Pharma Lab Information System Modernization: Proven 45% Time Savings

The average pharmaceutical lab loses $2.5 million per hour during unplanned system downtime, yet most Laboratory Information Management Systems (LIMS) are running on technology stacks that predate the smartphone. These legacy systems—often written in Delphi, PowerBuilder, or early .NET—are the "black boxes" of the enterprise. They hold the keys to drug discovery and clinical trials, but their lack of documentation and rigid architectures make them nearly impossible to update without risking catastrophic data loss or regulatory non-compliance.

The industry standard for a full-scale pharma information system modernization has historically been a grueling 18-24 month marathon. However, by shifting from manual documentation to Visual Reverse Engineering, enterprise architects are now achieving the same results in less than half the time.

TL;DR:

• •Legacy pharma systems suffer from a 67% lack of documentation, leading to high-risk modernizations.
• •Manual screen-to-code conversion takes 40+ hours per screen; Replay reduces this to 4 hours.
• •Visual Reverse Engineering allows labs to modernize without a "big bang" rewrite, saving 45-70% in total project time.
• •Key technologies: React, TypeScript, and AI-driven component extraction.

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The Technical Debt Wall in Pharmaceutical Research#

The global technical debt currently sits at a staggering $3.6 trillion. In the pharmaceutical sector, this debt is compounded by strict GxP (Good Practice) requirements and FDA 21 CFR Part 11 compliance. When you attempt a pharma information system modernization, you aren't just updating a UI; you are migrating decades of validated workflows that must remain audit-ready.

According to Replay's analysis, 70% of legacy rewrites fail or significantly exceed their timelines because the original business logic is "trapped" in the heads of retired developers or buried in undocumented codebases. When documentation is missing—which is the case for 67% of legacy systems—the only source of truth is the running application itself.

The Anatomy of a Legacy Pharma UI#

Most legacy lab systems rely on heavy-client architectures. They feature dense, data-heavy grids, complex nested modals, and proprietary charting engines. Manually mapping these to modern React components is a recipe for errors.

Video-to-code is the process of capturing these live user sessions and automatically generating structured documentation, component hierarchies, and production-ready React code. This is where Replay changes the math of modernization.

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Why Pharma Information System Modernization is Non-Negotiable#

The cost of doing nothing is no longer zero. Modern drug discovery requires high-throughput screening and AI-driven data analysis that legacy LIMS simply cannot support. To integrate with modern data lakes and AI models, the front-end must be decoupled from the monolithic back-end.

Industry experts recommend a "strangler fig" pattern for these migrations, but even that requires a clear map of the existing system. Manual mapping is the bottleneck.

Comparison: Manual vs. Replay-Accelerated Modernization#

As shown, the efficiency gain isn't incremental; it's exponential. By using Replay, teams can bypass the "archeology phase" of software engineering and move straight to implementation.

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Technical Implementation: From Legacy Recording to React Components#

The core challenge in pharma information system modernization is maintaining the complex state management found in lab environments. For example, a sample tracking grid might have 50+ columns with conditional formatting based on reagent stability.

When you record these workflows using Replay, the platform's AI Automation Suite analyzes the visual output and the DOM structure to generate a clean, accessible React component library.

Step 1: Extracting the Design System#

Instead of guessing CSS values, Replay identifies recurring UI patterns across your lab software and centralizes them into a "Library." This ensures that your new React-based system maintains the functional density required by lab technicians while adopting a modern look and feel.

Step 2: Generating the Component Code#

Here is an example of how a legacy data grid for "Reagent Inventory" might be transformed into a modern, type-safe React component using the output from Replay's Visual Reverse Engineering.

typescript
// Generated React Component from Replay Blueprint
import React from 'react';
import { DataGrid, GridColDef } from '@mui/x-data-grid';
import { useLabInventory } from '../hooks/useLabInventory';

interface ReagentInventoryProps {
  labId: string;
  onAlert: (reagentId: string) => void;
}

/**
 * ReagentInventoryGrid: Modernized from legacy Delphi Grid v4.2
 * Captured via Replay Visual Reverse Engineering
 */
export const ReagentInventoryGrid: React.FC<ReagentInventoryProps> = ({ labId, onAlert }) => {
  const { data, loading, error } = useLabInventory(labId);

  const columns: GridColDef[] = [
    { field: 'id', headerName: 'Lot ID', width: 120 },
    { field: 'name', headerName: 'Chemical Name', flex: 1 },
    { 
      field: 'stability', 
      headerName: 'Stability Index', 
      type: 'number',
      renderCell: (params) => (
        <span className={params.value < 20 ? 'text-red-600 font-bold' : ''}>
          {params.value}%
        </span>
      )
    },
    { field: 'expiryDate', headerName: 'Expiration', width: 150 },
  ];

  if (loading) return <div>Synchronizing with Lab Middleware...</div>;

  return (
    <div style={{ height: 600, width: '100%' }}>
      <DataGrid 
        rows={data} 
        columns={columns} 
        pageSize={10} 
        checkboxSelection
        onRowClick={(row) => row.value < 20 && onAlert(row.id.toString())}
      />
    </div>
  );
};

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Mapping Workflows with Replay Flows#

Modernization isn't just about individual screens; it's about the "Flows" between them. In a pharma environment, a "Sample-to-Result" flow might involve six different screens and three different approval gates.

