Christopher Jimenez’s Post

Two weeks ago, I shared my enthusiasm for @ReadoutAI, a Merck Accelerator company with an exciting platform that automates data management and biometrics. Response to my post was terrific; thank you to the 2 CROs and 2 sponsors that contacted me directly to learn more! Today, I’d like to highlight one specific piece of functionality that contributes greatly to the overall 85%-time savings across all tasks driven by the AI platform; the Clinical Study Report (CSR). As I've learned more about how weeks and months of time investment routinely required of biostatisticians and medical writers can be accelerated to just days, my dropped-jaw closed as my focus shifted to the exciting possibilities created simply due to this one aspect of the platform. Here is a link to one of their blog posts on AI for generating the CSR. https://lnkd.in/eAtKkCZK AI is not yet dominant but is here to stay, analogous to EDC in 2002 (8% of trials). As with EDC, there will be churn of vendors ramping up; those that understand both artificial intelligence and clinical trials, such as ReadoutAI, are sure to be the winners. Please contact me directly to learn more!  #ClinicalStudyReport #DataManagement #Biometrics #CRO

Navigating Innovation in Biologics: Why Bayesian Statistics Matter Bayesian statistics, once a niche methodology, is now emerging as a transformative tool for advancing drug development and quality, This growing adoption is driven by advances in computing power, novel clinical trial designs, and supportive regulatory frameworks. The Role of Bayesian Statistics in Biologics: At its core, Bayesian statistics combines prior knowledge with new data to update model probabilities, enabling dynamic, evidence-based decision-making. Unlike traditional methods, which rely solely on newly collected data, Bayesian approaches leverage historical evidence (prior knowledge), external information, and expert input to enhance data analysis and improve the understanding of relationships between datasets. Current applications of Bayesian statistics in biologics include (1) Pediatric Drug Develipment, (2) Oncology Dose-Finding Trials for determining maximum tolerated doses (MTD), (3) Improving trial designs for limited patient populations by using prior information and adapting trial structures. 📊 Pros of Bayesian Statistics include: 1. Flexibility in Trial Design: Bayesian methods support adaptive trials, reducing resource use, and timelines. 2. Better Data Integration: By combining diverse evidence sources, Bayesian methods ensure robust and comprehensive data analyses. 3. Smaller Sample Sizes: By incorporating data from related studies or populations, Bayesian trials require fewer participants, making them especially valuable in rare disease research. 4. Real-Time Decision-Making: Enables faster and more informed decisions during trials, accelerating product development timelines. 📊 Cons and Challenges include: 1. Computational Complexity: Bayesian methods demand sophisticated software, computational power, and statistical expertise, potentially increasing costs and creating barriers for some applications. 2. Dependence on Prior Knowledge: The accuracy of Bayesian conclusions depends on the quality of prior data. Biased or incorrect prior information can lead to flawed results, necessitating rigorous validation. 3. Regulatory Hesitancy: Despite growing acceptance, Bayesian methodologies still face skepticism in certain global regulatory bodies. The FDA’s anticipated draft guidance on Bayesian methodologies, expected in 2025, aims to address concerns and provide a clearer roadmap for implementation. As regulatory frameworks evolve, staying informed about Bayesian approaches will be essential for professionals seeking to lead in this dynamic field. References: 1. https://lnkd.in/gcDeKQgC 2. https://lnkd.in/g_Hm3pTq 3. https://lnkd.in/g4kYS38r #BayesianStatistics #AdvancedBiologics #CellTherapy #GeneTherapy #GMPCompliance #PharmaInnovation #QualitySystems #ClinicalTrials #RiskManagement #calidad #quality #atmp #cellandgene #car-t #cart

Quantifying uncertainties today to streamline & speed-up drug development tomorrow! AI is doing wonders already in clinical phase which will ultimately result drugs to come faster into the market from a molecule invented in research labs! A recent study in Health Data Science unveils a groundbreaking method that not only quantifies uncertainty in clinical trials but also enhances interpretability, surpassing current techniques. The innovative model, combining Selective Classification (SC) with the Hierarchical Interaction Network (HINT), marks a significant leap in clinical trial management. By pinpointing trials with low confidence levels and refraining from predictions when necessary, this approach ensures more accurate forecasts of trial outcomes, particularly beneficial for early-stage trials where uncertainty looms large. Learn more about this game-changing advancement: https://lnkd.in/gpsfdQFz #ClinicalTrials #DrugDevelopment #HealthDataScience #Innovation #NewAIModel

🚀 Introducing Welltree Analytics: Your Partner in Precision Biostatistics for Clinical Trials 🚀 We’re excited to announce the launch of Welltree Analytics, a specialized consultancy dedicated to elevating clinical trials and medical research through cutting-edge biostatistics. 🎉 At Welltree Analytics, we bring extensive expertise in advanced statistical methods, including Bayesian Interim Analysis, AI-driven insights, survival analysis, and adaptive trial designs. We know the critical role that precise data analysis plays in driving impactful clinical results, and our goal is to provide seamless, high-quality support for teams working to innovate in healthcare. Whether you're a research organization, pharmaceutical company, or a healthcare startup, we’re here to empower your clinical journey with: ✨ Customized trial design & planning ✨ Innovative real-world data & AI solutions ✨ Accurate, regulatory-compliant reporting If you’re looking for a partner to ensure data-driven, compliant, and optimized outcomes in your clinical research, let’s connect! Together, we can bring your studies to the next level. 🌐 Visit us at https://lnkd.in/gWe8SrEC #Biostatistics #ClinicalTrials #HealthcareInnovation #DataAnalysis #WelltreeAnalytics #AIinBiostatistics #ClinicalResearch #Pharma #HealthTech

