All the ThoughtSphere’s platforms work based on their inbuilt algorithms to interpret the unstructured, semi-structured or structured data and amalgamate them. To do so, the company has designed their data platform ‘ClinDAP’ that accommodates the volume, veracity, and velocity of the data for drug R&D by using machine learning and deep learning algorithms. ThoughtSphere has also built an oversight analytics platform—ClinACT— to monitor and manage drug R&D risks. This platform provides quality insight into the drug development studies along with monitoring and managing the risks associated with drug clinical trials. Additionally, ClinACT’s eager learning and fuzzy distance algorithms enable the platform to learn from every drug research it has been used for and apply its knowledge to newer studies in similar therapeutic areas, based on the prior learning experience.
ThoughtSphere also offers a life science R&D financial lifecycle management platform— SPACE—that performs budget planning and automates payment cycles for clinical trials along with the agreement execution between pharma companies and sites/investigators.
Technology itself cannot solve all the challenges that arise in the pharma industry; it can only act as an enabler to do the same, and we have developed our services around that fact
“Our platforms–SPACE and ClinACT—can be combined to deliver a distinct payment service in the pharma market. This union allows data quality triggered auto payments for Sites/Investigators if site maintains an appropriate level of quality and timeliness of the data,” explains Pattnaik.
Furthermore, to automate numerous manual activities involved in clinical trial data management, ThoughtSphere provides its customers a data science-driven workbench, DMSphere. This tool addresses the discrepancies that arise when disjointed data from various data collection systems and platforms are integrated for various clinical research activities. Moreover, ThoughtSphere has developed a Business Intelligence (BI) tool to offer users the ability to slice and dice data in near real time. This tool can be further integrated with ClinACT to provide ad-hoc reporting and ad-hoc analytics to the end users.
With its flexible approach toward managing clinical researches, ThoughtSphere assisted one its clients to reduce their study oversight and monitoring related expenses by 30 percent. Along with that, the client also observed a 55 percent gain in faster start-up time for the R&D process of the study data for early issue detection with the help of ThoughtSphere.
ThoughtSphere invests majority of its capital in product development and further envisions working toward the development of machine learning, natural language processing, and AI-driven automated clinical study build. “Our goal is to be among the best Vertical Cloud BI Solution to power Data Driven Decisions and improve Clinical R&D Outcome using Artificial Intelligence, Machine Learning & Data Science” concludes Pattnaik.