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Prabha Ranganathan

Prabha Ranganathan is a delivery director at Perficient and is responsible for delivering data warehousing and analytics solutions for various life sciences and health care companies. Prabha works closely with customers providing strategic advice on clinical data flows, data reviewing and cleaning using latest technological tools and solutions. Prabha has experience in building and releasing products from concept to release at Oracle, in various roles as Product Manager, Architect and Lead Developer. During most of her career, she has worked on enterprise products dealing with large volumes of data from various sources that need to be reviewed, cleaned and analyzed. With a clear understanding of business and strong technical knowledge, she brings a unique skillset to solve complex problems. She received her MBA from Babson College and M.S in Computer Science from Illinois Institute of Technology.

Blogs from this Author

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3 Takeaways from SCOPE Summit 2023

The SCOPE Summit for Clinical Ops Executives is an annual conference to drive collaboration and innovation in the clinical research community. I attended the 14th annual SCOPE Summit on February 6-9 of 2023 to connect with my colleagues and other industry experts about what technology advancements are driving growth in the life sciences industry. Here […]

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Leveraging AI for Knowledge Repositories and Content Curation in Life Sciences

–Ruby Lin and Nicolas Frantzen contributed to this blog. Overview In life sciences, like many other industries, knowledge is power. Historically, the main challenge has been around sourcing, organizing, and meaningfully surfacing this knowledge. To solve this challenge, one needs to look at innovative and scalable ways, such as AI, to find and organize a […]

Artificial Intelligence: Success Criteria in Life Sciences

Previously, I dove into how artificial intelligence helps review, and provide statistical analysis to data. The final blog of this series outlines how to be successful with an artificial intelligence implementation. Setting initial expectations and not promising a magic bullet is a key factor in determining the success of an initiative that focuses on deploying […]

AI Helps Review Plans, Data and Robotic Process Automation

My last installment explained how artificial intelligence (AI) assists search, confidence scores, and data reviews. This blog dives into how artificial intelligence helps review plans, provide statistical analysis to data, and robotic process automation. Review Plans Prior to starting data review, each team has its own review plan. The data review team has a data […]

AI Helps Search, Confidence Scores, and Data Review

Previously, I analyzed clinical data review platforms. This blog explains how artificial intelligence assists search, confidence scores, and data reviews. Search Data managers and reviewers log in to clinical data review platforms (CDRP), and slice and dice the data they want in order to review for missing, wrong, or inaccurate data. If they can search […]

Clinical Data Review Platforms in Life Sciences (CDRP)

My last blog discussed how AI assists to create human-computer systems. This next blog in the series analyzes clinical data review platforms. While machine learning (ML) and natural language processing (NLP) functionalities are not currently available in today’s clinical data review platforms (CDRP’s), we know they offer tremendous benefits to the clinical data review and […]

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AI Creates a Human-Computer System in Life Sciences

Previously, I discussed artificial intelligence (AI) enhancing clinical data review processes. This blog discusses how AI assists to create a human-computer system. Humans and machines each have their own strengths. On the one hand, machines are good at processing and analyzing large volumes of data with high speed and accuracy. On the other hand, humans […]

How AI Can Enhance the Clinical Data Review and Cleaning Process

Ensuring that clinical trial data is accurate and that clinical trials are safe and effective, is a time-consuming and a manually intensive process. Many life sciences companies have implemented home-grown or off-the-shelf clinical data review platforms and defined the reviewing and cleaning processes to be used with them. Many of these systems have proven to […]

Overview of AI in Clinical Data Review Platforms

Enhancing the clinical data review and cleaning process using available AI technologies, will enable pharma companies to release new drugs to the market following an effective process and ensuring the safety & efficacy of the drugs released. During the past several years, many pharmaceutical companies implemented home-grown or off-the-shelf Clinical Data Review Platforms. They defined […]