Modernizing Legacy Pharma Manufacturing Systems for Data Integrity Compliance

The average pharmaceutical manufacturing facility operates on software that is, quite literally, a black box. While the industry moves toward Pharma 4.0, the reality on the plant floor is often a collection of legacy LIMS (Laboratory Information Management Systems) and MES (Manufacturing Execution Systems) that haven't seen a documentation update since the early 2000s. When data integrity is the difference between a successful batch and a multi-million dollar FDA warning letter, "hoping" your legacy code still works isn't a strategy—it's a liability.

TL;DR: Modernizing legacy pharma systems no longer requires high-risk, 24-month "Big Bang" rewrites; by using visual reverse engineering, organizations can extract business logic and UI components in weeks while maintaining strict ALCOA+ data integrity compliance.

The $3.6 Trillion Compliance Trap#

Global technical debt has ballooned to $3.6 trillion, and nowhere is this debt more dangerous than in life sciences. In pharmaceutical manufacturing, the "documentation gap" is a systemic crisis. Recent audits show that 67% of legacy systems lack up-to-date documentation. When you combine this with the fact that 70% of legacy rewrites fail or exceed their timelines, CTOs find themselves paralyzed.

They are stuck between two impossible choices:

1. •The Status Quo: Run on unsupported, fragile systems that risk data integrity breaches.
2. •The Big Bang Rewrite: Spend 18–24 months and millions of dollars trying to replicate logic that no one living truly understands.

The risk isn't just technical; it's regulatory. The FDA’s focus on ALCOA+ (Attributable, Legible, Contemporaneous, Original, Accurate) means that if you cannot prove how your system handles data, you don't have a validated system.

The Modernization Matrix: Comparing Approaches#

Why Pharma Rewrites Fail#

Most pharma modernization projects fail because they treat the legacy system as a "code problem" rather than a "workflow problem." Developers spend months performing "software archaeology," digging through obfuscated COBOL, Java, or legacy .NET code to find business rules that are often buried in stored procedures or hard-coded UI logic.

In a regulated environment, you cannot afford to guess. If a legacy system calculates a dissolution rate or a tablet hardness deviation, the new system must do it identically. Manual extraction takes an average of 40 hours per screen. With Replay, this is reduced to 4 hours. By recording real user workflows, we use the video as the "source of truth" to extract exactly what the system does, not what the outdated documentation says it should do.

⚠️ Warning: Attempting to modernize without a "Source of Truth" workflow recording often leads to "Requirement Drift," where the new system fails to meet 21 CFR Part 11 compliance because subtle audit trail triggers were missed during manual analysis.

Step-by-Step: Modernizing Legacy Pharma Systems with Replay#

To move from a black box to a documented, modern React-based architecture, follow this battle-tested framework.

Step 1: Technical Debt Audit & Workflow Mapping#

Before touching a line of code, you must identify the high-risk areas. Focus on the screens that handle "Critical Process Parameters" (CPPs) and "Key Quality Attributes" (KQAs).

• •Identify the top 20% of screens that handle 80% of the data integrity risk.
• •Map the user roles (Operator, QA, Lab Tech).
• •Audit the existing API endpoints (or lack thereof).

Step 2: Visual Recording of Validated Workflows#

Instead of reading code, record the application in use. Use Replay to capture a laboratory technician performing a standard titration log or a batch release. This recording captures the DOM state, network calls, and state transitions.

💡 Pro Tip: Capture "Negative Paths" as well. Recording how the legacy system handles an invalid input is just as important for validation as recording the "Happy Path."

Step 3: Automated Component & Logic Extraction#

Once the workflow is captured, Replay's AI Automation Suite converts the visual recording into modern React components and TypeScript logic. This eliminates the "blank page" problem and ensures the UI matches the validated process.

typescript
// Example: Generated React Component from a Legacy Batch Record Screen
// This component preserves the exact validation logic found in the legacy system.

import React, { useState, useEffect } from 'react';
import { Alert, TextField, Button } from '@/components/ui';

interface BatchValidationProps {
  initialpH: number;
  targetRange: [number, number];
  onValidate: (isValid: boolean) => void;
}

export const BatchpHValidator: React.FC<BatchValidationProps> = ({
  initialpH,
  targetRange,
  onValidate
}) => {
  const [currentValue, setCurrentValue] = useState<number>(initialpH);
  const [error, setError] = useState<string | null>(null);

  // Logic extracted via Replay from legacy 'Validation_Module_v4.dll'
  const validateThreshold = (value: number) => {
    const [min, max] = targetRange;
    if (value < min || value > max) {
      setError(`Critical Deviation: pH ${value} is outside range ${min}-${max}`);
      return false;
    }
    setError(null);
    return true;
  };

  const handleUpdate = (e: React.ChangeEvent<HTMLInputElement>) => {
    const val = parseFloat(e.target.value);
    setCurrentValue(val);
    const isValid = validateThreshold(val);
    onValidate(isValid);
  };

  return (
    <div className="p-4 border rounded-lg bg-white shadow-sm">
      <h3 className="text-lg font-bold">Batch Quality Control</h3>
      <TextField 
        label="Enter Measured pH"
        type="number"
        value={currentValue}
        onChange={handleUpdate}
        error={!!error}
      />
      {error && <Alert variant="destructive" message={error} />}
      <Button disabled={!!error} className="mt-4">
        Sign and Submit to Audit Trail
      </Button>
    </div>
  );
};

