AI/ML for Pharmaceutical & Life Sciences
Accelerate drug discovery, optimize clinical trials, and automate pharmacovigilance — with ML pipelines that meet FDA and EMA validation requirements.
Why pharma teams choose us
GxP-ready ML with full validation support
FDA/EMA validation support
IQ/OQ/PQ documentation, GAMP 5 compliance, model validation reports, and 21 CFR Part 11 electronic records. We help you through regulatory submission.
Reproducible ML pipelines
Version-controlled data, models, and code. Deterministic training runs, containerized environments, and complete lineage tracking for audit trails.
Biotech expertise
Team includes ML engineers with pharma domain knowledge: SMILES, protein folding, molecular dynamics, and clinical trial design.
IP protection & security
On-prem or VPC deployments, no third-party model APIs, encrypted data lakes, and SOC 2 compliant infrastructure. Your IP stays yours.
Solutions for pharma & life sciences
From molecule design to post-market surveillance
Drug Discovery & Molecular Design
Generative models for de novo molecule design, property prediction, and retrosynthesis. Graph neural networks, transformers, and reinforcement learning for hit-to-lead optimization.
- • Molecular property prediction (ADMET, toxicity, solubility)
- • De novo molecule generation (VAE, GAN, diffusion models)
- • Protein-ligand binding affinity (docking score prediction)
- • Retrosynthesis planning (synthesis route optimization)
Impact: 10-20× faster lead candidate identification
Clinical Trial Optimization
Patient recruitment, site selection, protocol optimization, and endpoint prediction. Reduce trial duration and improve success rates with predictive analytics.
- • Patient eligibility screening (EHR matching to inclusion/exclusion)
- • Site selection & enrollment forecasting (geographic analysis)
- • Protocol deviation detection (real-time monitoring)
- • Endpoint prediction (survival analysis, time-to-event modeling)
Impact: 30-40% faster patient enrollment, 25% cost reduction
Pharmacovigilance & Adverse Event Detection
Automated AE signal detection from clinical notes, social media, and FAERS data. NLP for case report processing and regulatory submission.
- • Adverse event extraction (clinical notes, patient forums)
- • Signal detection (disproportionality analysis, Bayesian methods)
- • Case report automation (E2B formatting, MedDRA coding)
- • Literature monitoring (PubMed surveillance for safety signals)
Impact: 60-70% reduction in case processing time
Regulatory Document Intelligence
Extract, classify, and search regulatory submissions. NLP over CTD, eCTD, SDTM, and ADaM datasets for FDA/EMA filings.
- • Regulatory document search (RAG over submission history)
- • Label comparison (SmPC, USPI automated delta analysis)
- • Clinical study report extraction (efficacy/safety tables)
- • Submission readiness checks (completeness validation)
Impact: 50% faster regulatory document review and preparation
Manufacturing & Quality Control
Process optimization, anomaly detection, and predictive maintenance for pharma manufacturing. Computer vision for visual inspection.
- • Batch quality prediction (process parameters to yield)
- • Visual inspection automation (defect detection, contamination)
- • Predictive maintenance (equipment failure prediction)
- • Process optimization (DoE + Bayesian optimization)
Impact: 15-20% yield improvement, 40% reduction in defects
ML for faster R&D cycles
Real impact across the pharma value chain
10-20×
Faster molecule screening
30-40%
Faster trial enrollment
60-70%
AE processing time saved
15-20%
Manufacturing yield gain
Technology stack for pharma
Specialized tools for life sciences R&D
Cheminformatics
RDKit, DeepChem, OpenMM, PyMOL, Schrödinger
ML Frameworks
PyTorch, TensorFlow, DGL, PyG, AlphaFold
Clinical Data
CDISC SDTM, ADaM, CDASH, HL7 FHIR
BioPharma NLP
BioBERT, PubMedBERT, MedCAT, scispaCy
Ready to explore AI for your business?
Book a 30‑min consult. No obligations.