Maxis AI at PHUSE US Connect 2026 | Advancing Clinical Data Science with Agentic AI

Advancing Clinical Data Science with Agentic AI

At PHUSE US Connect 2026, Maxis AI showcases how Agentic AI transforms clinical data workflows for statistical programmers, data scientists, and health data professionals. From AI-driven validation frameworks and risk-stratified governance to problem-first autonomous automation, our solutions help sponsors, CROs, and biotechs accelerate submissions while improving data integrity and operational efficiency.

What We’re Showcasing at SCOPE 2026:

DTect AI – Agentic Anomaly Detection & Risk Intelligence: Maxis AI’s Agentic AI capability for clinical data quality – combining real-time anomaly detection, accelerated review workflows, and proactive risk management, purpose-built for statistical programmers and data scientists.

Statistical Computing Environment (SCE) – Agentic Programming: Multi-language support (SAS, R, Python, Julia) with Agentic AI for CDISC-compliant dataset generation, interactive data review (RShiny, Tableau, Python), and centralized workflows for blinded and unblinded studies.

Risk-Based Quality Management (RBQM) – Agentic Quality Oversight: Continuous, tiered risk assessment powered by autonomous AI agents using ISO, ICH Q9, and FMEA frameworks – identifying, prioritizing, and recommending mitigation strategies across all trial activities.

Verticalized Agentic AI Platform: Purpose-built autonomous agents for end-to-end clinical data workflows that learn from your standards, independently execute complex tasks across data review, validation, and submission preparation, and collaborate intelligently with human experts.

Featured Presentations:

ML04: Validation Strategies for Agentic AI Platforms in GxP-Regulated Clinical Data Environment
Monday, March 23 | 2:00 PM – 2:30 PM | San Antonio Room
Learn industry-validated frameworks and best practices for validating agentic AI platforms operating within GxP-regulated clinical data environments.

ML05: Performance-Driven Risk Oversight for AI Agents in Clinical Research
Monday, March 23 | 2:30 PM – 3:00 PM | San Antonio Room
Learn how performance metrics drive risk oversight for AI agents in clinical research – enabling proactive quality management, continuous improvement, and accountability across regulated data environments.

ML36: Risk-Driven AI Oversight in Clinical Research: A Tiered Framework Using ISO, ICH Q9 and FMEA
Tuesday, March 24 | 9:00 AM – 9:30 AM | San Antonio Room
Discover Maxis AI’s tiered framework for risk-driven AI oversight – integrating international standards (ISO, ICH Q9) with proven risk methodologies (FMEA) for comprehensive, scalable governance of AI systems in clinical research.

AS12: Orchestrating Multi-Agent Workflows for Complex Trial Data Integration
Tuesday, March 24 | 9:30 AM – 10:00 AM | Sabine Room
See how Agentic AI orchestrates multiple autonomous agents to handle complex trial data integration workflows – improving data quality, reducing manual intervention, and accelerating submission timelines across multi-source datasets.

AS23: Problem-First Agentic AI – Transforming Statistical Computing with Purposeful Automation
Tuesday, March 24 | 5:00 PM – 5:15 PM | Sabine Room
Learn Maxis AI’s problem-first approach to Agentic AI – where autonomous agents are designed to solve specific statistical computing challenges with purposeful, GxP-compliant automation rather than generic AI adoption.

PP06: The SMART+ Framework for AI Systems
Wednesday, March 25 | 5:30 PM – 7:00 PM (Poster Session) | Rio Grande
About the SMART+ Framework: The SMART+ Framework introduces a streamlined taxonomy tailored for Clinical Research – integrating Safe, Monitored, Accountable, Reliable, and Transparent (SMART) principles.

Connect with Us:

Fill out the form to meet Maxis AI Team at Booth #10 to see how our Agentic AI is moving clinical data science from reactive automation to proactive, intelligent decision-making.

Meet Our Experts:

Nicole Powell

Senior Vice President, Business Development

Nicole, a strategic leader with over 17 years of experience in the clinical research industry, has consistently driven transformative revenue growth across diverse markets. Her expertise lies in building strong partnerships and steering corporate strategies that align with evolving industry needs. At Maxis AI, Nicole is excited to bring her insights and passion for collaboration to expand the reach of Maxis AI’s Clinical Data Analytics Platform, helping clients streamline trials and achieve their objectives. Nicole recently led business development and marketing at SDC, where she pioneered growth initiatives and contributed to shaping the future of clinical trial technology. An experienced speaker, Nicole has presented at numerous industry conferences on tech-driven innovation in clinical research. She holds a BA from the University of Texas San Antonio and an MBA from Baylor University. Based in Virginia, Nicole enjoys golfing, exploring new destinations, and karaoke in her free time.

Ankur Goel

Vice President, Strategic Accounts

Ankur has over 20 years of experience in clinical strategy, advisory, consulting, and solutioning in SAAS and functional services. His expertise spans across clinical data management, statistical programming, biostatistics, data standardization, clinical ops, and digital transformation for 1000’s of clinical trials.

Rajesh Hagalwadi

Director, Clinical Data Solutions

Rajesh is a PMP- and CSM-certified professional who brings over 15 years of experience implementing eClinical systems within the life sciences industry. His expertise includes pre-sales engineering, product advocacy, solution implementation, computer system validation (CSV), and end-user training. He frequently collaborates with account executives to develop strategic account plans, conduct client discovery, and deliver impactful presentations that showcase the technological and business value of Maxis AI.

Marni Romano

Director, Business Development

With 17 years of experience in scientific sales, Marni Romano is a dynamic leader in business development. Armed with a background in biology and a master’s in biotechnology, she combines scientific acumen with a problem-solving mindset to help organizations unlock the full potential of their research and development efforts. Marni’s passion lies in building trust-driven partnerships, ensuring clients leverage Maxis AI’s cutting-edge solutions for streamlined clinical trials and data-driven decision-making. Her commitment to integrity, innovation, and collaboration makes her a strategic ally for organizations navigating the complexities of clinical research.

Laxmiraju Kandikatla, MPharm, CQA

CSV Lead

Laxmiraju Kandikatla brings over 13 years of experience in life sciences, pharmaceutical, and clinical research sectors to his role as CSV Lead at Maxis AI. He holds a master’s degree in Pharmaceutical Sciences (M. Phar, NIPER) and is an ASQ-Certified Quality Auditor (CQA). In his role at Maxis AI, Laxmiraju leads the design and implementation of validation and compliance frameworks for systems used in clinical research and has hands-on experience in validating systems across GAMP 5 Categories (3, 4, and 5). He works directly with customers during implementation, aligning validation and compliance activities to ensure smooth delivery. He has extensive knowledge of GxP regulations, including 21 CFR Part 11, EU Annex 11, and FDA guidance. He is the author of “A Risk-Based Framework for Human Oversight in AI“, through which he advances ethical assurance frameworks centered on fairness, accountability, and transparency in AI Systems.