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Case Study | TLV Drug Price Tracking Automation for Pharmaceutical Pricing

Automating TLV drug price tracking beyond manual Excel

Full-Cycle Development Automation Custom Software Development

FiftyFive built a secure drug pricing intelligence platform that replaces manual TLV Excel monitoring with daily automated ingestion. The system detects AIP and AUP price changes, keeps historical pricing records, and sends scheduled email alerts to pricing and market access teams.

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The Client

Overview

The client operates in Sweden's regulated pharmaceutical pricing market. The business covers drug pricing intelligence, TLV dataset monitoring, compliance tracking, and competitive pricing analysis. Pricing data feeds market access decisions, so accurate and timely visibility of regulated price movements is central to how the client works.

The Need

Challenges

Replacing a manual Excel workflow with an automated pricing intelligence platform meant solving data engineering, security, and reliability problems at the same time. Regulated pharmaceutical pricing data leaves no room for missed updates or unprotected records.

  • The client reviewed TLV Excel files by hand and compared them release over release. Repeated file reviews and manual comparison delayed the point at which a price change was actually noticed.
  • Pharmaceutical pricing datasets had to be ingested every day without timeouts or memory failures, which required streaming and chunking rather than loading whole files into memory.
  • The platform needed reliable AIP and AUP change detection logic, plus historical price versioning across large datasets so that every past value stayed queryable rather than being overwritten.
  • Multi-user authentication, role-based authorization, and PostgreSQL Row-Level Security policies all had to work together so users only ever saw the records their role permitted.
  • Cron-driven ingestion and alerting had to run dependably every day, while edge function changes carried regression risk across the authentication and processing flows.
  • Logging had to stay GDPR-compliant and personally identifiable information had to be protected throughout the system.
Our Approach

Solution

FiftyFive delivered the platform end to end: architecture, development, QA, and deployment. The system ingests TLV Excel datasets automatically every day, detects AIP and AUP price changes, stores historical pricing records, and pushes alerts by email on a schedule. It runs on a React and Supabase stack with Auth0 authentication, PostgreSQL Row-Level Security, and a production deployment on Vercel. The client no longer opens a spreadsheet to find out what changed.

Automated TLV ingestion pipeline

FiftyFive replaced the manual file review with a scheduled ingestion pipeline built for large structured datasets.

  • Automated TLV Excel ingestion using streaming and chunking.
  • Scheduled cron jobs running daily ingestion.
  • Supabase Edge Functions handling event-driven processing workflows.

Price change detection and historical tracking

The platform turns each day's dataset into a comparison rather than a file to read.

  • Price change triggers for AIP and AUP values.
  • Historical price tracking across large pharmaceutical datasets.
  • Price versioning so previous values remain available for analysis.

Secure access and compliance architecture

Security was designed into the data layer, not added at the interface.

  • Auth0 integration for secure authentication and role-based user management.
  • PostgreSQL schemas with indexing, Row-Level Security policies, and access controls.
  • GDPR-compliant logging and protection of personally identifiable information.
  • Endpoint hardening as part of the production deployment.

Alerting and notifications

Price movements reach the people who act on them without anyone checking a file.

  • Resend API integrated for transactional and digest notifications.
  • Scheduled cron jobs sending email alerts.
  • Alerts tied directly to detected AIP and AUP price changes.

Frontend and delivery stack

The interface and delivery approach were chosen for speed of build and production stability.

  • Frontend built with React 18, TypeScript, Vite, Tailwind CSS, and shadcn/ui.
  • Supabase used as the Backend as a Service layer.
  • Lovable AI used to accelerate AI-assisted development workflows.
  • Production platform deployed on Vercel with performance hardening.
Technology

Tech Stack

Frontend

React 18TypeScriptViteTailwind CSSshadcn/ui

Automation

Scheduled Cron Jobs

Deployment

Vercel

Backend

Supabase (BaaS)Supabase Edge Functions

Authentication

Auth0Role-Based Access

Notifications

Resend API

Database

PostgreSQLIndexingRow-Level SecurityAccess Controls

AI-Assisted Development

Lovable AI
Experts

Team

1

AI-Enabled Full
Stack Developer

1

Penetration /
Security Tester

1

Quality
Analyst

1

Project Manager /
Technical Lead

The Impact

Results

Project Duration2 Months

FiftyFive delivered a production-ready drug pricing intelligence platform in two months. The platform replaced manual TLV Excel tracking with automated ingestion, change detection, historical records, and scheduled alerts.

