Pharma and life sciences
Helping pharma & biotech organisations turn complex data into real-world outcomes, from molecule to market.
Pharmaceutical and biotech companies face growing pressure to bring innovative treatments to market, while navigating complex data, regulatory frameworks, and clinical decision-making. Life sciences analytics is critical to support everything from early-stage research to real-world performance tracking.
But data in this sector is anything but straightforward. It’s often fragmented, study-based, sensitive, and challenging to interpret. That’s where Vizify comes in.
We work with global life sciences teams to transform complex and incomplete datasets into compelling, credible stories. Our tailored analytics solutions help product, research, and medical teams drive understanding, adoption, validation, and ultimately, better patient outcomes.
UK sector stats:
£17.6bn GVA (Gross Value Added)
The UK life sciences sector generates £17.6bn in direct GVA, making it a cornerstone of national growth and innovation.
£9bn annual R&D investment
Pharmaceutical and biotech companies invest over £9bn each year into UK R&D, more than the entire UKRI budget.
411 industry clinical trials initiated in 2022
Trial activity is recovering, rising from 394 in the previous year, but still remains below the 2015 peak of 690.
£28.6m NHS cost savings from clinical trials
Industry-sponsored clinical trials deliver £28.6m in annual cost savings to the NHS via reduced treatment and service pressures.
Source: Facts, figures and industry data by the Association of the British Pharmaceutical Industry (ABPI) – link
Key challenges in life sciences & pharma
Life sciences and pharma organisations are rich in domain and analytical expertise, from clinical researchers to therapeutic area specialists. But even the most data-literate teams face obstacles when managing, interpreting, and communicating data in highly regulated and globally distributed environments.
Regulatory complexity:
GDPR, FDA, MHRA, and other regulations require secure, auditable analytics.
Robust platforms are needed to maintain compliance and enable international data sharing.
Limited early-stage evidence:
New treatments often have minimal real-world evidence (RWE) and clinical trial data; data comes from fragmented, secondary or study-based sources, such as PDFs or scanned registries.
Advanced modelling and aggregation tools are required to derive actionable insights, even when data is sparse or inconsistent.
Data-savvy, not tech-native users:
Life sciences teams including PhDs, researchers, and medical affairs professionals, often lack intuitive, compliant tools to operationalise knowledge.
User-friendly analytics platforms can bridge this gap.
Global business, local nuance:
Pharma must balance global consistency with local healthcare system variation and diverse payer models (from single-payer systems like NHS to fully private markets).
Flexible analytics platforms can handle both scales effectively.
Fragmented, post-launch reporting:
Lack of structured frameworks makes tracking real-world performance difficult.
Integrated dashboards and reporting tools can demonstrate value to stakeholders.
Payer engagement & market access:
Securing reimbursement and demonstrating value to payers requires clear evidence.
Targeted analytics and forecasting can support payer conversations.
Data drift & evolving evidence:
Clinical evidence, real-world evidence (RWE), and registry data continuously evolve, creating uncertainty.
Continuous monitoring and adaptive modelling are essential for accurate insights.
GDPR, FDA, MHRA, and other regulations require secure, auditable analytics.
Robust platforms are needed to maintain compliance and enable international data sharing.
New treatments often have minimal real-world evidence (RWE) and clinical trial data; data comes from fragmented, secondary or study-based sources, such as PDFs or scanned registries.
Advanced modelling and aggregation tools are required to derive actionable insights, even when data is sparse or inconsistent.
Life sciences teams including PhDs, researchers, and medical affairs professionals, often lack intuitive, compliant tools to operationalise knowledge.
User-friendly analytics platforms can bridge this gap.
Pharma must balance global consistency with local healthcare system variation and diverse payer models (from single-payer systems like NHS to fully private markets).
Flexible analytics platforms can handle both scales effectively
Lack of structured frameworks makes tracking real-world performance difficult.
Integrated dashboards and reporting tools can demonstrate value to stakeholders.
Securing reimbursement and demonstrating value to payers requires clear evidence.
Targeted analytics and forecasting can support payer conversations.
Clinical evidence, real-world evidence (RWE), and registry data continuously evolve, creating uncertainty.
Continuous monitoring and adaptive modelling are essential for accurate insights.
Data analytics solutions for pharma & biotech teams
At Vizify, we help subject matter experts translate scientific insight into real-world impact through adaptable analytics tools, rigorous modelling, and secure technology built for pharmaceutical compliance standards. Our analytics solutions span the entire product lifecycle, supporting both pre-launch and post-launch strategies with clear, agile, and compliant tools.
Pre-launch analytics:
Integrate clinical trial and early-stage real-world evidence (RWE) to model potential outcomes.
Identify key patient populations and clinical sites for trials and early interventions.
Forecast treatment adoption patterns to inform launch strategy.
Service & budget impact modelling:
Quantify how a new therapy will impact hospital capacity, staffing, and appointments.
Predict efficiency gains and potential cost savings for procurement discussions.
Provide scenario modelling to support decision-making with payers and regulators.
