COTA

AI models need to be trained & validated on high-quality, fit-for-purpose data to produce trustworthy, accurate, & consistent results.  Increasingly, this data is being drawn from real-world data sources, many of which require careful curation to get to the point of being usable for these purposes. So what’s really involved in this process, & how will it change in the future as our understanding of both AI & RWD evolve? We asked one of COTA’s product leads, Nick Ritter, to help us answer some key questions. 1️⃣ What data quality metrics have proven effective in identifying & mitigating biases in AI models developed from real-world-data?  Mitigating biases in models developed from RWD starts by mitigating any biases in the datasets themselves.  We would rely on quality metrics such as data completeness & representativeness, appropriate sample sizes, the recency of data to ensure the RWD & resulting AI-based products would perform with minimal biases. 2️⃣ Given the current limitations of data standardization, how can we ensure that AI models trained on heterogeneous RWD maintain high predictive accuracy across different healthcare settings? The answer lies in collaboration across the industry & across settings where AI models are being deployed.  Developers & users need to create high-quality data standards – & push themselves & others to conform to those standards.  Users of AI models also need to do their part by understanding which datasets & standards their models are based on so they can make the right choices about how to use the results & provide meaningful feedback to developers.  At COTA, we’ve developed a data model based on the type of high-quality standards we’d like to see across the industry, & we’re subsequently building our AI applications based on those standards. 3️⃣ What’s your 3-to-5 year prediction about the dynamic between human data curation & AI’s ability to perform the same functions? While we’re excited about the potential use of AI for the purpose of curation, we know there’s currently a gap between AI’s maturity in this space & the imperative to ensure that researchers have access to the highest quality RWD.  That being said, COTA is currently developing products where AI shows the most opportunity to provide assistance. We’re staying focused on the extremely high standards these models have to meet in order to replace or assist experienced humans in these tasks. In the next few years, I suspect we’ll see certain data elements that can be reliably curated by technology, given the nature of how they’re documented & discussed among healthcare teams.  But we can’t lose sight of the value that human intelligence & organic clinical knowledge can bring to the curation process, especially around complex health data. #RWD #AI #Healthcare

Quarterly wellness days are an important part of the COTA experience. These are days when our only job is to prioritize our wellbeing - and it's no coincidence the most recent wellness day landed in the same week as World Mental Health Day. The news about increasing rates of stress and anxiety at workplaces globally is concerning. And while we can't fix it with wellness days alone, at COTA we strive to create a workplace that is rewarding, meaningful, kind, and fun. Thank you to our talented and hard working team members. We are so pleased to see you enjoying another COTA Wellness Day! 💜 #WorldMentalHealthDay #MentalHealthMatters

The topic of healthcare data is often overshadowed by the latest and greatest AI advancement or the buzzy tech that promises to be the next great healthcare disruptor. That's why we love Datavant's Future of Health Data conference so much - because it's all about the data! We heard from pioneers and innovators about the current state of healthcare data including the challenges, the opportunities, and the potential that exists 𝑰𝑭 we can get the data foundation right. COTA's CEO Miruna Sasu shared her vision for real-world data in clinical research alongside panelists Andrew von Eschenbach M.D, Laura Wallace, and Alastair Thomson, wrapping up with a series of mic drop moments 🫨 when moderator Kathleen Gavin, PhD asked each panelist: "In one sentence, what is the ROI or overarching value proposition of RWD?" 🎤 RWD can identify specific patients who are going to benefit from a treatment because many of today's drugs are so targeted that you are going to be challenged to find and enroll them in a traditional RCT. 🎤🎤 RWD can get people the evidence they need to answer questions - from the lab ➡️ to clinical development ➡️ to external stakeholders - RWD can help us throughout the continuum as we go from cool molecule in a lab to patient benefit. 🎤🎤🎤 RWD allows us to track changes in our patients and their disease so we can understand the entire movie and not just a single scene. 🎤🎤🎤🎤 RWD allows us to develop drugs that are tailored to someone's unique biology in order to give each individual patient the best chance of survival. YES, YES, YES, and YES! COTA is so grateful to be part of the healthcare data revolution. Thank you for hosting and including us in this fabulous event, Datavant 💜 #FOHD2024 #realworlddata #realworldevidence