Two-month delivery

FiftyFive delivered the production pharmaceutical pricing platform in two months, covering architecture, development, QA, and deployment.

Daily automated ingestion

The platform ingests TLV pricing datasets daily through scheduled jobs, removing repeated manual Excel file reviews and comparison work.

AIP and AUP detection

Automated triggers detect AIP and AUP price changes across regulated drug datasets, improving visibility of pricing updates for market access teams.

Compliance-ready architecture

Row-Level Security, role-based access, and GDPR-compliant logging strengthened compliance readiness across a secure, scalable pharmaceutical pricing system.

Support

FAQs

A drug pricing intelligence platform automatically collects, monitors, and compares regulated pharmaceutical pricing data so teams can see price changes as they happen. It replaces manual spreadsheet reviews with scheduled data ingestion, automated change detection, historical price records, and alerts that reach pricing and market access teams directly.

Pharmaceutical companies automate TLV price monitoring by building a pipeline that ingests TLV datasets on a daily schedule, compares each release against stored history, and flags AIP and AUP changes automatically. Scheduled jobs and email alerts remove the need to download, open, and manually compare Excel files.

Manual Excel tracking is slow, error-prone, and hard to audit. Teams must repeatedly download files, compare versions by hand, and risk missing a change or spotting it late. Spreadsheets also lack access controls, version history, and automated alerting, all of which regulated pricing work depends on.

Pharmaceutical price monitoring is the ongoing tracking of regulated and competitor drug prices so companies can react to changes quickly. Teams watch official pricing datasets for increases, decreases, and new listings, then use those movements to support reimbursement, tender, and market access decisions.

Most pharmaceutical companies track drug price changes by downloading official pricing files and comparing them manually in spreadsheets. Automated pricing platforms replace that work by ingesting datasets on a schedule, comparing each release against stored history, and alerting teams by email whenever a price moves.

The TLV is Sweden's Dental and Pharmaceutical Benefits Agency, which decides which medicines are subsidised and publishes the regulated prices that apply. Companies selling in Sweden monitor TLV datasets to follow pharmacy purchase and retail prices, reimbursement decisions, and competitor pricing positions.

Drug pricing intelligence software collects pricing data automatically, detects changes, stores historical values, and alerts the people who act on them. It gives pricing, market access, and commercial teams one current view of how regulated and competitor prices move, instead of scattered spreadsheet versions.

Spreadsheets are risky because they depend on someone remembering to download, open, and compare every file. A missed update, a broken formula, or an outdated copy can go unnoticed for weeks. Spreadsheets also lack access controls, audit trails, and automatic alerts that regulated pricing work requires.

A drug price monitoring platform should offer automated data ingestion, price change detection, historical version tracking, role-based access control, and scheduled alerts. Compliance-ready logging, secure authentication, and an interface non-technical pricing teams can use without training matter just as much for daily adoption.

Pricing automation gives market access teams faster visibility of price movements, so decisions rest on current data rather than a spreadsheet someone updated last week. Automated detection and alerting shorten the gap between a published price change and the commercial response to it.

Pharmaceutical platforms stay secure and GDPR compliant through role-based access, database-level security policies that limit what each user can read, protection of personally identifiable information, and compliant logging practices. Secure authentication and hardened production endpoints keep regulated data protected once the system is live.

Pharmaceutical data platforms are typically built with a web frontend, a cloud database for structured pricing data, scheduled jobs for automated ingestion, and managed authentication. FiftyFive used React, TypeScript, Supabase, PostgreSQL, and Auth0 to build this regulated pharmaceutical pricing platform.

A focused pharmaceutical data platform can be built in around two months with a small dedicated team. Timelines depend on dataset complexity, the number of integrations, compliance requirements, and how much historical data must be migrated, with larger multi-market systems taking considerably longer.

Cost depends on team size, project length, data complexity, and security requirements. A focused platform delivered by a small team over roughly two months sits at the lower end, while multi-market data sources, deeper integrations, and extensive compliance work increase scope and budget.

Choose a partner with experience in regulated data, secure architecture, and compliance requirements, not general web development alone. FiftyFive Technologies builds custom pharmaceutical and regulated-data platforms from offices in India, the UK, Sweden, and the UAE, covering architecture, development, QA, and deployment.

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