The future of clinical research is here, powered by patients' willingness to share their health data and the innovation of AI-driven technologies. By integrating data from diverse sources, biopharma companies can accelerate research, enhance trial designs, and bring new therapies to market faster. Dive into this topic and the actions to take here: #ClinicalTrials #ClinicalResearch

For providers that conduct clinical research, participant inclusion and exclusion data are often buried in digital, unstructured doctor’s notes and diagnostic image files within EMR systems.  Traditional recruitment methods overlook these qualifying details and can lead to participant attrition – and more importantly, can lead to trial non-compliance and disqualification.  This scenario is very costly and most importantly, can further delay time to market / patient for potentially life-saving therapeutics.    Read our latest blog to see how LLMs can enhance trial recruitment and execution, positioning the study for success. #generativeai #responsibleai #LLM #pharma #healthcare #provider

By focusing on responsible by design principles and utilizing advanced data encryption technology, generative AI can assist patients, trial sponsors, and site managers realize substantial efficiencies, cost savings and increased patient adherence. #clinicaltrials #generativeai #uniqeminds #healthcare

Drug Discovery & Development brings us expert predictions covering synthetic data, hybrid trials, and more. Brent Dover of Carta Healthcare, joins the conversation and sees 2025 as a “turning point for AI-powered clinical trials.” “I believe 2025 will be the year drug researchers begin harnessing the power of AI at scale to accelerate clinical trials and get life-saving treatments into the hands of patients faster. Quality data is the most important ingredient for improving healthcare, but that data often is buried in unstructured clinical notes. Fortunately, AI-based tools are available today that, along with the help of clinical experts ‘in the loop,’ enable providers to leverage insights from clinical data for drug trials and medical registries. Expect more providers to adopt these clinical data abstraction tools in the coming year and beyond.” Brian K. Buntz has the story: https://bit.ly/4g2tkAu | #DrugResearch #ResearchData #AIinHealthcare #QualityData #ClinicalDataAbstraction

#Topics 9xchange Partners with PhaseV on Causal Machine Learning Clinical Trial Optimization [ad_1] PhaseV, a leader in applying causal machine learning (ML) for dynamic clinical trial analysis and optimization, has formed a partnership with Israeli biopharma marketplace 9xchange. The collaboration integrates PhaseV’s ML technology into 9xchange’s transaction platform, providing its members the ability to retrospectively analyze and optimally design and execute advanced clinical studies.Anat Naschitz, CEO and co-founder of 9xchange, stated, “Too many deserving drugs never get to patients due to insufficient resource or attention, or objective issues such as suboptimal trial design. The seamless, online and initially anonymous transaction path offered by 9xchange removes friction and unveils unexpected availability and matches, while enabling members to tap into new value through a range of AI/ML technologies. For our members, the PhaseV partnership means new opportunities. Owners can chart a new course for assets lost to trial failure, increase the value at sale and build confidence in a likely outcome. Buyers and investors can conduct due diligence on an asset and circumscribe the cost and probability of success. We build partnerships carefully, and are excited to col...

The demand for data analysts (DAs) in Biostatistics is expanding due to the increasing reliance on data-driven decision-making in healthcare and pharmaceuticals. Altair RapidMiner is a powerful data analytics and AI platform that can significantly enhance biostatistics, particularly in clinical research and data analysis. Here are several ways it can be beneficial: 𝐂𝐨𝐦𝐩𝐫𝐞𝐡𝐞𝐧𝐬𝐢𝐯𝐞 𝐃𝐚𝐭𝐚 𝐏𝐫𝐞𝐩𝐚𝐫𝐚𝐭𝐢𝐨𝐧: Altair RapidMiner provides robust data preparation functionalities, allowing users to acquire, cleanse, and transform data efficiently. 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 (𝐀𝐮𝐭𝐨𝐌𝐋) : The platform offers automated machine learning capabilities that streamline building and testing statistical models. This feature saves time and resources, enabling biostatisticians to focus on interpreting results rather than excessive model development. 𝐕𝐢𝐬𝐮𝐚𝐥 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞: Biostatisticians can create visual workflows to analyze complex datasets, making it easier to identify patterns, trends, and anomalies in clinical trial data. 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐄𝐱𝐢𝐬𝐭𝐢𝐧𝐠 𝐓𝐨𝐨𝐥𝐬: The platform supports integration with various third-party machine learning libraries, allowing biostatisticians to leverage existing methodologies while utilizing RapidMiner's advanced features. 𝐑𝐞𝐚𝐥-𝐓𝐢𝐦𝐞 𝐃𝐚𝐭𝐚 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠: RapidMiner enables processing and visualization of real-time data, which is particularly useful in monitoring clinical trials as they progress. This capability allows timely interventions if anomalies or trends are detected. 𝐄𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐥𝐞 𝐀𝐈 : The platform emphasizes transparency in model building, helping biostatisticians understand the underlying mechanics of their models and build trust in their predictions. This is important in regulatory environments where interpretability is required. 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬 : RapidMiner facilitates collaboration among team members by allowing users to share workflows and insights easily. In biostatistics, where multidisciplinary teams work together, this feature enhances communication and efficiency. 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐚𝐥 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐒𝐮𝐩𝐩𝐨𝐫𝐭: The platform includes a wide range of native algorithms and statistical functions crucial for conducting various analyses in biostatistics, from hypothesis testing to survival analysis. 𝐃𝐚𝐭𝐚 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐓𝐨𝐨𝐥𝐬: With built-in tools for creating dashboards and visual reports, RapidMiner helps biostatisticians present their findings effectively to stakeholders, enhancing communication of results from clinical studies. #Biostatistics , #DA, #ML, #OnlyForward Pavan Kallurkar https://lnkd.in/gP_P4cru