Now accepting early access partners

Validation that moves
at the speed of science.

EVOLV | The Validation Factory

The first AI-native Computer System Validation platform built for GAMP 5, 21 CFR Part 11, and FDA QMSR. Generate compliant URS, automate risk assessment, and govern AI model changes — in minutes, not months.

Request Early Access ▶ Try Live Demo
GAMP 5 21 CFR Part 11 21 CFR Part 820 QMSR ISO 13485:2016 FDA PCCP Guidance Aug 2025 GMP Annex 11 EU GMP

The Problem

CSV validation still runs on
spreadsheets and email chains.

Life sciences teams spend months on documentation that should take days. Regulatory guidance has changed. Most platforms haven't.

📋

Weeks to generate a URS

Requirements written manually in Word, reviewed in meetings, rewritten after audit findings. No regulatory traceability. No version control. Just documents.

⚠️

Regulations change. VMPs don't.

FDA's QMSR replaced the QSR on February 2, 2026. The PCCP final guidance landed August 2025. Most validation plans still cite rules that no longer exist.

🤖

AI in GxP with no governance

Drug interaction predictors and defect classifiers are being deployed with no PCCP, no change control, no audit trail. FDA inspectors are starting to notice.

The Platform

One platform.
The entire validation lifecycle.

From first requirement to post-market governance — every step compliant, auditable, and powered by AI that knows GAMP 5.

📄

Validation Factory

Generate GAMP 5-compliant URS from plain English. SMART refinement, PCCP verification, UR/FR decomposition, CSA test scripts, and PDF export with e-signature — in one guided workflow. What took days takes minutes.

URS Generation SMART Refinement UR/FR Decomposition CSA Test Scripts PDF + E-Signature
🔄

Change Control

ServiceNow change requests cross-referenced against your system portfolio in real time. GxP classification, GAMP-aware risk calculation using Severity × Occurrence × Detectability, and automatic revalidation flags. No spreadsheet required.

ServiceNow Integration GxP Classification GAMP Risk Matrix Revalidation Flags
🤖

AI Model Governance

Validated AI models treated as GAMP Category 5 assets. PCCP-aware change assessment aligned to FDA final guidance August 2025. Human-in-the-loop approval queue with 21 CFR Part 11 compliant audit trail.

PCCP Assessment HITL Governance FDA Aug 2025 21 CFR Part 11
📊

Portfolio Dashboard

Every system, every site, every phase — one view. RAG status, action items, regulatory due dates. Register new systems with GxP classification and track their full validation journey from plan to monitor. Built for QA Heads and CTOs.

RAG Status System Registry Lifecycle Tracking Multi-Site

See It In Action

Watch EVOLV handle in 4 minutes
what takes your team weeks.

Three real workflows. No voiceover scripts. No slides. Just the platform doing what it's built to do.

Demo 01

Portfolio Dashboard

Your entire validated system landscape — GAMP category, GxP status, risk level, revalidation due dates — in one view. Built for QA Heads and CTOs who need portfolio-wide compliance visibility instantly..

Demo 02

Change Control & GxP Classification

ServiceNow CR received → portfolio cross-reference → GAMP risk calculation → revalidation decision. Automatic.

Demo 03

AI Model Governance

AI model change in a validated system → PCCP assessment → Governance Hub → human-in-the-loop approval → 21 CFR Part 11 audit trail. Built for FDA's final guidance (Aug 2025).

Try the Validation Factory — live, right now.

Generate a real GAMP 5-compliant URS from your own requirement. No login required.

▶ Open Live Demo

Built For

EVOLV speaks the language
of regulated industries.

Whether you're defending a validation package in an inspection or governing 150 systems across 25 sites — EVOLV gives you the records to back it up.

🧪 QA Head · CSV Manager

Stop writing in Word. Start validating.

EVOLV generates, verifies, and manages your entire validation portfolio with a complete audit trail FDA inspectors can review on the spot.

  • URS from plain English in minutes
  • SMART requirements, auto-verified against GAMP 5
  • Full lifecycle tracking — Plan to Monitor
  • Audit-ready PDFs with e-signature

📋 VP Regulatory Affairs

FDA updated the rules. EVOLV already knows.

QMSR is mandatory. PCCP guidance is final. EVOLV cites the right regulations, routes the right changes, and produces the records you need when an inspector walks in.

  • Aligned to FDA PCCP Guidance Aug 18, 2025
  • 21 CFR Part 820 QMSR / ISO 13485:2016
  • SHA-256 tamper-evident audit trail
  • 21 CFR Part 11 electronic records

💻 CTO · CDO

Your AI models are GAMP Cat 5 assets.

