Analytics Operations Lead
Associate Clinical Professor
university of Toronto
United States of America
Ankit Lodha has high-end expertise in clinical trail conduct and interpretation of clinical operations data in the pharmaceutical/ biotechnology industry. In his current position, Ankit is responsible for setting the data strategy supporting clinical trials, generating real-time dashboard, and predictive modelling for patient enrollment, site quality and forecasting study start-ups and cycle times. Ankit is Analytics Operations Lead in Clinical Systems & Analytical Reporting (CSAR) function at Amgen. Within Amgen he has worked on R&D and Commercial Analytics. Before this position he has provided strategic consulting services, supporting the analytics, data reporting, and data management needs of senior leadership at AstraZeneca and Pfizer. He holds a Bachelors in Biotechnology Engineering from Dr. D.Y. Patil University, Masters in Business of Bioscience from Keck Graduate Institute and MBA from Redlands University – School of Business. Ankit Lodha has high-end expertise in clinical trail conduct and interpretation of clinical operations data in the pharmaceutical/ biotechnology industry. In his current position, Ankit is responsible for setting the data strategy supporting clinical trials, generating real-time dashboard, and predictive modelling for patient enrollment, site quality and forecasting study start-ups and cycle times. Ankit is Analytics Operations Lead in Clinical Systems & Analytical Reporting (CSAR) function at Amgen. Within Amgen he has worked on R&D and Commercial Analytics. Before this position he has provided strategic consulting services, supporting the analytics, data reporting, and data management needs of senior leadership at AstraZeneca and Pfizer. He holds a Bachelors in Biotechnology Engineering from Dr. D.Y. Patil University, Masters in Business of Bioscience from Keck Graduate Institute and MBA from Redlands University – School of Business.
Clinical trial design, Oncology, Study start-up time and Clinical trail cycle time analytics