We are pleased to announce the completion of the software validation process for our Transparency Virtual Trials platform. In partnership with @Sierra_Labs, we have executed a set of SOPs and software validation documents that reflect our commitment to software quality.
That’s why TLS created the Discover toolkit, which combines past trial data with our proprietary Natural Language Processing technology to find the most relevant historical trial data so you can design your protocol with confidence.
Learn more at https://t.co/kZQExSJhkt
Study designers have expressed a challenge in discovering key comparative data in past studies. Whether inclusion & exclusion criteria or trial outcomes, they seek to learn from past efforts so they can design protocols with less risk of amendments and recruitment challenges.
Our technology powers Clinical Research activities centered around the patient experience.
We enable patient & researcher engagement, analyzing their sentiments, and employing this data to execute recruitment and other trial activities. Learn more: https://t.co/Q50qqldlkH
When preparing a clinical trial, past trial knowledge can be critical in honing inclusion & exclusion criteria, understanding trial outcomes, and finding the right investigators to support the trial. #ClinicalResearch
TLS has developed a proprietary Clinical Trial Data search & filtering solution that will help discover the most relevant trial findings and investigators, saving hours of effort and improving the search results to add the most value to trial preparation.
That’s why Transparency Life Sciences created a study platform that is easy to implement while maximizing the data capture & analysis potential.
How have your tech experiences been with executing Real World Data studies? We’d love to learn about your experiences and help. (2/2)
#realworlddata researchers are conveying to us a need for balanced software solutions that harness the power of advanced data analytics capabilities (NLP, ML), while maintaining a lightweight study framework without cumbersome and costly system implementation. (1/2)
Thankfully, today there are modern technologies such as Natural Language Processing and Correlation Discovery tools that can process the collected data to yield the key insights needed to make critical decisions to better serve the patient community. (2/2)
Clinical research organizations who conduct patient surveys to inform study protocol design and other key decisions tell us they are seeking more advanced analytics capabilities so they better understand the needs of patients they serve. (1/2)
"TLS creates a model in which #patients are more than subjects, but thoughtful collaborators in #clinicaltrial design and execution." Learn more: https://t.co/7OkozN6eY7 - Ginger Spitzer Foundation for #Sarcoidosis Research #patientchat
You're invited! Join us for “The Engaged Patient: Utilizing Digital Health” Empowered #patientchat Friday 01/08 1pmET | 10amPT with @SimplyKristyD!
https://t.co/7ZQMkkDLsb
"@transparencyls crowdsourcing expertise obtained fresh insights for our protocol assessing metformin in #prostatecancer. Their commitment to all-digital clinical trials will benefit patients & investigators." - Dr. Galsky #clinicaltrials https://t.co/7OkozMODzx @MountSinaiNYC