The Time is Now for Innovation in Clinical Trials

Earlier this week, Saama Technologies announced it had signed an agreement to acquire Comprehend Systems. If you’ve been following the life sciences industry and the state of clinical trials, this announcement is just one of many recently, demonstrating a very active market space. In the past 90 days, Verily announced they’re moving into the market to modernize clinical trials. Veeva Systems spent a great deal of time on their May earnings call talking about their Clinical Data Management System. And then in June, Dassault Systemes SE agreed to buy Medidata Solutions to “gain a foothold in the fast-growing market for clinical trial technology.”

ThoughtSphere welcomes the innovation these vendors potentially bring with these acquisitions and announcements and the investments they’re making. I recently joined ThoughtSphere as Chief Marketing Officer because of the opportunity we have to disrupt the industry and make a difference in helping pharmaceutical companies bring their treatments to market faster and at a reduced cost. The technologies and processes employed to bring these treatments to market are often outdated and very manual and time-consuming, and the time is right to disrupt this market. One of the biggest challenges plaguing the clinical research industry today is the inability to integrate large volumes of data from a variety of sources. These and other associated problems with the quality and access to clinical trials and data management are laid out very nicely in this Oracle Research Report.

The industry has the technology to address these problems.

• Cloud computing provides a scalable and elastic platform at a reduced cost, and with robust security, for running clinical trials.
• Artificial intelligence (AI) also holds great promise in improving clinical trial processes from detecting trends, identifying and learning risks, and predicting outcomes. AI can help sponsors understand the effectiveness of drugs, predict the ultimate success of a clinical trial, or enhance subject identification and enrollment, a significant problem for the industry today.
• Clinical data are very dynamic and every study is unique. AI with machine learning will be applied in mapping highly complex studies allowing those studies to be on-boarded more quickly.
• AI combined with a big data, data lake architecture will allow pharmaceutical companies (trial sponsors) to process the variety and volume of data produced in running clinical trials.

A clinical data and analytics hub leveraging these technologies will enable sponsors and CROs to ingest, aggregate, standardize and provide secure data access for all stakeholders throughout the clinical organization. Access to the data gives these organizations complete freedom to focus on high-value tasks such as analyzing clinical and operational data to better monitor risk and visualize outliers and trends.

ThoughtSphere was founded by Sudeep Pattnaik, who ran Products and Delivery for the world’s largest contract research organization (CRO). He saw first-hand how the industry had not changed much over the years and understood the power of data science. These new and emerging technologies can be applied to help improve clinical trials and data management. These technologies and our approach to solving the industry challenges are at the heart of ThoughtSphere’s Clinical Data and Analytics Platform. ThoughtSphere wants to make it easy to manage and interpret data from structured and unstructured clinical and operational data sources and unlock the value of accessing the data for analysis.

We have already proven our ability to disrupt the manual processes I mentioned earlier. One of our clients has reported a 50% time savings in mapping highly complex studies and a 30% cost reduction in overall data management. I am excited to be part of the ThoughtSphere team and, as all of the news lately shows, it’s an exciting time to be in life sciences.