Big data analytics - Clinical integration and visualization | 53874
Journal of Clinical Trials

Journal of Clinical Trials
Open Access

ISSN: 2167-0870

+44 1478 350008

Big data analytics - Clinical integration and visualization

2nd International Conference on Clinical Trials and Therapeutic Drug Monitoring

August 22-24, 2016 Philadelphia, USA

Ankit Lodha

University of Redlands-School of Business, USA

Scientific Tracks Abstracts: J Clin Trials

Abstract :

Pharma companies spend millions of dollars on research and even more on these clinical trials to ensure safety and efficacy of the drugs. Developing the right protocols, selecting the proper sites, setting the right expectations with all stakeholders, developing and tracking the right metrics and effective communication is the key to optimizing the resources and cost of clinical trials. The number of clinical trials underway each year has been increasing steadily, worldwide. In the last five years alone, over 75,000 federally and privately supported trials have been registered with the National Institute of Health��?s Clinical Trials registry. Conducting clinical trials today is a complex set of activities that amass huge volumes of data from multiple systems. Having real-time clinical metrics and dashboards which provides insights on patient enrollment, study conduct, close-out and reporting is one of the biggest challenges for bio-pharmaceutical R&D industry. With a broad range of study designs, varying data collection methods and time points, efficient data analysis in clinical development has become more important than ever. The more effectively study data are managed, the faster the data can be extracted and analyzed. The analysis of the data is important for each trial stage as valuable insights can be gained. For example, during the early stages of a clinical trial, access to data is vital not only for patient safety, but for solving problems while they are still manageable and before they become costly.

Biography :

Ankit Lodha has high-end expertise in study conduct and interpretation of clinical operations data in the pharmaceutical/ biotechnology industry. He is Analytics Operations Lead in Clinical Application & Analytical Services (CAAS) 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 Bachelor’s in Biotechnology Engineering from Dr. D Y Patil University, Master’s in Business of Bioscience from Keck Graduate Institute and MBA from Redlands University – School of Business.