Clinical documents are not AI-ready by default | Adlib @ BIO 2026
LLMs hallucinate up to 64% of the time on medical case data without safeguards. Adlib is the document accuracy layer that makes your clinical, regulatory, batch, and RWE workflows AI-ready and audit-proof.
The problem with AI in pharma & biotech
AI hallucinations on clinical data are not a model problem. They are a data quality problem.
Before your LLM can be trusted, your documents have to be. Most aren't.
MIT research found that when AI models hallucinate, they use more confident language than when providing accurate information: 34% more likely to say "definitely," "certainly," or "without doubt." In regulated clinical environments, confident-sounding fabrications are the most dangerous kind.
The root cause is upstream, not in the model: garbage-in, garbage-out. When clinical documents are unstructured, non-searchable, or inconsistently formatted, LLMs fill gaps with plausible-sounding fabrications. Structured, validated document inputs reduce hallucination rates by up to 33% with prompt-based mitigation alone.
How Adlib solves this
The document accuracy layer for life sciences AI
Adlib sits upstream of your core systems, LLMs, and RAG pipelines, transforming messy, multi-format clinical content into structured, validated, audit-ready data before AI ever touches it.
1. Multi-format normalization
Ingests 300+ document types (PDFs, scanned CRFs, CAD, emails, lab reports) and normalizes them into consistent, machine-readable structure with fidelity-preserving rendering and advanced OCR.
2. Multi-LLM comparison & voting (Adlib Accuracy Score)
Runs extractions across multiple LLMs simultaneously, cross-checks results via confidence scoring and voting algorithms, and routes low-confidence documents to human review before they enter downstream systems.
3. Validation against compliance rules
Checks documents against your organization's regulatory rules, flagging exceptions before they reach submissions. Every step is logged for SOC 2, HIPAA, FDA 21 CFR Part 11, and GxP audit trails.
4. PrecisionPath for life sciences
Pre-built accuracy pipelines for clinical operations, regulatory submissions, batch release, and RWE — packaged with extraction models, prompts, and integration starters for eTMF, Veeva, RIM, QMS, and MES systems.
Value by business area
Where Adlib delivers for CROs and sponsors
Select a business area to see specific challenges, outcomes, and proof points.
Ensure clinical data integrity from trial initiation to eTMF closeout
CROs and sponsors handle thousands of CRFs, ICFs, monitoring reports, IRB approvals, and GCP documents per trial. When these enter AI workflows in unstructured form, hallucination risk and compliance exposure multiply. Adlib auto-ingests, standardizes, and validates trial documents at scale, ensuring audit-readiness without expanding headcount.
✓Auto-ingestion and validation of CRFs, ICFs, site reports, and TMF documents
✓Structured extraction of subject IDs, adverse events, and critical endpoints for downstream AI
✓Real-time eTMF integration, documents processed in 15 seconds vs. hours manually
✓8,500+ work hours saved annually at a leading CRO supporting 85% of FDA-approved drugs
Eliminate FDA/EMA rejections with compliant, submission-ready document assembly
Regulatory submissions fail when source documents (NDAs, BLAs, INDs, CSRs) have format inconsistencies, broken structure, or missing validation. Adlib auto-assembles submission packages with PDF/A compliance, bookmarks, ToC, and field validation baked in, so your content arrives defensible on first submission.
✓Automated smart assembly and validation of NDA, BLA, and IND packages
✓PDF/A rendering, bookmarks, citation anchors, and format validation before submission
✓$1.7M annual savings at one CRO from reduced rejections and rework elimination
✓Integration with Veeva, RIM, and eCTD publishing tools, no rip-and-replace required
Accelerate batch record processing with AI-ready, compliant EBRs
Batch Manufacturing Records and Electronic Batch Records are among the most document-intensive and audit-sensitive workflows in pharma. Manual processing creates audit exposure, delayed batch release, and rising overhead. Adlib automates formatting, metadata validation, and distribution of batch documentation while feeding structured data into QMS, MES, and ERP systems.
