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Life Sciences

Fast, Easy Study Planning, Budgeting, and Outsourcing

Today, there are many obstacles in planning clinical trials. Complex study requirements, global patient populations, the need for shorter timelines, limited...

Today, there are many obstacles in planning clinical trials. Complex study requirements, global patient populations, the need for shorter timelines, limited personnel, and constrained financial resources, all contribute to making study planning a prolonged and difficult exercise for life sciences sponsors. Further, outsourcing all or part of these studies to a contract research organization (CRO) can add another layer of complexity. Clinical organizations need a way to plan...

Innovation, Transparency, and Success for Medical Device Trial

Medical device studies pose several unique challenges, many of which can be managed with targeted eClinical solutions such as InForm and CTMS.

Medical device studies pose several unique challenges, many of which can be managed with targeted eClinical solutions such as InForm and CTMS.

RWE & AI - The Opportunity Is Endless

Real World Evidence (RWE) is a very hot topic today. There is an endless opportunity for it when one considers combining Artificial Intelligence (AI) techniques...

Real World Evidence (RWE) is a very hot topic today. There is an endless opportunity for it when one considers combining Artificial Intelligence (AI) techniques on top of such a valuable digital asset cache! Oracle takes a look at it from both the business and technical perspectives.

The Value of Framework and Methodology in Clinical Data Consolidation

With the incredible growth in the amount of data generated by a trial, data consolidation has also become a necessity. As data continues to stream in from...

With the incredible growth in the amount of data generated by a trial, data consolidation has also become a necessity. As data continues to stream in from multiple sources, sensors, and mobile devices, the time is rapidly approaching where data sets can typically average 500 gigabytes to a terabyte in size. For biopharmaceutical companies, the question isn’t whether they need to adopt a unified data management strategy. The real question is how to engage in this transition...

Changing Clinical Trials, One Microservice at a Time

The Life Sciences industry is changing rapidly. But today’s core trial platform technology continues to force both trial processes and data to be siloed and...

The Life Sciences industry is changing rapidly. But today’s core trial platform technology continues to force both trial processes and data to be siloed and does not allow for the kind of rapid innovation the industry requires. To stay on pace with rapid change, innovation must be applied to our clinical trial processes so that they can offer quick ways to advance trial processes.

Repeat After Me: Change is Good!

The number one barrier to adopting mHealth/ digital into clinical trials is not whether the technology is ready, or whether there are enough sensors or...

The number one barrier to adopting mHealth/ digital into clinical trials is not whether the technology is ready, or whether there are enough sensors or validated digital endpoints (all these are important); but it is because the execution involves change, the biggest hurdle. However there is huge opportunity that can be gained from this kind of change when comparing the traditional data management world of today with the data-science-centric world of tomorrow, enabled by...

The Value of the Cloud for Multivigilance

Today’s safety professionals face a seismic wave of pressures that include increasing caseloads, changing regulations, and shrinking budgets. These developments...

Today’s safety professionals face a seismic wave of pressures that include increasing caseloads, changing regulations, and shrinking budgets. These developments are forcing them to seek new types of solutions that reduce costs while remaining compliant with fast-changing industry guidelines and standards. To address these concerns safety professionals are exploring ways to automate business process workflows using artificial intelligence to gain new efficiencies.

Challenges and Opportunities in Clinical Data Management

Clinical trial data management is fraught with frustrating difficulties like waiting weeks for data access, fragmented data, and siloed systems. These issues...

Clinical trial data management is fraught with frustrating difficulties like waiting weeks for data access, fragmented data, and siloed systems. These issues cause clinical teams to waste valuable time cleaning and reconciling data, instead of analyzing it . The wasted time is also costly, resulting in anything from small delays to catastrophic setbacks that can require repeating an entire trial. As the volume of trials continues to grow, these challenges can only multiply...

How Machine Learning Is Transforming Clinical Data

Machine Learning (ML) is a branch of Artificial Intelligence (AI) that allows computer systems to learn directly from examples, data, and experience. In the...

Machine Learning (ML) is a branch of Artificial Intelligence (AI) that allows computer systems to learn directly from examples, data, and experience. In the world of clinical trials, ML can be used to improve the quality, reliability, and availability of data by utilizing historical data to train ML algorithms and provide automated insights. This post provides a quick overview of non-clinical and clinical examples of how ML is transforming the production and consumption of...