Maxis AI

A big thank you to PHUSE for bringing together the clinical data community at PHUSE US Connect 2026. It was a great experience connecting with peers across the clinical data and biostatistics community. We truly appreciate everyone who visited us and engaged in meaningful conversations throughout the event. The presentations and discussions were highly insightful and engaging, reflecting the growing focus on AI, governance, and innovation in clinical research. We’re sharing a few moments from the event. 👉 If you’re unable to meet us in person, book a virtual meeting with us: https://lnkd.in/gV5YrugR Nicole Powell, MBA | Rajesh Hagalwadi | Laxmiraju Kandikatla, CQA | Ankur Goel #PHUSE #PHUSEUSConnect #ClinicalResearch #AgenticAI #Biostatistics #DataScience #MaxisAI

"The next phase of study startup will be defined by AI-driven workflows - not fragmented, sequential processes.” As Varsha highlights, the shift is already underway - toward faster, more coordinated execution across study startup. With just 1 day to go, this is your opportunity to understand how leading teams are using Agentic AI to reduce delays, improve efficiency, and move from protocol to patient faster. 📅 March 31 | 11 AM EST Join Varsha Kishore and Rachna Saralkar, MD, MS as they share practical perspectives on tackling study startup bottlenecks and accelerating timelines. ⏳ 𝐋𝐚𝐬𝐭 𝐜𝐡𝐚𝐧𝐜𝐞 - 𝐝𝐨𝐧’𝐭 𝐦𝐢𝐬𝐬 𝐢𝐭: https://lnkd.in/gy7Z_nya #ClinicalTrials #ClinicalOperations #StudyStartup #AgenticAI #DrugDevelopment #WebinarAlert #MaxisAI

Clinical trials have improved visibility. Execution capacity remains the constraint. Dashboards, risk monitoring platforms, and analytics systems now provide near real-time insight into study performance. But identifying a problem is not the same as resolving it. As study complexity increases, most delivery models still scale through headcount: More studies → More people This creates structural pressure: Workflow backlogs accumulate Timelines become harder to stabilize Costs scale linearly with resources Specialized talent becomes a bottleneck The industry has solved for visibility. Execution at scale remains unresolved. This is where the concept of an Agentic CRO becomes relevant. An Agentic CRO introduces a supervised execution layer across clinical workflows including: Study startup execution Site & patient operations Data management & query resolution Statistical programming Medical review & safety workflows Regulatory & reporting execution Structured operational work is executed across systems, while experts supervise, validate, and intervene where required. The objective is not autonomy. The objective is reliable, governed execution at scale. Put simply: An Agentic CRO is a clinical service model where: Intelligent systems execute structured workflows Experts supervise and validate outcomes Work happens across existing clinical systems Every action remains traceable and governed The shift is fundamental: From headcount scaling → to execution scaling If execution capacity within your clinical workflows is under evaluation, you can explore how this model applies to your environment. 👉 Talk to Experts: https://hubs.ly/Q048zFLc0 #AgenticCRO #ClinicalTrials #AIWorkforce #DrugDevelopment #MaxisAI

"Study startup remains one of the most expensive and least improved phases of clinical trials.” In this video, Dr. Rachna Saralkar shares why delays from contract negotiations to site activation continue to impact timelines and cost teams up to $55,000 per day. If this sounds familiar, this is a conversation you shouldn’t miss. 📅 March 31 | 11 AM EST Join Rachna Saralkar, MD, MS Saralkar from Flourish Research and Varsha Kishore from Maxis AI as they discuss how AI-driven workflows are helping clinical teams reduce delays and accelerate study startup. ⏳ 𝐎𝐧𝐥𝐲 𝐚 𝐟𝐞𝐰 𝐝𝐚𝐲𝐬 𝐥𝐞𝐟𝐭 - 𝐬𝐞𝐜𝐮𝐫𝐞 𝐲𝐨𝐮𝐫 𝐬𝐩𝐨𝐭 𝐧𝐨𝐰: https://hubs.ly/Q048rz1V0 #ClinicalTrials #ClinicalOps #StudyStartup #DrugDevelopment #AgenticAI #WebinarAlert #MaxisAI