The COTA team is in DC 🇺🇸 for Datavant's Future of Health Data conference!! Looking forward to the excellent lineup of speakers (including our own Miruna Sasu 🤩) See you there!!  #FOHD2024

🚀 A cross-industry collaboration is advancing RWD 🚀 The real world is an unpredictable place. It can be messy & confusing, full of challenges & uncertainties that have to be overcome before we can move forward with confidence & clarity toward our goals. The same is true of the #RealWorldData (RWD) generated throughout the patient journey. Before we can use these data elements as #RealWorldEvidence (RWE) for outcomes of interest, we have to answer some key questions. ❓What is actually in these datasets? ❓Are providers collecting sufficient data throughout the care journey? ❓How do we extract, aggregate, & analyze these high-value elements? ❓How can we be more consistent? These questions are too big & too complex for any one company to answer on their own. That’s why the non-profit Friends of Cancer Research (Friends) has convened an impressive coalition of data companies, life science companies, academic organizations, provider groups, & others to share their knowledge & resources in pursuit of effective cures. Since 2018, Friends has conducted a series of pilots designed to better understand the utility of #RWD & #RWE for research applications, starting with work to establish shared endpoint definitions & continuing with projects to evaluate the consistency of RWD & its potential to generate reliable, meaningful evidence. ⏩ The latest phase of this collaboration brings the industry closer than ever to understanding the reliability & consistency of RWD to be used in research applications, specifically in use cases related to non-small cell lung cancer (NSCLC). ⏩ In August, new research published in JCO Clinical Cancer Informatics found that RWD harmonized across sources to an aligned protocol demonstrated reasonable consistency in real-world response assessment. ⏩ In other words, oncologists treating patients in the real-world setting are documenting response to treatment on a regular frequency, & with enough clinical detail, to be useful for researchers, even though these oncologists & patients aren’t enrolled in clinical trials. ⏩ The study also shows that different data companies are processing information in a relatively consistent manner to produce consistent results despite some differences in proprietary methodologies. According to Andrew Belli, VP of Research at COTA: 💬 These results give further confidence in the use of real-world information to augment & enhance insights from traditional clinical trials. Researchers using RWD can gain access to broader & more inclusive datasets that are representative of actual populations of cancer patients, helping to ensure generalizability of results. 💬 We can't overstate the importance of this type of collaborative, forward-thinking research into advancing the use of RWD. We believe it is essential to take a leadership role in this ongoing conversation, & COTA is proud to be a part of the Friends community as well as other industry partnerships & collaborative organizations.

In this Q&A, hear from clinical and scientific leaders at COTA and Panalgo about the ways their recently announced partnership will add value for life sciences companies – and ultimately patients. #realworlddata #realworldevidence #oncologyresearch #pharma #lifesciences

Did you know every 3️⃣ minutes a person in the US is diagnosed with leukemia, lymphoma or myeloma? Or that blood cancers are expected to account for almost 🔟% of new cancer cases in the US in 2024? This 𝐁𝐥𝐨𝐨𝐝 𝐂𝐚𝐧𝐜𝐞𝐫 𝐀𝐰𝐚𝐫𝐞𝐧𝐞𝐬𝐬 𝐌𝐨𝐧𝐭𝐡, we are raising money and awareness in partnership with The Leukemia & Lymphoma Society's Light the Night. Will you help us support patients and families by donating to team COTA Hedgehogs? Please visit our team fundraising page to learn more about Light the Night and make a donation: https://lnkd.in/ezcThyZD #bloodcancerawarenessmonth #lightthenight #leukemia #lymphoma #myeloma

Since it's Friday 😎 we're switching up our usual oncology and real-world data related posts to talk about relationships. Particularly the one between a CFO, their executive team, and the board of directors 🤝 + 🤝 + 🤝 In a session hosted by #Fsuite, COTA's CFO Ritu Uppal Bahal will dig into this complicated topic and explore best practices for managing these key relationships. She and others will share their experience fostering strong partnerships and talk about bridging the gap between financial operations and a company's strategic vision. Looking to learn something new this Friday? Check out this and future programing from #FSuite on their website https://lnkd.in/estD9wWs Coco Schoeller Hein

