The life sciences industry is undergoing a rapid transformation, driven by scientific advancements, increasing regulatory complexities, and the growing demand for faster drug development. As organizations strive to accelerate research and development (R&D), they face mounting challenges across their operations including clinical trials, pharmacovigilance and regulatory document management.

Indeed the industry statistics suggest that 80% of clinical trials fail to meet enrollment timelines while 66% of protocols require substantial amendments due to evolving regulations or trial design changes. (Medidata Solutions. On the other hand 50% of serious adverse drug reactions (ADRs) are detected post-market, increasing patient safety risks.

Generative AI (Gen AI) presents a transformative opportunity to automate labor-intensive tasks, extract insights from vast datasets, and streamline decision-making. Quantiphi, an AI-first digital engineering company and an NVIDIA Elite Service Delivery Partner, is at the forefront of integrating Generative AI into life sciences. By leveraging the NVIDIA AI Enterprise software platform, they offer customizable industry solutions to streamline clinical operations, strengthen regulatory compliance while enhancing patient safety.

Quantiphi Gen AI Solutions Accelerated by NVIDIA AI Enterprise

Clinical Trial Patient Cohort Generation
Patient recruitment remains one of the biggest hurdles in clinical trials, with 19% of trials failing due to low enrollment. The process of manually reviewing Electronic Health Records (EHRs) against protocol inclusion and exclusion criteria is slow, inconsistent, and prone to bias, often leading to patient misclassification or delays in enrollment. This not only impacts trial timelines but also contributes to rising costs and underrepresentation of diverse populations in research.

Quantiphi’s Clinical Trial Patient Cohort Generation solution automates patient screening by analyzing EHRs and cross-referencing them with trial eligibility criteria. By leveraging LLMs to interpret clinical data, the solution ranks eligible patients into cohorts, enabling faster and more informed recruitment decisions. It seamlessly integrates with Clinical Trial Management Systems (CTMS) ensuring real-time updates, while AI-driven cohort ranking optimizes patient selection. This results in accelerated recruitment, improved trial diversity, and reduced operational burden on clinical teams.

To learn more, watch our demo:
Clinical Protocol Writer
Drafting a clinical trial protocol is a complex and time-intensive process that requires inputs from multiple stakeholders. On average, protocol development takes several months, with frequent revisions due to incomplete or inconsistent data. This leads to significant delays in trial initiation and increases the administrative burden on clinical operations teams. Moreover, ensuring compliance with global regulatory standards adds another layer of complexity, further slowing down the approval process.

Quantiphi’s Clinical Protocol Writer automates protocol generation by extracting and synthesizing information from investigator brochures, trial designs, historical protocols and from external systems including PubMed and clinicaltrilas.gov. Utilizing fine-tuned LLMs for clinical text generation, the solution creates structured, pre-filled drafts with contextualized content for each section, while significantly eliminating manual efforts for medical writers. By reducing protocol development time, the solution enables faster trial initiation and minimizes errors, improving overall operational efficiency.
Intelligent Clinical Document Processing with LLMs
Clinical trials generate vast volumes of regulatory and operational documents, from investigator brochures to site reports and compliance filings. Managing these documents manually is inefficient, with studies showing that 50% of trial data contains inconsistencies, increasing regulatory risks and delaying approvals. Ensuring audit readiness and maintaining compliance across multiple jurisdictions further compounds the challenge, leading to bottlenecks in document workflows.

Quantiphi’s Clinical Document Processing solution automates document classification, metadata extraction, and quality validation using LLMs and multi-modal AI. The platform intelligently categorizes documents, extracts key metadata, and flags inconsistencies for human review. Automated quality checks and human-in-the-loop workflows enhance validation, while a real-time dashboard provides complete visibility into document status. This streamlines document processing, ensures compliance, and improves audit readiness, reducing manual workloads and expediting regulatory submissions.

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Pharmacovigilance & Adverse Event (AE) Management
Pharmacovigilance teams are responsible for monitoring and reporting adverse events (AEs) to ensure patient safety, but manual case processing leads to delays and underreporting. With millions of scientific articles, case reports, and patient records published annually, extracting meaningful insights and ensuring timely reporting is a significant challenge. Regulatory agencies require stringent reporting timelines, and delays in AE detection can result in non-compliance, financial penalties, or even patient harm.

Quantiphi’s Pharmacovigilance Platform (QSafe) leverages LLMs to automate AE identification, causality assessment, and regulatory reporting. The platform scans medical literature, case reports, and safety databases to detect potential AEs, classifies their severity, and generates structured reports aligned with regulatory requirements. Built-in workflows for case assignment, review, and approval ensure seamless pharmacovigilance operations, while a centralized dashboard provides real-time tracking of AE cases. This solution enhances AE reporting accuracy, accelerates regulatory submissions, and improves overall patient safety.

To learn more, watch our demo:

NVIDIA Technology Stack: The Backbone of Clinical Innovation

These Gen AI -driven solutions are bullet using the NVIDIA technology stack ensuring scalability, efficiency, and high-performance execution.

NVIDIA NeMo – A powerful framework for building and fine-tuning domain-specific Large Language Models (LLMs), enabling accurate clinical text generation, cohort analysis, and adverse event detection.
NVIDIA NIM microservices – Optimized inference microservices that accelerate AI model deployment, ensuring real-time decision-making in clinical operations and regulatory compliance.
NVIDIA Multimodal PDF Data Extraction Blueprint – A blueprint, powered by NeMo Retriever, for extracting structured insights from complex clinical documents, streamlining regulatory reporting and compliance.

Conclusion

Quantiphi, in partnership with NVIDIA, is revolutionizing life sciences by harnessing Generative AI to transform clinical trials, document management, and pharmacovigilance. By integrating LLMs and advanced automation, these solutions eliminate inefficiencies, enhance compliance, and accelerate drug development.

Together, Quantiphi and NVIDIA are driving AI-powered transformation across the life sciences industry, enabling organizations to optimize operations, accelerate innovation, and improve patient outcomes. As Generative AI continues to reshape the future, this collaboration ensures that life sciences companies can stay ahead with intelligent, scalable, and efficient AI-driven solutions.

Meet Quantiphi at GTC’25 (booth #2308) or Get in touch with our experts to explore how AI-powered Digital Health Agents can elevate your healthcare operations.

As you conclude your reading, we invite you to explore Kimberly Powell’s (VP, Healthcare & Life Sciences, NVIDIA) session on “Digital and Physical AI Helps Write a New Chapter in Medicine” at NVIDIA GTC 2025.