Day 2 at PHUSE US Connect 2026 was all about meaningful conversations and real-world applications of AI in clinical research. From engaging session discussions to insightful interactions at Booth #10, it was great to see strong interest in agentic AI, multi-agent workflows, and risk-driven governance frameworks. Looking forward to Day 3 and continuing the conversation with the PHUSE community. If you’re unable to meet us in person, book a virtual meeting with us: https://lnkd.in/gV5YrugR Nicole Powell, MBA | Rajesh Hagalwadi | Ankur Goel | Laxmiraju Kandikatla, CQA #PHUSE #ClinicalResearch #ClinicalData #AgenticAI #Biostatistics #DataScience #MaxisAI

Day 1 at PHUSE US Connect 2026 wrapped with great conversations, strong engagement, and insightful discussions around AI in clinical research. From our presentation sessions to the poster showcase and booth interactions, it was great connecting with the PHUSE community on topics like agentic AI, validation, and risk-driven oversight. We’re back for Day 2 today - looking forward to more sessions and conversations. 📍 Booth #10 👉 Book Your Meeting in Advance: https://lnkd.in/gV5YrugR Nicole Powell, MBA | Rajesh Hagalwadi | Ankur Goel | Laxmiraju Kandikatla, CQA #PHUSE #PHUSE2026 #ClinicalResearch #AgenticAI #Biostatistics #DataScience #MaxisAI

We’re all set at PHUSE US Connect 2026. The Maxis AI team is kicking off at Booth #10 - looking forward to connecting with peers across clinical data, biostatistics, and AI. If you’re here, stop by to explore how we’re enabling agentic AI for clinical trials - from validation and governance to scalable execution. #PHUSE #PHUSE2026 #ClinicalResearch #AgenticAI #ClinicalTrials #MaxisAI

Clinical trials are no longer run from a single place. A typical study today spans: 1. Multiple sites 2. Several CRO partners 3. Distributed clinical teams 4. Multiple technology platforms The operational footprint has expanded dramatically. What used to be a single operational stream is now a network of moving parts. When something slips like enrollment delays, data backlogs, startup bottlenecks; the real challenge is rarely visibility. It is coordination. Who follows up? Which team owns the next action? How quickly can the issue be stabilized? This is why the concept of a Control Tower for Clinical Trials exists. But the next evolution of this concept is already here: Agentic AI-powered Control Towers. Instead of humans manually tracking, escalating, and coordinating, AI Agents constantly monitor operational signals, detect risks, trigger follow-ups, and orchestrate next actions across distributed teams. It is not another reporting dashboard. It is a central operational coordination layer across the study portfolio. A Control Tower is not just about coordination. It is about controlling how execution unfolds in real time. Timeline stability Quality consistency Workflow throughput Risk resolution Cost discipline This is where coordination becomes control. A well-designed Control Tower enables teams to: 1. Monitor operational signals across studies 2. Coordinate follow-up actions across stakeholders 3. Escalate emerging risks early 4. Stabilize execution across the trial network The goal is not simply to watch studies. It is supervised execution supported by Agentic AI. In simple terms: A Control Tower for Clinical Trials is a centralized operational hub that: 1. Monitors trial activity across sites and systems 2. Uses AI agents to coordinate follow-up actions 3. Escalates risks before they become delays Its purpose is straightforward: Keep distributed trials operationally aligned with intelligent agents doing the heavy lifting. #AgenticAI #ClinicalTrialExecution #ClinicalOperations

Leadership journeys are often shaped by the people who defined strength and purpose through their actions. In this edition of Women Who Shape Leadership, Rajesh Majji, Vice President, Product & Technology at Maxis AI, reflects on the woman who had the greatest influence on his life - his grandmother. Her resilience, humility, and belief in education reflect the spirit of #GiveToGain - enabling others to grow and become more than what circumstances define. Swipe through to read Rajesh’s reflection. #LeadershipStories #WomenWhoInspire #WomenInLeadership #LeadershipMatters #MaxisAI

𝐖𝐡𝐚𝐭 𝐃𝐞𝐟𝐢𝐧𝐞𝐬 𝐚𝐧 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐎𝐒 𝐟𝐨𝐫 𝐏𝐡𝐚𝐫𝐦𝐚? Pharma does not lack capability. It lacks coordinated execution. Study design Clinical operations Data management Medical monitoring Biostatistics Regulatory submission Each function delivers outcomes. But execution across them remains fragmented. The result: Delays Backlogs Variability Rework An Agentic OS for Pharma changes this. It orchestrates execution across functions - ensuring outcomes are delivered with consistency, speed, and control. In simple terms:- From functional silos to orchestrated execution. #AgenticAI #AgenticOS #ClinicalTrials #Pharma #MaxisAI