AI Drug Discovery for Pharma R&D
Deploy regulated AI for pharma spanning AI drug discovery workflows and trial operations. We accelerate artificial intelligence drug discovery with governance.
- Navigate complex protocols with AI for drug discovery copilots.
- Use AI in drug development agents to reduce manual burden across study startup.
- Keep sensitive drug discovery AI data inside compliant environments with clear governance.
- Move beyond AI drug discovery companies pilots to broad adoption of production-grade services.
R&D AI Stack
GovernedThe R&D Reality: Complex, Regulated, and Overloaded
We understand the unique pressures facing pharma and biotech R&D teams.
What Makes Pharma R&D Different
Multi-year programs with complex protocols, distributed teams, and continuously evolving requirements.
Heavy documentation and evidence requirements—from preclinical through regulatory submissions and beyond.
Coordination challenges between science, clinical operations, regulatory affairs, and external partners.
AI's potential is real, but so are risks: hallucinations, confidentiality breaches, and misinterpretations can have serious consequences.
Sound Familiar?
- We have mountains of protocols, reports, and publications that no one can keep up with.
- Study startup and feasibility processes are slow and manually driven.
- Teams build local spreadsheets and scripts that don't scale or govern well.
- Compliance is wary of generative AI touching regulated content.
Kriv AI focuses on governed AI patterns that respect these constraints.
Who We Work With in Pharma & Biotech R&D
From research leadership to clinical operations and digital teams.
R&D & Clinical Development Leaders
- Heads of R&D, Clinical Development, Translational Medicine.
- Need better visibility, faster insight generation, and less manual friction.
- Want AI that supports, not replaces, expert judgment.
Clinical Operations & Study Teams
- Study start-up, feasibility, and operations managers.
- Coordinate protocols, sites, and timelines under intense documentation load.
- Need automation and copilots that fit into existing tools and SOPs.
Data Science, Analytics & Digital
- R&D data science, AI, and digital transformation teams.
- Already experimenting with LLMs and automation, but need governance and production patterns.
- Want to avoid shadow AI and fragile prototypes.
How Kriv AI Supports Pharma R&D
Our solutions tailored to the unique needs of pharmaceutical and biotech research.
AI Readiness & Governance Assessment
Assess where AI can safely accelerate R&D workflows—from literature synthesis to study operations—while respecting regulatory constraints.
Learn moreAgentic AI & Automation
Design agents for protocol workflows, document routing, checklists, and orchestration around study startup and operations.
Learn moreLLM Fine-Tuning & Custom Models
Tune models on your protocols, internal reports, submissions, and curated evidence to power domain-accurate copilots.
Learn moreMLOps & Governance-as-a-Service
Keep R&D AI services monitored, governed, and explainable—so they can survive audits and leadership scrutiny.
Learn moreAI Governance & Compliance-as-a-Service
Define policies, risk classifications, and approvals for AI in R&D contexts, aligned with your existing QA and regulatory frameworks.
Learn moreExample AI Use Cases in Pharma R&D
Practical applications that address real R&D challenges.
Protocol & Study Document Copilot
LLM-based assistants that help teams navigate protocols, amendments, and SOPs with citations and guardrails.
View use caseLiterature & Evidence Review Assistant
Support systematic-like reviews by helping teams triage, summarize, and connect internal and external evidence.
View use caseStudy Startup & Feasibility Workflow
Agentic workflows to coordinate tasks, documents, and communications around study startup.
View use caseR&D Knowledge Hub Over Internal Reports
Search and Q&A over internal R&D reports, analyses, and meeting notes—within governed boundaries.
View use caseRegulatory & Submission Support Copilot
Assist teams with formatting, cross-references, and consistency checks, while leaving approvals and decisions to humans.
View use caseSignal & Risk Intake Automation
Structured AI-assisted intake of safety or quality signals, with routing to human experts.
View use caseHandling Regulated & Confidential R&D Data
Your scientific IP and clinical data deserve serious protection.
Our Approach to R&D Data
R&D data often touches clinical data, patient information, proprietary science, and confidential IP.
Kriv AI designs deployment patterns that keep these assets in controlled environments—your cloud, your access controls, your audit logs.
Governance extends beyond model behavior to confidentiality and information security, ensuring that AI doesn't become a vector for data leakage.
What This Means in Practice
- Architectures that prioritize your cloud, VPCs, and access controls.
- Patterns for de-identification or minimization when PHI appears in R&D workflows.
- Logging of AI interactions for audit and internal QA.
- Clear boundaries for what AI agents are allowed to access and do.
How We Work with R&D & Clinical Teams
A structured approach that respects the complexity of pharma R&D.
Use Case Discovery & Prioritization
- Workshop with R&D, clinical ops, and compliance to identify high-value, feasible use cases.
- Balance ambition with regulatory and operational realities.
Design & Pilot with Domain Experts
- Co-design workflows and AI behavior with R&D and operations stakeholders.
- Run pilots where human experts stay firmly in control of decisions.
Hardening & Governance
- Harden successful pilots into governed services with monitoring, access control, and documentation.
- Align with your existing QA, validation, and change-control processes.
Scale to the R&D Portfolio
- Extend proven patterns to adjacent teams, studies, or assets.
- Refine governance and playbooks as more use cases come online.
What R&D Leaders Aim to Achieve
Tangible outcomes that matter to pharma and biotech R&D.
Faster, Better-Informed Work
Reduce time spent hunting for information and reconciling documents.
Reduced Manual Overhead
Offload repetitive, documentation-heavy tasks to governed AI workflows.
More Trustworthy AI in R&D
Keep humans in the loop, with guardrails that build trust rather than skepticism.
R&D AI You Can Explain
Be able to show leadership and regulators how AI is used, controlled, and monitored across R&D.
Resources for Pharma & Biotech R&D
Insights, guides, and case studies relevant to R&D teams.
Governed AI Patterns for Pharma R&D Teams
How leading R&D organizations are implementing AI with proper governance and oversight.
View resourceLLM & Agentic Workflows in Regulated R&D Environments
A guide to deploying AI in pharma R&D while maintaining compliance and control.
View resourceDesigning a Protocol Copilot with Guardrails
How one biotech built an AI assistant for protocol navigation with proper human oversight.
View resourceWant AI that actually fits pharma R&D reality?
We help R&D, clinical ops, and compliance teams design governed AI that respects science, regulation, and human expertise.