Accelerate Drug Development with AI That Knows Regulation
Bringing a drug to market costs $2.6B and takes 10-15 years. We build AI that automates regulatory writing, optimizes clinical trial operations, and turns pharmacovigilance from a cost center into a strategic advantage.
Why Drug Development Timelines Keep Growing
Increasing regulatory complexity, trial diversity requirements, and data volumes are stretching pharma R&D budgets beyond sustainability.
Regulatory Writing Bottleneck
A single NDA submission can exceed 100,000 pages. Medical writers spend months on documents that follow predictable patterns.
Patient Recruitment Failures
80% of clinical trials fail to meet enrollment timelines. Poor site selection and narrow eligibility criteria waste millions.
Pharmacovigilance at Scale
Post-market safety monitoring generates millions of adverse event reports. Manual review cannot keep pace with global reporting requirements.
Data Silos Across the Pipeline
Discovery, preclinical, clinical, and commercial data live in separate systems with no unified view of the molecule lifecycle.
Global Regulatory Variation
FDA, EMA, PMDA, and NMPA each have different submission formats, timelines, and requirements for the same drug.
Declining R&D Productivity
Cost per approved drug has doubled every 9 years since 1950. The industry needs fundamentally different approaches to innovation.
AI Across the Drug Lifecycle
From preclinical data analysis to post-market surveillance, we build AI solutions that respect GxP requirements at every step.
Ready to Cut Regulatory Timelines by 50%?
See how AI-powered regulatory writing and trial optimization can accelerate your pipeline.
What Mid-Size Pharma Companies Achieve
Results from biotech and pharma clients with Phase II-IV programs across multiple therapeutic areas.
Where Pharma Teams See ROI
Three areas driving the biggest time and cost savings across the drug development lifecycle.
GxP and Regulatory Compliance
Every AI tool is built for the stringent regulatory requirements of pharmaceutical development.
Why Pharma Teams Choose OpenMalo
We combine deep regulatory domain knowledge with production-grade AI engineering.
Get a Pharma AI Readiness Assessment
Tell us about your pipeline and we will identify where AI can have the biggest impact.
Pharma Success
Biotech Cuts NDA Preparation Time by 50%
A mid-size biotech used AI regulatory writing to prepare their first NDA submission while simultaneously optimizing Phase III enrollment.
The Problem
A rare disease biotech had one shot at NDA submission with limited regulatory headcount and a Phase III trial that was 6 months behind enrollment targets.
Our Approach: We deployed regulatory writing AI to auto-generate CSR sections and CTD modules from clinical datasets, built an enrollment prediction model that identified 12 high-performing backup sites, and automated adverse event intake processing to clear the safety review backlog.
Read Full Case StudyWhat Our Clients Say
“The AI generated our first CSR draft in 3 days. Our team spent their time reviewing and refining instead of writing from scratch.
“We identified a safety signal 4 months earlier than our standard review cycle would have caught it. That changed our risk management plan.
“Their enrollment model pinpointed which sites to activate and which to drop. We hit our recruitment target 2 months ahead of the revised plan.
Frequently Asked Questions
Yes. Every AI model includes GAMP 5-aligned validation documentation, IQ/OQ/PQ protocols, performance specifications, and change control procedures. We support deployment into qualified GxP infrastructure.
Explore Related Industries
Discover how we serve similar verticals with tailored technology solutions and deep domain expertise.
