Serving as Chief Information, Expertise, and Product Officer at Clario, he boasts over two decades of cumulative experience in leading top-performing teams across Info, Expertise, and Product groups, with an unwavering commitment to information security and a passion for crafting innovative technologies and products that drive meaningful impact.
Before joining Clario, Jay held senior leadership positions, including Chief Information Officer (CIO), Chief Technology Officer (CTO), and Chief Product Officer (CPO) at prominent global organizations like Quikrete Companies and the American Cancer Society. Additionally, he serves as a member of the Board of Directors at Allata, LLC. His impressive achievements have garnered recognition on multiple occasions, including prestigious awards such as Government Chief of the Year from Atlanta Technology Professionals and Mid-Cap CIO of the Year from HMG Strategy.
As a pioneer in scientific trial administration, we deliver comprehensive endpoint solutions that revolutionize lives through reliable and precise evidence-based technologies. With a focus on oncology trials, Clario prioritizes patient-reported outcomes (PROs), leveraging their potency to amplify efficacy, ensure safety, and promote superior quality of life, championing the use of digital PROs as a more cost-effective alternative to traditional paper-based methods. With a global reach spanning over 100 international locations and extensive experience across diverse therapeutic areas, Clario specializes in efficiently managing decentralized, hybrid, and site-based clinical trials, harnessing the power of advanced technologies such as artificial intelligence and machine learning. Our streamlined options ensure seamless trial processes, fostering compliance and retention through integrated support and coaching for participants and sponsors alike?
We leverage our cutting-edge AI technology to deliver expedited speed, uncompromising quality, unwavering precision, and unshakeable privacy to over 800 esteemed clients across numerous scientific trials. While we’re thrilled that our innovative instruments are bucking the trend and providing tangible value in these trials, it’s essential we stay grounded and recognize their potential limitations.
Currently, our AI solutions primarily categorize into four distinct categories: information privacy, quality management assistance, learning assistance, and read evaluation. With advanced instruments in medical imaging, it’s now possible to efficiently remove Personally Identifiable Information (PII) from static images, videos, and PDF files with routine ease. Utilizing advanced AI tools, we integrate high-quality information with rapid assessments at the point of input, thereby fostering a robust level of trust in our data. We’ve engineered an innovative tool that continuously monitors ECG data to ensure exceptional quality, as well as another system that verifies accurate patient identification with precision. We have created a cutting-edge read-assist instrument capable of predicting slices, tracing lesion progression, and detecting illnesses with precision. By streamlining the learning assessment process through automation and standardization, we’ve integrated cutting-edge tools such as AI-powered quantitative ulcerative colitis Mayo scoring to enhance the accuracy and efficiency of our evaluations.
Since 2018, our team has been actively developing various forms of AI fashion, with notable advancements, but we’ve truly only scratched the surface.
We consistently train our AI models on vast amounts of data to learn the nuances of distinguishing between reliable information and unreliable or irrelevant content. As a result, our AI-powered insights engine processes comprehensive data profiles, generating superior decision-making capabilities for our clients.
Our comprehensive range of spirometry options effectively demonstrates the importance of conducting these tests. Clinicians employ spirometry to aid diagnosis and track progression of various lung conditions, quantifying the volume of air exhaled during a single forced breath. When an individual uses a spirometer, various errors may occur. Subjects may conduct the examination at an unacceptably slow pace, exhibit excessive coughing during testing, or be unable to create a complete seal around the spirometer’s mouthpiece. Unforeseen errors can arise from any variability, potentially remaining undetected until a human analyst scrutinizes the results. We’ve trained deep learning models on more than 50,000 examples to identify the difference between effective learning and ineffective learning. By leveraging our advanced analytics capabilities and streamlined processes, healthcare professionals can quickly access valuable insights in near-real time, eliminating the need for manual review and expediting informed decision-making. That issue arises partly because some patients may need to drive for several hours to participate in a clinical trial. Consider making the arduous drive home just because you’re instructed to retake a spirometry test the following week after the initial one reveals an error due to its positioning? The AI-powered fashion solutions are accurately processing data while the user remains engaged on the platform. If an error occurs, it can usually be corrected immediately. One of several approaches being developed to alleviate the strain on websites and users alike is simply a method.