EVOLV gives you the governance infrastructure to deploy AI in GxP contexts without regulatory exposure — with a full HITL approval layer and immutable decision records.

  • AI model registry with version history
  • PCCP-aware change assessment
  • Human-in-the-loop governance hub
  • Portfolio-wide RAG visibility

Regulatory Coverage

GAMP 5 (2nd Edition) 21 CFR Part 11 21 CFR Part 820 QMSR ISO 13485:2016 FDA PCCP Guidance Aug 18, 2025 GMP Annex 11 EU GMP GLP ISO 17025 GDPR 21 CFR Part 820.35 QMSR FDA CSA Guidance 2022

Early Access

Join our first cohort of life sciences partners.

We're working with a small group of pharma and biotech companies before general availability. Early access partners get priority onboarding, direct access to the founding team, and founding-tier pricing locked in permanently.

🔒  We'll respond within 1 business day. Your information is never shared.

Overcoming Common Challenges in Biotech Data Analytics

May 25, 2025

Understanding the Landscape of Biotech Data Analytics

Biotech data analytics is an ever-evolving field that offers immense potential for groundbreaking discoveries. However, navigating the complex landscape of big data in biotechnology can present several challenges. From data integration to ensuring data security, the obstacles can be daunting. Yet, with the right strategies and technologies, these challenges can be effectively overcome, paving the way for innovation and advancement.

Data in biotech comes from various sources, including clinical trials, laboratory experiments, and genomic sequencing. Integrating these diverse data types into a cohesive and usable format is often the first major hurdle. Efficient data integration requires advanced algorithms and robust software solutions capable of handling heterogeneous data formats and ensuring seamless interoperability.

data integration

Ensuring Data Quality and Accuracy

Another significant challenge is maintaining the quality and accuracy of the data being analyzed. Inaccurate or incomplete data can lead to misguided conclusions and ineffective decision-making. Ensuring data integrity involves rigorous validation processes and regular audits to detect and correct errors. Employing machine learning techniques can also enhance data accuracy by identifying patterns and anomalies that might otherwise go unnoticed.

Moreover, data preprocessing steps like cleaning, normalization, and transformation are crucial in refining raw data into a form fit for analysis. These processes help in eliminating noise and ensuring that the data is both reliable and relevant for the intended analytical purposes.

Optimizing Data Storage and Management

As the volume of biotech data continues to grow exponentially, efficient data storage and management have become more critical than ever. Traditional storage solutions often fall short in handling the sheer scale and complexity of biotech datasets. Cloud-based solutions offer scalable storage options that are both cost-effective and flexible, allowing organizations to manage large datasets without physical constraints.

cloud storage

In addition to storage, proper data management practices are essential to ensure easy access and retrieval of information. Implementing robust database management systems and utilizing metadata can significantly enhance data discoverability and usability.

Addressing Data Security Concerns

With the rise in cyber threats, ensuring the security of sensitive biotech data is paramount. Data breaches can have severe consequences, including loss of intellectual property and damage to organizational reputation. Implementing stringent security measures such as encryption, access controls, and regular security audits is crucial in safeguarding data integrity.

Furthermore, compliance with regulations such as HIPAA and GDPR is essential for organizations dealing with personal health information. Ensuring regulatory compliance not only protects patient privacy but also fosters trust among stakeholders.

data security

Enhancing Data Analysis with Advanced Tools

The complexity of biotech data requires sophisticated analytical tools capable of extracting meaningful insights. Advanced technologies like artificial intelligence (AI) and machine learning (ML) offer powerful capabilities for analyzing vast datasets efficiently. These tools can identify trends, predict outcomes, and provide actionable insights that drive innovation.

Moreover, visualization tools play a vital role in interpreting complex data sets by presenting information in an accessible and understandable format. Effective visualizations enable researchers to communicate findings clearly and facilitate informed decision-making.

Fostering Collaboration Across Disciplines

The interdisciplinary nature of biotech data analytics necessitates collaboration among experts from various fields, including biology, computer science, and statistics. Fostering a collaborative environment encourages knowledge sharing and promotes innovative problem-solving approaches.

Establishing cross-functional teams and leveraging collaborative platforms can enhance communication and streamline workflows. By working together, diverse teams can overcome challenges more efficiently and accelerate the pace of discovery in biotechnology.

team collaboration

In conclusion, while there are numerous challenges in biotech data analytics, they are not insurmountable. With strategic planning, technological advancements, and collaborative efforts, these obstacles can be transformed into opportunities for growth and innovation in the biotech industry.