R&D teams are using clinicogenomic data to shed new light on therapeutic approaches ⏬ ⏬ 𝑯𝒆𝒓𝒆 𝒂𝒓𝒆 𝒔𝒐𝒎𝒆 𝒓𝒆𝒂𝒍 𝒘𝒐𝒓𝒍𝒅 𝒆𝒙𝒂𝒎𝒑𝒍𝒆𝒔 ⏬ ⏬ There’s a lot to think about when considering how to integrate clinicogenomic data into the R&D process.  ❓ Where is it most useful?  ❓What tools and strategies are most applicable for processing large volumes of data?  ❓Is comprehensive whole exome sequencing or the higher sensitivity of more widely used large panel sequencing needed?  ❓What about sequential testing to monitor changes over time?  ❓And how can life science companies trust that the data is comprehensive, accurate, standardized, and fit-for-purpose for current and future use cases? The industry is still at the beginning of pondering these questions, but some of the answers are already becoming clear.  At the moment, clinicogenomic data is most useful in early- and mid-stage R&D to explore previously-unknown variants, put therapeutic results in context, or expand the utility of existing compounds. ▶ For example, genomic data played an integral part in helping to identify the PCSK9 mutations linked to coronary heart disease and helped accelerate the drug development process for related conditions. (𝑎𝑐𝑐𝑒𝑠𝑠 𝑠𝑡𝑢𝑑𝑦 𝑓𝑟𝑜𝑚 𝑜𝑢𝑟 𝑏𝑙𝑜𝑔 - 𝑙𝑖𝑛𝑘 𝑖𝑛 𝑐𝑜𝑚𝑚𝑒𝑛𝑡𝑠) ▶ In another case, researchers used both clinicogenomic and claims data to identify shared biology and drug targets for three strains of coronaviruses. The synthesis of multiple data types helped researchers identify two current medications that could be used to improve patient outcomes. (𝑎𝑐𝑐𝑒𝑠𝑠 𝑠𝑡𝑢𝑑𝑦 𝑓𝑟𝑜𝑚 𝑜𝑢𝑟 𝑏𝑙𝑜𝑔 - 𝑙𝑖𝑛𝑘 𝑖𝑛 𝑐𝑜𝑚𝑚𝑒𝑛𝑡𝑠) ▶ And clinicogenomic data played a vital role in a third team being able to assess the relationship between tumor genomics and clinical outcomes in patients with non-small cell lung cancer (NSCLC). Researchers were able to identify a subset of NSCLC patients who responded best to PDL-1 therapies and identify a specific predictor of immunotherapy response. (𝑎𝑐𝑐𝑒𝑠𝑠 𝑠𝑡𝑢𝑑𝑦 𝑓𝑟𝑜𝑚 𝑜𝑢𝑟 𝑏𝑙𝑜𝑔 - 𝑙𝑖𝑛𝑘 𝑖𝑛 𝑐𝑜𝑚𝑚𝑒𝑛𝑡𝑠) These are just some of the intriguing ways R&D teams are using clinicogenomic data to start shedding new light on therapeutic approaches.  With the drug development process taking upwards of 15 years with up to a 90% failure rate, it’s no wonder that life science companies are beginning to invest more heavily in non-traditional datasets that can add value while shortening the development timeline. #clinicogenomics #rwd #realworlddata #pharma

📣 📣 📣 Through this partnership, COTA makes our hematologic oncology data available through Panalgo's Instant Health Data Analytics (IHD) platform. The collaboration will initially focus on COTA's hematologic oncology data, with plans to add solid tumor data in the future. The partnership also includes research collaborations and AI/technology co-development opportunities. At COTA, we are known for having the highest quality and most complete oncology RWD from electronic health records (EHRs) sourced from a 50/50 split of academic and community care settings across the U.S. Our data contain complete and concise longitudinal patient journeys that support regulatory submissions and help to answer research questions involving treatment patterns, real-world outcomes, care comparisons, and more. Read the full announcement ➡ link in comments ⬇ #realworlddata #rwd #realworldevidence #rwe #oncologyresearch #pharma