Our top priority when conducting scientific trials is to provide the highest-quality information, yet the inherent capabilities of our AI algorithms enable a significant acceleration in data collection and analysis. Our advanced algorithms empower us to deliver comprehensive management evaluations with unparalleled speed and accuracy, outperforming human interpretation at every turn. With these features, we’re able to perform rigorous quality control measures as data is input. We can identify and rectify incomplete or inaccurate participant data while they remain on the trial website, rather than notifying them at a later date.
Decentralized trials are increasingly becoming a norm in clinical research, and while they may not always involve a traditional centralized component, it’s true that many modern studies do incorporate hybrid elements to maximize efficiency and effectiveness. By allowing members to utilize their personal units or similar units at home, we unlock a wealth of opportunities for more inclusive and accessible trials. Simplifying trial participation is a core objective of our knowledge roadmap, aiming to create solutions that increase participant diversity, streamline enrollment and retention, foster greater member comfort, and expand opportunities for more inclusive clinical trials. We offer at-home spirometry, home blood pressure monitoring, and electronic patient-reported outcomes (eCOA) solutions that deliver equivalent data integrity to traditional methods, all while collaborating with our team of expert endpoint and therapeutic area specialists. The results yield significant benefits in enhancing user knowledge for improved endpoint outcomes.
Since 2018, we have been developing AI instruments that have become integral to both our internal processes and products, thoroughly infusing them across our entire portfolio. What remains unwavering is our commitment to transparent decision-making: keeping stakeholders informed, collaborating with regulatory bodies, engaging with customers, and consulting with legal, privacy, and scientific experts to guarantee that every step taken is ethical and responsible.
Responsible AI development and deployment should positively impact a broad spectrum of domains, yielding numerous constructive outcomes. Our AI program’s muse is grounded in a hypothetical interpretation of the company’s initial Accountable Use Rules. Anyone at Clario who interacts with AI adheres to these five fundamental principles. We utilize a rigorous approach to select the most comprehensive data available, ensuring our algorithms are trained on the richest possible information set among all contenders. We continuously monitor and scrutinize data to identify and neutralize potential threats, relying exclusively on anonymized insights to refine models and optimize algorithmic decision-making processes. By incorporating these guidelines into the development process for a novel AI tool, we can swiftly deliver accurate information on a large scale, minimizing bias, amplifying diversity, and safeguarding patient privacy. The sooner we obtain accurate sponsorship data, the greater the impact will be on their bottom line, subsequently influencing individual outcomes.
Biases often arise when coaching information sets are unrealistically constrained for their intended purposes. Although an abundance of information appears to be provided upfront, difficulties can arise when a user pushes the limits of an AI-trained instrument, potentially leading to inaccuracies. Clario’s Chief Medical Officer, Dr. By employing mannequins, Todd Rudo enables healthcare professionals to simulate correct lead placement in electrocardiograms (ECGs), thereby empowering clinicians to verify whether technicians have accurately positioned the leads on a patient’s body. With a substantial amount of valuable data at our disposal, we’re well-equipped to fine-tune the model and test its efficacy on a massive dataset of 100,000 ECGs. What happens when we solely train our AI model on data from adult checks? What would a lifeless mannequin do with an electrocardiogram (ECG) report of a 2-year-old patient, anyway? It’s crucial to thoroughly examine data accurately to avoid overlooking errors that could significantly impact treatment outcomes.
That’s why at Clario, our product, information, R&D, and science groups all work carefully collectively to make sure that we’re utilizing probably the most complete coaching information to make sure accuracy and reliability in real-world purposes. We leverage vast amounts of readily available data to train the sophisticated algorithms embedded in our products. That’s why we prioritize incorporating human oversight to ensure the safe development and application of AI technologies.
