Overland Park, Kansas, United States
I am an enterprise AI and advanced analytics leader with 17+ years of experience building and scaling predictive ML, GenAI, and agentic AI solutions across life sciences, clinical research, and real-world evidence (RWE). At Thermo Fisher Scientific, I lead enterprise AI strategy, capability development, and platform enablement across two major pillars—Evidera and CRG Digital—driving AI from experimentation to regulated, production-scale impact. Evidera – Predictive Science & RWE Leadership I lead AI initiatives across real-world data and predictive science, with focus areas including diagnosis prediction and delayed diagnosis analytics, social media–derived patient insights, imaging-based ML, patient identification and case-finding algorithms, and risk stratification modeling. Beyond model development, I architect scalable AI platforms (Azure, AWS, Databricks), establish governance and validation frameworks, and ensure regulatory-grade deployment across multi-region environments. CRG Digital – Enterprise AI Transformation Within CRG Digital’s Patient & Advisory Services Division (PASD), I lead AI strategy and architecture, embedding agentic AI and intelligent automation into patient-facing and advisory workflows. I define AI roadmaps, governance models, ROI frameworks, and scalable platform foundations that improve productivity, accelerate innovation, and position CRG as a digitally forward, AI-enabled CRO. Previously at ICON (including PRA Health Sciences), I led predictive analytics for clinical operations and safety, building models for enrollment forecasting, site performance optimization, risk-based monitoring, and safety signal detection across global trials. At Allscripts, I developed hospital optimization algorithms for patient flow, length-of-stay forecasting, resource allocation, and clinical decision support—improving operational efficiency and care delivery outcomes. I contribute to industry thought leadership through leadership and working group roles with ISPOR, PHUSE, and the Pistoia Alliance, advancing dialogue on AI in RWE/RWD, AI governance, and responsible AI adoption in regulated environments. I have presented at national and international conferences including ISPOR (US & Europe), PHUSE, IEEE, GetReal, Value-Added Medicine Congress, the Japanese Society of Computational Statistics, and SCDM Japan. I am passionate about building enterprise AI ecosystems that create measurable impact for patients, sponsors, and healthcare systems.
Lead enterprise AI strategy, capability development, and platform enablement across Evidera and CRG Digital–PASD, advancing predictive ML, GenAI, and agentic AI from experimentation to regulated, production-scale deployment. Evidera – Predictive ML & Real-World Data Innovation • Lead predictive ML and NLP models leveraging EHR, claims, registry, and unstructured data for: o Diagnosis acceleration and delayed diagnosis analytics (e.g., HCM, ILD) o Risk stratification and patient identification algorithms o Case-finding and real-world drug–drug interaction analytics o Social media–derived patient insights and imaging-based ML • Develop AI-driven proposals, protocols, and RFP responses supporting sponsor engagements and strategic data initiatives. • Partner with Business Development and scientific leadership to design scalable AI solutions aligned with client objectives. CRG Digital – Patient & Advisory Services Division (PASD) • Lead Digital Agentic AI initiatives embedding intelligent automation into patient-facing and advisory workflows. • Drive enterprise-wide use-case discovery, ROI modeling, architecture design, and product delivery. • Establish scalable AI foundations improving productivity and positioning CRG as a digitally forward, AI-enabled CRO. Enterprise AI Strategy, Governance & Platform Enablement • Architect cloud-based AI platforms (Azure, AWS, Databricks) and enterprise data pipelines supporting multi-region analytics across US, UK, and Nordic operations. • Establish AI governance standards, model validation frameworks, and regulatory-grade deployment in GxP environments. • Partner with Quality, Legal, Compliance, Security, and Digital teams to operationalize AI at scale. External Engagement & Industry Leadership • Represent the organization at ISPOR, PHUSE, IEEE, GetReal, SCDM, and other global forums. • Engage sponsors and strategic clients on AI-enabled RWE and predictive analytics initiatives.
Led AI and advanced analytics initiatives supporting healthcare financial and operational performance. Developed predictive models for patient flow, length-of-stay forecasting, resource allocation, and clinical decision support, improving hospital efficiency and throughput. Partnered with product and engineering teams to integrate ML capabilities into cloud-based healthcare analytics platforms.
Set up the infrastructure to conduct Statistical analysis and Machine learning on Big Data. Using Symphony & IQVIA US prescription, Claims & EMR data developed many Machine learning, Neural network and pattern recognition models that can identify the patterns in data which could be used identify drug interaction and its reaction, identify and track adverse event, identify offlabel drugs, predict patient diagnosis, misuse/abuse of onmarket drugs. Been part of many HEOR & Real World Evidence projects for pharmacetiucal clients wherein interacted with the clients to design the HEOR project and conducted Statistical Analysis, Survival Analysis, Regression Analysis, Hazard Models, Propensity score matching etc to identify Risk factors, analyze cost trend and to test the Hypothesis, the results of which has been used in many published papers. Cleaned and standardized the FDA adverse event reporting system data and developed post marketing Safety dashboard using the standardized data.Developed Safety and data quality sensors that can predict the number of adverse event (AE) that could occur for a given patient in a clinical trial.Worked on many NLP projects dealing with unstructured data and built many Text Analytics products and dashboard.