Patient Support & Adherence Analytics for Life Sciences
Real-time patient prioritization, adherence risk scoring, and connected CGT order management – so support specialists focus on the patients who need them most.
~5%
Patient adherence improvement via real-time outreach prioritization for 110 specialists
30%
Operational efficiency increase via connected CGT order management across 5 functions
$200K
Savings and 3× faster insights via AI-NLP drug experience analysis
The Problem Patient Services Leaders Face
Across therapeutic areas, approximately 50% of patients do not take their medications as prescribed. For pharma companies, this represents billions in lost revenue and, more importantly, millions of patients who are not receiving the full benefit of their therapy.
Most patient support programs take a one-size-fits-all approach: every patient gets the same outreach cadence and the same messaging. Support specialists spend as much time reaching adherent patients as those at high risk of discontinuation. Resources spread thin, and the patients who need the most support often do not receive it in time.
For cell and gene therapy companies, the challenge compounds: order milestones are scattered across systems, manual reconciliation is the norm, and cross-functional visibility is nonexistent.
What We Do
We empower life sciences patient services teams with AI‑driven patient support and adherence analytics that prioritize at‑risk patients, optimize case management, and improve therapy persistence across the patient journey.
Real-Time Patient Prioritization
We build dynamic risk-scoring models that use prescription fill data, engagement history, demographic factors, and therapy complexity to rank patients by discontinuation risk. The system refreshes every 15 minutes and embeds directly into Salesforce – so specialists see their prioritized outreach list without leaving their workflow.
CGT Order Management
We connect order milestones across Trade Operations, Quality, Care Coordination, Finance, and Logistics into a single real-time dashboard. Every stakeholder sees the same patient journey, with automated alerts for delays and escalation triggers for critical path items.
Drug Experience Intelligence (AI-NLP)
We deploy AI-NLP solutions that automatically extract sentiment, themes, and emerging signals from patient and HCP drug experience feedback. This surfaces safety signals and satisfaction trends that manual review cannot detect at scale.
Hub Services Analytics
We build analytics for hub operations including benefits verification, prior authorization tracking, co-pay assistance utilization, and patient enrollment funnel optimization.
Who It’s For
Built for patient services, hub operations, and analytics teams focused on improving adherence, engagement, and patient outcomes through data‑driven insights.
Results
~5%
Adherence improvement, ~110 specialists enabled with 15-min refresh (Amazon Athena, Python, Power BI, Salesforce)
30%
Operational efficiency increase, 5 functions connected for CGT order management (Snowflake, Power BI, dbt, Fivetran)
$200K
Savings, 3× faster insights via AI-NLP drug experience analysis (Dataiku, NLP, Python)
Resources
Explore proven strategies and real‑world examples leveraging real‑time prioritization, NLP‑driven insights, and data‑driven patient engagement.
Blog
The Data Platform Modernization Playbook for Life Sciences: Cloud, Governance, and AI Readiness
Read MoreFAQs
How does real-time patient prioritization work?
The system uses fill data, engagement history, and therapy complexity to calculate a dynamic risk score for each patient. Scores refresh every 15 minutes and are embedded directly in Salesforce, so specialists always see their highest-priority patients.
What is CGT order management?
CGT order management connects every milestone in a cell or gene therapy patient journey – from order placement to apheresis, manufacturing, quality release, logistics, and infusion – into a single real-time dashboard with automated alerts.
Can this integrate with our existing patient support platform?
Yes. We design solutions that embed into existing workflows (Salesforce, custom hubs) rather than requiring new tools. Our approach minimizes change management and maximizes adoption.
How does AI-NLP help with drug experience analysis?
NLP models automatically extract sentiment, themes, and emerging signals from unstructured patient and HCP feedback. This surfaces safety signals and satisfaction trends at scale – 3× faster than manual review.
Book a Patient Analytics Discovery Session
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