✓Automated EBR assembly, validation, and compliant PDF generation for batch delivery
✓Structured extraction of batch data into QMS, MES, and ERP for real-time updates
✓ICH and GMP formatting compliance enforced automatically, no manual rework
✓Instantly searchable batch records for faster inspection response and audit readiness
Make real-world evidence and adverse event data defensible for regulators
Real-world evidence programs and safety reporting depend on extracting accurate, traceable data from complex, multi-format sources, EHRs, claims, lab reports, adverse event narratives. When LLMs process unstructured documents without an accuracy layer, fabricated safety signals or missed adverse event details create serious regulatory and patient safety risk. Adlib structures and validates these inputs before AI ever acts on them.
✓Structured extraction of adverse event narratives, safety reports, and follow-up documents
✓LLM-based PII/PHI redaction before data leaves the document processing layer
✓Citation-anchored chunking ensures every AI-generated insight is traceable to source documents
✓Audit trails and chain-of-custody logging for every extracted value, defensible by design
Join Us for an Exclusive Executive Dinner | June 23, San Diego
An invitation-only evening for senior life sciences leaders, hosted by Kristen Sauter and Mike Chasteen
On the evening of June 23, Adlib will host a small, invitation-only Executive Dinner for 8–10 senior leaders from leading life sciences organizations. The conversation will focus on one of the most pressing challenges in the industry: how to operationalize AI across highly complex, regulated document workflows, and what it takes to make every AI-driven decision defensible to your FDA, EMA, or board.
The dinner will be led by Kristen Sauter, Adlib's new GTM Leader for Life Sciences and a 20+ year veteran of regulatory operations at Deloitte and Takeda, joined by Mike Chasteen, Chief Revenue Officer.
Space is strictly limited. If you are a VP or above in Regulatory Affairs, Clinical Operations, or IT at a life sciences organization and would like to be considered for an invitation, reach out to communications@adlibsoftware.com.
Our Speakers
Benjamin O’Connor
Benjamin O’Connor is a Global Strategic Account Executive at Adlib, partnering with life sciences organizations to bring order to messy, unstructured content and reduce risk in document-heavy workflows. He brings deep life sciences go-to-market experience across eTMF/clinical operations platforms and quality/compliance systems, having held business development roles at TransPerfect Life Sciences, Phlexglobal, and ComplianceQuest. Ben is focused on practical ways to improve submission and information management readiness, by strengthening document accuracy, consistency, and validation upstream.
Bob Mezzadri
Bob Mezzadri is a customer success and retention leader with 30+ years in healthcare technology, focused on helping enterprise customers realize measurable value from their solutions faster. Bob is known for building scalable playbooks and success tooling (like use case libraries and success trackers) and partnering closely with Sales, Product, and Engineering to translate customer goals into outcomes and reduce friction, so teams see adoption, impact, and ROI sooner.
Kunal Bargotra
Kunal is an accomplished Product Owner with a passion for solving real-world problems through innovative product development. He's mastered the art of engaging stakeholders, conducting market research, and devising impactful go-to-market strategies. Kunal will assist Anthony in demonstrating Adlib's new enhancements in a detailed live presentation.
Kristen Sauter
Kristen Sauter leads Adlib's life sciences go-to-market strategy, bringing more than 20 years of regulatory operations, data, and AI expertise from inside the industry. Most recently, she led Deloitte's Regulatory, AI & Data practice for Life Sciences and Health Care. Prior to that, she served as Sr. Director, Global Head of Regulatory Affairs Information Management & Digital Innovation at Takeda, where she built the information management infrastructure supporting global regulatory submissions. Kristen has spent her career at the intersection of regulatory complexity and the technology organizations need to manage it, and joins Adlib to help life sciences leaders build AI they can actually defend.
