GxP

Life Sciences

All that accelerates discovery to approval. Optimize trials, automate submissions, and scale pharmacovigilance—safely and compliantly for mid-market biotech, med-device, and CROs.

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R&D

Pre-clin

Trials

Submissions

GxP

Value

Overview

Industry Overview & Outlook

Mid-sized biopharma and device firms are compressing cycle times from protocol to submission. AI is moving from point pilots to end-to-end workflows across study start-up, monitoring, and safety.

Over the next 2–5 years, expect AI copilots for protocol design, site selection, eSource ingestion, and continuous PV monitoring—driving probability of technical and regulatory success.

Speed & Cost Pressure

Rapid site setup, high demand resource issues.

Regulatory Rigor

ALCOA+, data lineage, and audit trails across GxP systems.

AI Opportunity

Study start-up, monitoring, and audit-ready intelligence in one view.

Key Stats

–20–35%

study cycle time

–25–45%

sponsor effort in SDV/RBM

+10–18%

enrollment velocity

–15–25%

protocol amendments

–20–30%

query load

+5–10pts

submission quality

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Key Trends

AI-Assisted Protocol Design

Feasibility checks, criteria simulation, and amendment risk.

Decentralized & Hybrid Trials

eConsent, ePRO/eCOA, and remote monitoring at scale.

eSource & RAG for GxP

Structured extraction and retrieval for SOPs, labels, and literature.

Explainable Compliance

ALCOA+ evidence, change logs, and audit-ready outputs.

RBQM & Anomaly Detection

Central signals flag risk signals for targeted SDV/SDR.

Synthetic Control Arms & RWE

External comparators and fit-for-purpose RWD to augment trials.

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CX Challenges

Clinical & Regulatory Challenges

Slow Study Start-Up

Site activation, contracting, and document collection drag timelines.

Enrollment Friction

Inclusion/exclusion filters and travel burden hurt accrual.

Monitoring Overhead

100% SDV/SDR costs without clear risk targeting.

Submission Rework

Inconsistent modules and missing references delay approvals.

PV & Safety Scale

Case intake, follow-ups exceed campaign capacity.

Data Silos & Traceability

Disconnected eSource, lab, and EDC hinder lineage and ALCOA+.

Learn how we fix them

Solutions

AI Solutions for Life Sciences

Speed

Quality

Compliance

Study Start-Up Orchestration

Maps to: SSU delays.

Automate contracts, document chase, and site packet QC with copilots.

–20–45% SSU time

↑ site readiness

Recruitment & eConsent

Maps to: Enrollment friction.

Eligibility screening, travel assist, and digital consent flows.

+10–18% accrual

↓ screen fail

RBQM & Central Monitoring

Maps to: Monitoring overhead.

Signal detection guides targeted SDV/SDR and remote reviews.

–25–40% SDV

↓ query rate

Submission Copilot (eCTD)

Maps to: Rework.

Draft/validate modules, cross-reference citations, and change logs.

+ quality

↓ rounds

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Case Studies

Mid-Stage Biotech

Challenge: Slow SSU and high screen failure rates across ~25 sites.

AI Solution: Start-up orchestration + eligibility copilot + RBQM central monitoring.

–28%

SSU time

+14%

accrual

–22%

SDV effort

Med-Device Company

Challenge: Manual safety case handling and slow trend detection for complaints.

AI Solution: PV copilot with intake triage, literature/social scan, and signal alerts.

–31%

case time

+8pts

signal recall

–24%

backlog

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