Step 4: API Contract Generation#

Legacy systems often lack documented APIs. As you record workflows, Replay monitors the network layer to generate OpenAPI (Swagger) specifications. This allows you to build a modern frontend that communicates with the legacy backend via a "wrapper" or "adapter" layer, following the Strangler Fig pattern.

yaml
# Generated API Contract for Legacy LIMS Integration
openapi: 3.0.0
info:
  title: Legacy LIMS Wrapper API
  version: 1.0.0
paths:
  /samples/{sampleId}/results:
    post:
      summary: Submit lab results to legacy database
      parameters:
        - name: sampleId
          in: path
          required: true
          schema:
            type: string
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                analyte: {type: string}
                value: {type: number}
                unit: {type: string}
                timestamp: {type: string, format: date-time}

Step 5: Automated E2E Test Generation#

Validation is the most expensive part of Pharma IT. Typically, for every hour of development, you spend four hours on validation. Replay generates Playwright or Cypress E2E tests directly from the recorded workflows, ensuring that the new system behaves exactly like the old one.

typescript
// Generated E2E Test to Verify Logic Parity
import { test, expect } from '@playwright/test';

test('Verify pH Validation Parity with Legacy System', async ({ page }) => {
  await page.goto('/modern/batch-validator');
  
  // Enter an out-of-range value observed in legacy recording (ID: REC-992)
  await page.fill('input[type="number"]', '14.5');
  
  // The error message must match the legacy system's requirement for 21 CFR Part 11
  const errorMessage = page.locator('text=Critical Deviation');
  await expect(errorMessage).toBeVisible();
  
  // Ensure the submit button is disabled (Data Integrity Rule)
  const submitBtn = page.locator('button:has-text("Sign and Submit")');
  await expect(submitBtn).toBeDisabled();
});

Solving the Data Integrity (ALCOA+) Challenge#

In pharma, "Data Integrity" isn't just a database constraint; it's a regulatory requirement. Legacy systems often fail because they have "ghost logic"—triggers and constraints that aren't documented but exist in the compiled binaries.

Replay addresses this by providing Visual Reverse Engineering. When you record a workflow, you aren't just seeing the UI; you are seeing the system's reaction to data.

• •Attributable: Replay captures the user identity and the exact sequence of actions.
• •Legible: Converts "black box" logic into readable React/TypeScript code.
• •Contemporaneous: The documentation is generated as the system is used, not months later from memory.
• •Original: The video recording serves as the original source of truth for the reverse engineering process.
• •Accurate: AI-driven extraction reduces the human error inherent in manual code translation.

💰 ROI Insight: By automating the extraction of 50 screens in a typical MES modernization, an enterprise saves approximately 1,800 man-hours. At an average architect rate of $150/hr, that’s $270,000 saved on a single module, while reducing the time-to-market from 18 months to 12 weeks.

Built for Regulated Environments#

We understand that Pharma doesn't just need "fast"—it needs "compliant." Replay is built from the ground up for the most stringent security requirements:

• •SOC2 & HIPAA Ready: Your data is protected by industry-standard security protocols.
• •On-Premise Availability: For manufacturers with strict air-gapped requirements, Replay can be deployed entirely within your firewall.
• •Audit Trails: Every extraction and code generation event is logged, providing a clear path for GAMP5 Category 4 or 5 software validation.

Frequently Asked Questions#

How does Replay handle complex business logic hidden in the backend?#

Replay captures the interaction between the frontend and the backend. By observing the data sent, the state changes in the UI, and the responses received, our AI Automation Suite can reconstruct the expected business logic. For complex server-side calculations, Replay generates the API contracts and unit tests required to verify that the new backend logic matches the legacy output 1:1.

Can we use this for systems with no source code available?#

Yes. This is a primary use case. Because Replay uses "Visual Reverse Engineering," it doesn't need to read your COBOL or legacy C++ source code. It observes the application's behavior at the runtime level (DOM, Network, State), making it the perfect tool for systems where the original vendor is out of business or the source code has been lost to time.

How does this fit into GAMP5 validation?#

Replay significantly accelerates the "Design Qualification" (DQ) and "Installation Qualification" (IQ) phases. By providing automated documentation and E2E tests that are derived from actual system usage, you provide auditors with higher-quality evidence of system behavior than manual screenshots and Word documents could ever offer.

What is the learning curve for our team?#

If your team knows React and TypeScript, they can use Replay. The platform is designed to augment your existing engineers, not replace them. Instead of spending months on "archaeology," they spend their time reviewing and refining the code that Replay generates.

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Ready to modernize without rewriting? Book a pilot with Replay - see your legacy screen extracted live during the call.