Replay Flows allow architects to visualize the entire user journey. By recording a technician performing a standard operation, Replay generates a functional map of the architecture. This is critical for Modernizing Mainframe UIs or complex client-server applications where the sequence of operations is as important as the data itself.

Handling Complex State in Pharma Systems#

Legacy systems often use global state variables that make modernizing a single module difficult. Replay’s AI analyzes the transitions between screens to suggest a state management strategy (like Redux or React Context) that mirrors the legacy logic without the technical debt.

typescript
// State Management Structure suggested by Replay AI for Lab Workflows
export interface LabWorkflowState {
  currentSampleId: string | null;
  validationStatus: 'PENDING' | 'APPROVED' | 'REJECTED';
  activeProtocols: string[];
  lastAuditTimestamp: number;
}

export const workflowReducer = (state: LabWorkflowState, action: any) => {
  switch (action.type) {
    case 'SET_SAMPLE':
      return { ...state, currentSampleId: action.payload };
    case 'UPDATE_VALIDATION':
      return { ...state, validationStatus: action.payload };
    default:
      return state;
  }
};

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Overcoming Regulatory Hurdles with Automated Documentation#

In the world of pharma, "if it isn't documented, it didn't happen." This is the primary reason why pharma information system modernization projects stall. Auditors require proof that the new system behaves exactly like the old one.

Traditional modernization requires manual side-by-side testing and thousands of pages of functional specifications. Replay automates this by providing a "Visual Source of Truth." You can compare the recording of the legacy system directly against the new React implementation.

For more on how this works in highly regulated sectors, see our guide on Design System Automation.

Security and Compliance#

Replay is built for regulated environments:

• •SOC2 & HIPAA Ready: Data is handled with enterprise-grade security.
• •On-Premise Availability: For labs with strict data residency requirements, Replay can be deployed within your own firewall.
• •Audit Trails: Every component generated and every flow mapped is logged, providing a clear history for regulatory bodies.

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The Strategic Advantage of Visual Reverse Engineering#

By reducing the time per screen from 40 hours to just 4 hours, Replay allows pharma companies to reallocate their budget from "keeping the lights on" to actual innovation.

Pharma information system modernization is no longer about a risky, multi-year "Big Bang" migration. Instead, it becomes a series of rapid, high-confidence sprints. You can modernize the most critical lab modules first—such as inventory management or result reporting—while keeping the rest of the legacy system running in the background.

Real-World Impact: The 45% Time Savings#

Consider a typical LIMS with 200 screens.

• •Manual approach: 200 screens * 40 hours = 8,000 developer hours.
• •Replay approach: 200 screens * 4 hours = 800 developer hours.

Even when you factor in the time for backend integration and QA, the front-end acceleration provided by Replay typically results in a 45% to 70% reduction in the total project lifecycle.

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Frequently Asked Questions#

How does Replay handle proprietary lab hardware integrations?#

Replay focuses on the software interface layer. While it records how the software interacts with hardware (e.g., displaying a "Reading..." state), the actual driver integration is handled via modern APIs or middleware. Replay provides the React hooks and UI components that make these integrations seamless for the end-user.

Can we use Replay for systems that are completely undocumented?#

Yes. In fact, this is where Replay excels. Since Replay uses Visual Reverse Engineering to analyze the running application, it doesn't matter if the source code is lost or the original developers are gone. If you can run the application and record the workflow, Replay can modernize it.

Is the code generated by Replay "clean" or is it "spaghetti code"?#

Replay generates human-readable, type-safe TypeScript and React code. It follows modern best practices, including component modularity and separation of concerns. The code is designed to be owned and maintained by your internal team, not hidden behind a proprietary layer.

How does this impact FDA validation (CSV)?#

Because Replay provides a visual and functional map of the legacy system, it actually simplifies the Computer System Validation (CSV) process. You have a clear baseline of the "As-Is" system to compare against the "To-Be" system, making it easier to prove functional equivalence to auditors.

Does Replay support on-premise deployments for sensitive lab data?#

Yes. We understand that pharmaceutical data is highly sensitive. Replay offers on-premise deployment options that allow you to keep all recordings and generated code within your secure network, ensuring compliance with internal data governance policies.

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Conclusion: The Path to a Modern Lab#

The complexity of pharma information system modernization has historically been a barrier to entry for many organizations. The risk of breaking a validated workflow was simply too high. However, with the advent of Visual Reverse Engineering and tools like Replay, that risk is mitigated through automation and visual verification.

By converting video recordings of real user workflows into documented React code, pharmaceutical companies can finally shed their technical debt and build a foundation for the future of digital health.

Ready to modernize without rewriting? Book a pilot with Replay