Hi folks! You can identify the 2 to 5 targets most likely to advance from in-silico models to in-vivo studies and further one candidate that will translate to clinical studies. Tomorrow, in our live webinar, we will share a framework required to select the exact targets that successfully validate. Register now to join and learn how to:
Automate evidence extraction: Pull context-rich data from full-text papers to bypass manual curation bottlenecks.
Establish biological context: Find the exact mechanistic proof required to understand disease progression.
Connect data to AI: Integrate trusted evidence into your current AI tools via MCP servers to test hypotheses in real time.
This approach helps teams easily compare candidates, eliminate weak targets early, and construct a defensible shortlist. Can’t attend live? Register, and we will send you the recording.
Hey guys, Most knowledge graphs miss a critical piece of the puzzle: the mechanistic evidence buried deep within full-text papers, supplementary tables, and figure legends. At Elucidata, my team is changing this. We are also building MCPs that connect these evidence-rich knowledge graphs directly to AI assistants like Claude and ChatGPT. On July 14th, join our Senior Product Manager, Jainik Dedhia, and Scientific Manager, Krishna Patel, for an exclusive webinar demonstrating this workflow in action, in the specific context of AML. They are asking the question "What pushes a leukemic blast out of a self-renewing, differentiation-arrested state and onto a myeloid differentiation trajectory?" What you will see during the session:
AML Case Study: How we reconstructed disease-state transitions in Acute Myeloid Leukemia (AML).
Live Demonstration: How our MCP connections enable scientists to query mechanistic evidence
Hi guys Treatment-induced lineage plasticity is a major hurdle in prostate cancer therapy. Join Pawan Verma and Kewal Mishra at American Association for Cancer Research 2026 in San Diego to see how we are using Causal Knowledge Graphs to predict new therapeutic vulnerabilities and repurpose drugs for NEPC. https://www.linkedin.com/feed/update/urn:li:activity:7447996835782397952
Hi guys Treatment-induced lineage plasticity is a major hurdle in prostate cancer therapy. Join Pawan Verma and Kewal Mishra at American Association for Cancer Research 2026 in San Diego to see how we are using Causal Knowledge Graphs to predict new therapeutic vulnerabilities and repurpose drugs for NEPC. https://www.linkedin.com/feed/update/urn:li:activity:7447996835782397952
Hi guys! How are you all? Have you had a chance to register for DataFAIR Global on March 12? This virtual-only event is the digital precursor to our flagship DataFAIR Boston summit on March 19. We will discuss how to measure progress in AI for Drug Discovery: The Turing Test for Drug Discovery. Specifically, we will be asking our leaders to -
Score the Problems: Which end-to-end tasks are the most valuable to solve from a strategic and economic standpoint?
Define the "Pass" Criteria: What must AI achieve to complete these tasks successfully even with a human-in-the-loop to be considered transformative?
Event Details Date: March 12, 2026 (Virtual) Agenda & Registration: https://www.elucidata.io/datafair-2026-spring You can register here to join
File competitive RFPs and compress tech transfer timelines by modernizing your data infrastructure. We are hosting an interactive session to show exactly how agent-based AI workflows contribute directly to revenue goals. Current challenges in the CDMO industry rely on data accuracy. From modeling plant capacity to ensuring gene vector purity, success requires a shift from static reports to dynamic knowledge graphs. You will learn how to:
Accelerate Tech Transfer: Move molecules from the lab to production faster.
De-risk Operations: Validate data to stop manual entry errors and batch failures.
Ensure Compliance: Use GxP-compliant AI that documents every decision for auditors.
Hey folks, For most of history, menstrual blood has been treated as something to hide and never as data. With NextGen Jane’s tampon-based multi-omics approach, menstrual fluid is now becoming a valuable diagnostic resource. Stephen Gire, CSO at NGJ, said in an article. “With molecular tools, physicians could potentially diagnose and treat earlier, drug developers could find new targets, leading to more-refined therapeutics, and run more-efficient clinical trials.” Read more. We are excited to have him join our experts for our upcoming webinar, Building a Predictive Diagnostic Model from Menstrual Fluid Data. We will break down new insights and practical ways to work with a sample type that has hardly been studied before. Learn how to turn scattered clinical notes, symptom histories, and EMR data into a unified picture alongside menstrual‑omics and see a concrete framework for connecting longitudinal patient records to new datasets so your predictive models are reliable enough, straight from the experts who have already done it. Date - December 2nd, 2025 Time - 9 AM PT Register Now to Join Menstrual fluid is one of the richest and untapped biological samples in modern medicine. It carries genomic, transcriptomic, proteomic, and immune signatures that can reshape how we diagnose conditions earlier and more accurately. Your insights, skepticism, and questions can enrich a conversation that has been absent from mainstream biomedical research. If relevant, please circulate it within your network.
Hey folks! Developing new therapies for autoimmune diseases like RA and lupus is a significant challenge, despite a $160B+ global market need. Many translational teams struggle to build a robust biomarker strategy, leading to delays in IND filings and trial initiation. Our upcoming session will show how a distinctive combination of technology and expertise equips your team to:
Validate the most impactful biomarker endpoints for your specific drug candidate.
Integrate patient-reported outcomes (PROs) with biomarkers to lower trial cost and reduce patient burden.
Design an informed, de-risked Phase 1 trial that accelerates your path to approval.
To share how leading biopharma teams are building these data-driven strategies, we invite you to this session. Register Now to request your invite
Hey folks! Clinical and real-world datasets hold enormous potential for discovery and trials, but the data rarely aligns. Patient records remain fragmented, inconsistently defined, and siloed across labs, imaging, omics, and outcomes. In fact, most EHRs capture little more than demographics and diagnoses but leave high-resolution measurement and molecular context out of reach. What's the cost?
Weeks (sometimes months) lost pulling data just to define a cohort.
Gaps that skew models and introduce bias.
Slowdowns in translational pipelines, biomarker validation, and trial readiness.
What if you could bring patient and molecular data into one knowledge graph that’s ready to use? Join us for Incorporating “Patient Data” into Knowledge Graphs, a practical session on how to turn heterogeneous clinical data into a coherent, privacy-preserving, and update-ready knowledge graph that accelerate translational research. Date: September 18, 2025 Time: 10:30 AM PST / 1:30 PM EST Register Now to request your invite!
Hey folks! Clinical and real-world datasets hold enormous potential for discovery and trials, but the data rarely aligns. Patient records remain fragmented, inconsistently defined, and siloed across labs, imaging, omics, and outcomes. In fact, most EHRs capture little more than demographics and diagnoses but leave high-resolution measurement and molecular context out of reach. What's the cost?
Weeks (sometimes months) lost pulling data just to define a cohort.
Gaps that skew models and introduce bias.
Slowdowns in translational pipelines, biomarker validation, and trial readiness.
What if you could bring patient and molecular data into one knowledge graph that’s ready to use? Join us for Incorporating “Patient Data” into Knowledge Graphs, a practical session on how to turn heterogeneous clinical data into a coherent, privacy-preserving, and update-ready knowledge graph that accelerate translational research. Date: September 18, 2025 Time: 10:30 AM PST / 1:30 PM EST Register Now to request your invite!