With human oversight in place, a select group of individuals possesses unparalleled insight into the fashion development process, from conception to validation, ensuring meticulous attention to detail. After integrating a model into a technology, our experts closely scrutinize outputs to identify any latent biases and guarantee that the results are honest and reliable. I envision AI as a catalyst for amplifying scientific innovation and human ingenuity. Artificial intelligence provides individuals with the freedom to tackle more complex challenges. We excel at resolving problems and possess a distinct advantage over machines in terms of intuition and subtlety. With Clario, we leverage AI to automate routine tasks and free up resources for more strategic pursuits. We utilize this approach to examine comprehensive data sets, encompassing both individual profiles and previous case studies, as well as other factors requiring thorough analysis. Machines often perform tasks faster and occasionally with greater accuracy than humans can. While others may lack the ability to combine human intuition with scientific knowledge and real-world experience, a hallmark of professionals in our field.
As a healthcare professional, I’m passionate about leveraging the potential of applied artificial intelligence in radiomics to extract valuable, data-driven insights from medical images, revolutionizing the field of oncology. Radiomics involves a multi-step process, comprising image acquisition of tumours, pre-processing, feature extraction, model development, followed by validation and clinical implementation. By leveraging advanced AI technology, we can accurately forecast tumour progression, personalize treatment responses, and anticipate patient outcomes through the application of non-invasive imaging techniques to tumours. With this technology, we will be able to identify early warning signs of illness and promptly detect any recurrences, enabling timely interventions and improved health outcomes. As advanced AI tools become increasingly integrated into radiomics and scientific workflows, significant advances are expected to occur in the fields of oncology and patient care.
I am thrilled by the exciting prospects for future advancements in respiratory research. In 2022, we made a strategic acquisition of ArtiQ, a pioneering Belgian company that developed cutting-edge AI models to revolutionize the collection of respiratory data in clinical trials. As our founder transitions to Chief AI Officer, we’re bracing ourselves for significant challenges in respiratory care options. Our algorithmic software strategy has emerged as a true game-changer, primarily due to its ability to significantly reduce patient and website burdens. An unintended delay occurs when exhalation data isn’t promptly scrutinized, resulting in anomalies being identified only after the fact, thus requiring the individual to revisit the clinic for further evaluation. Moreover, delays and additional costs associated with a participant’s non-adherence can have far-reaching consequences, including increased operational challenges for the trial sponsor and heightened stress for the individual involved, which ultimately jeopardizes the success of the study. Utilizing advanced Artiq technologies, our cutting-edge spirometry devices efficiently manage the high workload through the provision of near-real-time overread capabilities. Whenever unexpected issues arise, they are swiftly identified and addressed, enabling the individual to remain at the facility uninterrupted.
Ultimately, we’re developing tools that can impact treatment outcomes across various therapeutic sectors.
In a rapidly evolving landscape, artificial intelligence will increasingly bring added value to digital scientific outcome assessments, or eCOAs. AI fashions will track and quantify refined adjustments made by the individual. This knowledge will greatly benefit a multitude of researchers, enabling, for example, Alzheimer’s researchers to pinpoint exactly where the patient stands in the progression of the disease. By assessing drug efficacy more effectively, patients and caregivers will be better equipped to manage the condition.
You may struggle to fully grasp the implications of artificial intelligence if you solely view it through a technological prism. The development of artificial intelligence requires a multifaceted approach that encompasses technological advancements, scientific research, regulatory frameworks, and various other factors. In our industry, exceptional results stem from the synergy between human collaboration and thoughtful inquiry, allowing us to pose crucial questions such as: “Are we crafting models that account for age, gender, sex, race, and ethnicity?” By collectively exploring these queries, we can ensure that AI-driven drug development accelerates progress not just for some patient populations, but all.
By 2025, the biopharma industry is poised to harness the power of artificial intelligence (AI) and real-time analytics in ways previously unimaginable. Advancements in this area are poised to simplify the scientific trial process, thereby enhancing the accuracy of crucial decisions. By accelerating research buildouts and adopting a data-driven approach to risk-based monitoring, we will enable the timely delivery of innovative therapies, alleviate the strain on patients, and empower sponsors to bring life-changing treatments to market with greater speed, efficiency, and precision. It’s an exciting period for everyone involved, as we collaborate to revolutionize healthcare.