuracy. CareSource was named a 2024 UiPath AI25 Award winner.
Hospitals and Clinics
Operations
Helse Vest Deploys RPA to Reduce Clinical Admin Burden for Doctors and Nurses
Helse Vest, a regional health authority in Norway, deployed UiPath RPA (nicknamed 'Robbie Vest') to automate repetitive clinical data entry tasks across its hospitals. Key processes automated include prostate cancer patient data registration across three separate systems (DIPS, a research database, and reporting tools) and midwifery intake forms for pregnant women — replacing paper forms and manual multi-system entry.
Use Case
Automation of clinical data entry and patient record management across multiple hospital systems
Tools
UiPath
Input
Patient clinical data including prostate cancer records requiring entry into multiple systems, and digital intake form data from pregnant women submitted via the national health portal helsenorge.no
Process
UiPath robots automatically read patient data from source systems and replicate it across DIPS journal system, research databases, and reporting tools — eliminating duplicate manual entry. For midwifery, the robot captures digital form submissions and populates all required hospital systems automatically.
Output
Accurately populated patient records across all required clinical systems, with no manual re-entry; complete midwifery intake data available to midwives before birth
Outcome
Significant reduction in time spent on administrative data entry for doctors and nurses; improved accuracy of patient data in clinical systems; midwives now receive complete patient information before births, improving patient safety. Helse Vest has become a leading proponent of RPA within Norwegian healthcare.
Hospitals and Clinics
Operations
Novo Nordisk's NNGPT internal AI employee assistant
Novo Nordisk has built NNGPT, a proprietary chat assistant trained on internal knowledge including SOPs, safety documents, research databases, and code repositories, to approximately 17,000 employees across R&D, manufacturing, and corporate functions.
Use Case
Enterprise AI Knowledge Assistant for Employees
Tools
NNGPT
Input
Employee natural language queries submitted via the NNGPT interface, resolved against a curated corpus of internal standard operating procedures, scientific literature, safety documentation and software API references.
Process
A large language model fine-tuned on Novo Nordisk's proprietary internal knowledge base retrieves and synthesises accurate, contextually relevant answers to employee questions in real time.
Output
Instant, accurate answers to operational and scientific questions, boilerplate code generation for developers, and procedure look-ups for process engineers, all surfaced via a conversational interface.
Outcome
Adopted by approximately 17,000 employees, NNGPT reduces time spent searching documentation and answering routine queries, freeing staff to focus on higher-value scientific and commercial work.
Pharma and Biotech
People
Guy's & St Thomas' NHS Foundation Trust CAFM Automation with MRI Software
Guy's & St Thomas' NHS Foundation Trust deploys MRI Software's AI-powered Computer-Aided Facilities Management (CAFM) system to forecast equipment failures, prioritise maintenance across the Trust's estate, and extract operational insights from large volumes of asset data improving efficiency and decision-making in a critical public sector healthcare environment.
Use Case
Predictive Estates Maintenance
Tools
MRI Software CAFM
Input
Asset condition data, maintenance histories, work orders, and operational estate data
Process
MRI Software's AI analyses asset performance data to forecast equipment failures, auto-prioritise work orders by criticality and automate routine scheduling and reporting.
Output
Predictive maintenance alerts, prioritised work order queues, automated scheduling recommendations, and operational efficiency reports for NHS estates managers
Outcome
Reduced unplanned downtime, improved equipment reliability, and facilities staff freed from manual processing to focus on patient care environments.