Market sizing & access analytics:
Segment target populations by geography, demographics, and condition.
Identify key patient populations and clinical sites for trials and early interventions.
Forecast treatment adoption patterns to inform launch strategy.
Post-launch cohort performance analytics:
Track real-world uptake and adherence by geography, hospital, and clinician.
Analyse patient outcomes and treatment effectiveness for evidence generation.
Enable reporting for payers, regulators, and internal teams.
Uptake modelling:
Monitor adoption curves and identify high- or low-performing regions.
Forecast future adoption scenarios to guide commercial and medical strategy.
Provide early warning signals for intervention if uptake lags.
Market impact & effectiveness dashboards:
Visualise treatment effectiveness across cohorts and geographies.
Measure health economic outcomes and service impact.
Provide actionable insights to demonstrate value to payers and stakeholders.
Real-world evidence & data integration:
Aggregate real-world evidence (RWE) from multiple sources (registries, EHRs, observational studies).
Ensure data quality, standardisation, and compliance with regulations.
Support continuous evidence generation for clinical, commercial, and regulatory needs.
Integrate clinical trial and early-stage real-world evidence (RWE) to model potential outcomes.
Identify key patient populations and clinical sites for trials and early interventions.
Forecast treatment adoption patterns to inform launch strategy.
Quantify how a new therapy will impact hospital capacity, staffing, and appointments.
Predict efficiency gains and potential cost savings for procurement discussions.
Provide scenario modelling to support decision-making with payers and regulators.
Segment target populations by geography, demographics, and condition.
Identify key patient populations and clinical sites for trials and early interventions.
Forecast treatment adoption patterns to inform launch strategy.
Track real-world uptake and adherence by geography, hospital, and clinician.
Analyse patient outcomes and treatment effectiveness for evidence generation.
Enable reporting for payers, regulators, and internal teams.
Monitor adoption curves and identify high- or low-performing regions.
Forecast future adoption scenarios to guide commercial and medical strategy.
Provide early warning signals for intervention if uptake lags.
Visualise treatment effectiveness across cohorts and geographies.
Measure health economic outcomes and service impact.
Provide actionable insights to demonstrate value to payers and stakeholders.
Aggregate real-world evidence (RWE) from multiple sources (registries, EHRs, observational studies).
Ensure data quality, standardisation, and compliance with regulations.
Support continuous evidence generation for clinical, commercial, and regulatory needs.
Who we support
We create tools that bridge expertise and insight across roles, enabling smoother communication and smarter decision-making.
Therapeutic area (TA) specialists & researchers
PhDs and clinicians who need to extract insight from data but are not technologists.
Strategic healthcare account leaders
Field-based reps who need to explain therapeutic value to clinicians in a clear, evidence-backed way.
Health economics and market access (HEOR)
Those preparing and defending value cases before, during, and after launch for reimbursement and regulatory approval.
Product and operations teams
Seeking cross-market visibility, uptake, and performance analysis.
Customer success
We supported a global pharmaceutical firm in the UK with the roll-out of 3 new treatments in multiple therapeutic areas, by creating unified analytics dashboards. The tools allowed therapeutic area experts to demonstrate cost savings, staffing efficiencies, and patient outcome improvements, accelerating uptake in NHS settings.
Our technology toolkit
We are technology agnostic, meaning we can build into your existing systems or provide a secure, standalone solution using any technology — always with regulatory and security needs in mind.
Client success stories
NHS NWL
Delivered a whole-systems integrated care dashboard suite for population health management across London.
Well Pharmacy
Built workforce capacity planning and patient flow tools to optimise services
Agito Medical
Supported integration of supply chain and clinical data for equipment and healthcare partners.
CNWL NHS Foundation Trust
Delivered a comprehensive data strategy and data maturity assessment, and now partnering on the delivery of their enterprise analytics platform.
NHS NWL
Developed clinical radars to support long-term condition management such as Asthma, Diabetes, etc
Why Vizify?
Healthcare + pharma experience
We bring deep sector understanding, not just tech. Our team has worked with therapeutic area specialists, payers, and healthcare teams in the UK and globally.
Technology agnostic
Our tools are built using the technologies you prefer, whatever suits your environment and regulatory setup.
Consulting-first approach
We combine data analytics with domain expertise to bridge the gap between research and adoption.
Post-launch proof, not just pre-launch promise
We help teams not only model value, but measure and communicate it after go-live.
Agile delivery, global understanding
We customise our approach to suit national payer models, clinician needs, and international compliance frameworks. Whether you're making modest investments or planning a global rollout, we can quickly adapt.
Secure and compliant
ISO-certified and an approved supplier on G-Cloud 14 (the UK government's Digital Marketplace), providing solutions designed to protect sensitive patient health data.
Ready to turn your pharma and life sciences data into insight and impact?
Whether you’re preparing for launch, navigating global compliance, or proving real-world outcomes, Vizify delivers analytics tailored to pharma and biotech.
📩 Get in touch to discuss your pharmaceutical data analytics needs.
Related case studies:
Related blog posts:
