Time-saving global filters: Instead of applying the same filters across multiple charts in a dashboard, you can now apply dashboard-level common filters, and all visualizations will instantly reflect your filtered dataset.
Improve collaboration and onboarding with organizational sharing: New “share with all” functionality enables organization-level permissions. New users can access dashboards as soon as they log in.
Visualization engine enhancements:
Statistical tests, including parametric and nonparametric tests, for richer biomarker data analysis / visualization (Figure 1)
Sample testing status heatmap for rapid insights (Figure 2)
Figure 1. Statistical tests are now available, including statistical tests for boxplots: Compare boxplots within a series to determine if their mean difference is statistically significant.
Figure 2. Sample status heatmaps added as visualization options. Gain rapid insights into multiple sample statuses to track sample collection or testing, as part of our Sample Intelligence Solution.
by Tobi Guennel, PhD, SVP of Product Innovation, QuartzBio
I just read Microsoft’s latest Work Trend Index report, “The Year the Frontier Firm Is Born,” and it resonates deeply with the challenges and opportunities we’re seeing in precision medicine R&D.
The report highlights a seismic shift: the rise of AI agents isn’t just about automating tasks; it’s about fundamentally rewiring how businesses operate.
Key takeaways from the report include:
Intelligence on Tap: AI is becoming an abundant, on-demand resource, offering “digital labor” to bridge the gap between increasing business demands and human capacity.
Human-Agent Teams: The future isn’t human vs. machine, but human + machine. Teams will increasingly integrate AI agents as “digital colleagues,” shifting the focus from functional silos to outcome-driven “Work Charts”. This requires a new mindset, viewing AI not just as a tool, but a thought partner.
Every Employee an Agent Boss: Managing and directing AI agents will become a core skill across all levels, accelerating careers and enabling more strategic work earlier.
This vision of AI-augmented work mirrors the complexities we navigate daily in the precision medicine value chain.
Currently, getting answers often involves a complex “information ping-pong” across various teams and systems, delaying critical insights. Clinical trials generate vast amounts of data, yet extracting timely value remains a significant hurdle for many organizations.
At QuartzBio, we believe the future lies in connecting this intricate value chain. We envision a future empowered by a seamless, semi-autonomous system – our Precision Medicine AI Agent Platform. This network of specialized AI agents is designed not to replace human expertise, but to amplify it.
Our platform aims to:
Autonomously ingest and manage complex data streams across the R&D ecosystem.
Enable conversational interaction, allowing researchers and operational teams to interrogate data and receive insights in seconds, not weeks.
Proactively deliver rich, contextual information to support strategic decision-making.
Foster interoperability and collaboration, breaking down data silos.
By integrating human ingenuity with intelligent agents, we can shift the focus from manual processes to strategic insight generation, ultimately accelerating the delivery of novel treatments.
The “Frontier Firm” concept isn’t just a future hypothetical; it’s the operational model we are building towards in life sciences today.
https://www.quartz.bio/wp-content/uploads/2025/04/QB_LinkedIn_AI-Agents-Reshape_1200x1200_A.jpg12001200Chandreyee Dashttps://www.quartz.bio/wp-content/uploads/2025/03/QuartzBio-Banner-Logo_Blue.svgChandreyee Das2025-04-29 12:32:272025-05-09 15:45:29The Dawn of the Frontier Firm: How AI Agents Are Reshaping Work & Precision Medicine
Duration: 30 minutes, on demand
Sign up to watch the webinar:
What you’ll learn:
R&D teams in biomarker-rich clinical trials are constantly chasing insights around a complex data ecosystem. By the time stakeholders find their data, gain access, ideate on the right analysis and get results, the chance to make impactful decisions may be over.
Domain-specific AI agents, orchestrated by our Precision Medicine Virtual Assistant, enable operations, translational, and informatics teams to conversationally interact with a connected ecosystem of biomarker, sample, and clinical data.
Join Bill Hall as he chats with the Virtual Assistant, conversationally extracting insights in seconds, achieving:
Amplified Operational Efficiency: e.g., “Show me biopsy samples from patients in the 70th percentile of JAK2 expression at baseline”
Autonomous Workflows & Interoperability: e.g., automatically ingesting and harmonizing assay data upon arrival from testing lab
Amplified Translational Research: e.g., ““Compare gene expression profiles for responders vs non-responders at baseline”
You’ll learn how QuartzBio’s approach transforms the way precision medicine teams work with 360° intelligence.
Who should attend:
Translational Scientists
Biomarker Operations and Biospecimen Operations Teams
https://www.quartz.bio/wp-content/uploads/2025/04/LinkedIn_MAY-Webinar_1200x1200_Grey-A-2.jpg12001200Chandreyee Dashttps://www.quartz.bio/wp-content/uploads/2025/03/QuartzBio-Banner-Logo_Blue.svgChandreyee Das2025-04-11 13:34:422025-05-22 12:39:13Webinar: Precision Medicine AI Agents Accelerate Data-to-Insights
Watch the full episode:
Tobi Guennel, PhD, SVP of Product Innovation at QuartzBio, joins AI expert Srivatsan Nagaraja to discuss his insights on integrating AI into the precision medicine value chain in an episode of the Life Sciences D’n’A Podcast.
Tune in to learn about:
Leveraging AI and advanced analytics to improve clinical trial efficiency
Using AI agents to automate clinical trial operations
https://www.quartz.bio/wp-content/uploads/2025/03/QB_LinkedIn_Integration-AI-Podcast_1200x1200.jpg12001200Chandreyee Dashttps://www.quartz.bio/wp-content/uploads/2025/03/QuartzBio-Banner-Logo_Blue.svgChandreyee Das2025-03-27 19:07:382025-07-07 14:16:49Podcast: Integrating AI into Precision Medicine
For teams working at the interface between precision medicine and information technology, don’t miss meeting the QuartzBio team at the Bio-IT World Conference and Expo (April 2-4, 2025, Boston, MA).
QuartzBio will be presenting
“The Precision Medicine AI Agent Network: Intelligence at Scale”
4:00 PM, Thursday, April 3, Cloud for AI/ML & Modern Data Science track
We’ll demonstrate how a network of domain-specific AI agents amplifies efforts of translational, informatics, and IT teams, using AI-driven integration of biomarker, sample, and clinical data.
This unified, scalable solution shortens time from data to insights, analytics, and visualizations, accelerating study close and time-to-market.
Then visit booth #614 to explore our Precision Medicine Intelligence Platform, hands-on!
https://www.quartz.bio/wp-content/uploads/2025/02/LinkedIn_BioIT2025_AI-Agent-Network_A.jpg12001200Chandreyee Dashttps://www.quartz.bio/wp-content/uploads/2025/03/QuartzBio-Banner-Logo_Blue.svgChandreyee Das2025-02-17 21:27:342025-05-09 15:46:10Join QuartzBio at Bio-IT World | Booth #614
19 December 2024 — Before we celebrate the new year, let’s celebrate new feature releases, brought to you by the winning collaboration between QuartzBio’s product teams, managed services teams, and, most of all, our clients.
This month, we released version 10.0.0 of QuartzBio’s Precision Medicine AI Agent Platform, delivering enhancements to the enterprise Biomarker Data Management (eBDM) and virtual Sample Inventory Management (vSIM) use cases for biomarker and sample intelligence, as well as the underlying Enterprise Data Platform, which supports data management activities.
If you’re a current QuartzBio user, log in now to see how these features and improvements can help you work faster and impress your colleagues.
Highlights of What’s New
Sample Intelligence (vSIM) and Biomarker Intelligence (eBDM) products:
Create tailored plots easily and update plots in real time with more flexible visualization tools (Figure 1)
Easily navigate, filter, sort Data Hub and Dashboard elements with intuitive new layouts
Group connected resources of different types with new “Activity” tag (Figure 2)
Faster access to vSIM reports with more customizable data table outputs
Figure 1. New plot options enhance readability, offering full labels, color palette selection, and more flexible plot rendering.
Figure 2. Activity Tag: Quickly identify all resources related to a specified “Activity” (e.g., Sample Collection Monitoring) using this new tag and filter.
Enterprise Data Platform (EDP data management layer):
Improved efficiency and accuracy with enhanced file and vault management
Robust process tracking with auditable trail of user actions
Slice data faster with enhanced Global Search queries (Figure 3)
Figure 3. Advanced global search filters: Efficiently perform advanced global searches by applying filters directly from the UI. R and Python queries are automatically generated based on the filter values, saving time and eliminating manual steps.
Feedback?
We love to hear from current and potential users! Let us know your thoughts on this release and ideas for future enhancements!
https://www.quartz.bio/wp-content/uploads/2024/12/Figure-1-for-24R3-post-1.png664829Chandreyee Dashttps://www.quartz.bio/wp-content/uploads/2025/03/QuartzBio-Banner-Logo_Blue.svgChandreyee Das2024-12-19 10:10:362025-04-08 17:41:36QuartzBio Platform Version 10.0.0: Flexibility, Efficiency and Accuracy
Interoperability in Precision Medicine: What does it mean?
In modern drug development, connectedness is crucial for success, especially in remote and decentralized teams. This connectedness involves linking people and information to extract shared insights from data and make faster decisions.
In practice, this means ensuring interoperability of data, technology, systems, and ecosystems through a scalable, modular data fabric architecture. It connects various data sources, including enterprise data lakes, biomarker data, sample data, clinical sites, real-world information, and public databases, to create a robust data and insights supply chain (Figure 1, below).
Interoperability in Precision Medicine: Why does it matter?
Interoperability is vital for precision medicine as it enables seamless integration of applications and workflows for data analysis, storage, and processing. This reduces human intervention, minimizes variability, and enhances data reproducibility.
The Data-Value Gap: Only 32% of companies have reported being able to extract business value from their data, and only 27% have described the output of data and analytics projects as being “highly actionable.” Interoperability of systems and technologies closes this gap.
QuartzBio’s Precision Medicine AI Agent Platform uses a fully interoperable, scalable, and modular data fabric solution to maintain connectivity with all data streams across complex technology and vendor ecosystems generated by R&D programs. This platform supports cross-ecosystem interoperability and generates insights using business intelligence tools.
QuartzBio’s approach drives value for multiple teams by unifying point solutions and enabling sample and biomarker insights to flow freely between operations teams, translational researchers, data science/bioinformatics teams, and business executives, thus powering decision-making for day-to-day use cases.
By creating a data fabric architecture to ingest and harmonize data and technologies spanning across this complex ecosystem, QuartzBio’s Precision Medicine AI Agent Platform can serve as either a standalone enterprise system supporting Precision Medicine, or a robust system that can integrate seamlessly and serve domain-specific functions in the context of the broader drug ecosystem.
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QuartzBio’s approach drives value for multiple teams by unifying point solutions and enabling sample and biomarker insights to flow freely between operations teams, translational researchers, data science/bioinformatics teams, and business executives, thus powering decision-making for day-to-day use cases.
By creating a data fabric architecture to ingest and harmonize data and technologies spanning across this complex ecosystem, QuartzBio’s Precision Medicine AI Agent Platform can serve as either a standalone enterprise system supporting Precision Medicine, or a robust system that can integrate seamlessly and serve domain-specific functions in the context of the broader drug ecosystem.
The Opportunity: Closing the Data-Value Gap
As sponsors invest more and more resources in generating data as part of clinical programs, there is increasing pressure to close the data-value gap. Because QuartzBio’s platform is built to be fully interoperable with clients’ systems and applications, clients can recognize immediate value across multiple functions across their enterprise.
Figure 1. A typical Precision Medicine Ecosystem and how QuartzBio’s Precision Medicine AI Agent Platform fits within it, providing data fabric architecture tailored for Precision Medicine.
https://www.quartz.bio/wp-content/uploads/2024/11/QuartzBio-approach-to-interoperability_.jpg11171080Chandreyee Dashttps://www.quartz.bio/wp-content/uploads/2025/03/QuartzBio-Banner-Logo_Blue.svgChandreyee Das2024-11-21 14:18:572025-03-26 10:35:52System and Ecosystem Interoperability: How Connectedness Drives Drug Development
Ask a question, get an answer, and gain valuable insights across the precision medicine data ecosystem.
Powered by the first network of Precision Medicine AI Agents.
Supercharges the day-to-day work of translational researchers, data scientists, and informatics teams.
Join Bill Hall as he chats with QuartzBio’s Virtual Assistant, conversationally extracting insights in seconds with questions such as:
“Which mutations have highest prevalence at baseline?”
“Which subjects are in the 70th percentile of JAK2 expression at baseline and have stored, consented, baseline samples?”
“What is the correlation of JAK2 and STAT1 expression at baseline across samples?”
You’ll discover QuartzBio’s approach, which employs smart, automated integration of biomarker, sample, and clinical data to create a unified data ecosystem – now amplified with the power of conversational interactions to enable more consumable insights, regardless of your data expertise.
Who should attend:
Translational Scientists Data Science and Bioinformatics Teams R&D Information Technology (IT)
https://www.quartz.bio/wp-content/uploads/2024/07/Linkedin_Webinar-SEPT2024_Empowering-PM-with-Conversational-AI_On-Demand-1.jpg10801080QuartzBio Teamhttps://www.quartz.bio/wp-content/uploads/2025/03/QuartzBio-Banner-Logo_Blue.svgQuartzBio Team2024-07-26 19:14:102025-07-11 15:09:09Webinar: Empowering Precision Medicine with Conversational AI — A New Era of Biomarker Intelligence
It was late in the afternoon, a windy day in Boston, as we listened to precision medicine development leaders within pharma and biotech spaces get excited about applying AI to their day-to-day work.
“We’ve gone from optimism to real opportunity here,” said one precision oncology team lead, eliciting nods across the room.
The explosion of generative AI and, specifically, AI agents, has created renewed energy, focus and promise around the hype of AI impacting the R&D lifecycle. Generative AI is revolutionizing precision medicine clinical trial planning, execution, and operations. Organizations are increasingly recognizing its potential, rallying behind AI initiatives. The race is on – the race to leverage AI as a force multiplier, knowledge amplifier and value generator, ultimately accelerating time-to-insight.
How can generative AI deliver on these promises?
Applications of generative AI and AI agents in precision medicine
AI-enabled technologies are empowering precision medicine development teams to make better decisions, faster, thanks to AI augmentation of human efforts in data processing, pattern recognition, insight generation, broadening of use cases, and performing complex queries.
As a result of these capabilities, the list of use cases for generative AI in drug development grows longer each day: drug target identification, target prioritization, patient selection, trial design, protocol generation, site management, trial monitoring, biomarker data analysis, regulatory submissions, and more.
Example use case 1: Extracting insights from previous precision medicine clinical trials to inform subsequent studies. AI and machine learning algorithms can help researchers organize and interrogate billions of existing clinical trial data points, including clinical annotations of collected samples, information from scientific literature, and exploratory biomarker data, before a new clinical trial begins.
The insights from these data sets can help identify drug targets, define the patient populations most/least likely to respond, and even identify relevant, stored clinical samples from closed studies that have been consented for future biological research.
Example use case 2: Optimizing operational efficiency of precision medicine clinical trials. Biomarker-informed clinical programs depend on the right samples and their associated data / metadata trails arriving at the right place, at the right time.
Augmenting the hard work of human clinical operations, biomarker and sample operations teams, AI-enabled technologies can monitor sample collection, informed consent and compliance, data generation, and data quality, surfacing inconsistencies in time for intervention.
Human power, optimally utilized via efficient workflows and streamlined processes, remains a key determinant of the success of a clinical program. Our goal is to establish a framework in which AI-enabled technologies amplify the talent and knowledge of human teams.
QuartzBio’s approach: amplifying talent and knowledge with generative AI and LLMs
As AI agents and domain-specific LLMs proliferate, precision medicine development organizations are discovering that these technologies have the most impact when they enable not just one team, but key stakeholders across the entire precision medicine R&D lifecycle – human-centricity and AI as an amplifier is a key focus of many organizations. In the words of Samer Ansari, Takeda Oncology’s Head of Data, digital transformation is “really about elevating the human experience.”
Organizations are moving away from point solutions, each of which address a narrow use case, and towards platform-based solutions with two key characteristics:
Platform-based solutions address broad use cases, such as the entire precision medicine development lifecycle.
They can be easily deployed in the space of a more broadly connected, interoperable data and technology ecosystem.
The Precision Medicine Ecosystem and its interaction with QuartzBio’s Precision Medicine AI Agent Platform, creating a framework for amplifying knowledge and talent across all stakeholders and teams across the enterprise. The enterprise can consist of one or many clinical programs at all stages of development.
The industry’s experience with traditional technology applications supports the need for a unifying AI-enabling framework. The average organization uses 130 different software applications, and the average worker must toggle between applications over 1,200 times a day. The result is that information and insights stay in siloes, and teams exert enormous effort just to connect data and technology.
Imagine an AI-enabled precision medicine intelligence platform, optimized for augmenting the daily work of biomarker operations teams, translational scientists, sample operations teams, data scientists, R&D IT teams, and executive-level stakeholders.
Such a tailored platform would multiply the force of each team member by empowering them with role-specific insights, based on high-quality, interconnected data, while also making it as easy as possible for teams to work together. This is the vision behind QuartzBio’s next-generation approach to generative AI for precision medicine intelligence.
Three pillars of precision medicine intelligence: conversational, prescriptive, and navigational AI
There are three core concepts that form the foundation of our approach to precision medicine intelligence: conversational, prescriptive and navigational AI.
Conversational AI enables users to conversationally interact with the precision medicine data ecosystem using natural language, for both data management and insight generation. In response, conversational AI provides easily digestible outputs and insights without requiring users to navigate the complex underlying data structures.
Prescriptive AI proactively serves up information around data anomalies and operational trends, then recommends potential actions to take based on this information.
Navigational AI drives a re-envisioned user interface for precision medicine intelligence, guiding users to the specific data, insights, and modules of an application fit for their immediate needs.
Considerations for building a generative AI framework for precision medicine
As we build a generative AI framework out of an ensemble of conversational, prescriptive, and navigational AI agents, there are four main considerations to ensure that the resulting technology remains practical and usable:
System and ecosystem interoperability via a scalable, modular approach
Task and domain specificity, including specificity for user personas
Compliance, including data privacy and security, without hampering innovation
https://www.quartz.bio/wp-content/uploads/2024/08/QB_AI_LLM-Article_Evolving-Impact_1200x1200_v1.jpg12001200QuartzBio Teamhttps://www.quartz.bio/wp-content/uploads/2025/03/QuartzBio-Banner-Logo_Blue.svgQuartzBio Team2024-07-09 16:17:202025-07-11 14:17:10From Optimism to Opportunity: Evolving Impacts of AI on Precision Medicine
“Harnessing Insights Across Clinical Trials with the Power of Conversation” — a presentation by Tobi Guennel, Ph.D., head of product development and innovation at QuartzBio
Watch the recording of the presentation:
Summary:
Discussions were lively at the “Digitization of Clinical Development & Clinical Trials” symposium at last week’s Bio-IT World conference.
Addressing an audience of biotech and pharma IT and data leaders, QuartzBio’s Tobi Guennel gave a provocative presentation on how deploying generative AI can amplify the ability of precision medicine approaches to accelerate drug development.
“It’s great to have a clinical trials-focused session at Bio-IT World, and being able to share success stories, especially about AI, in this landscape,” said Guennel. “We are firm believers that iteration and collaboration can only improve technology and create new paths for innovation.”
Guennel’s narrative centered around QuartzBio’s Precision Medicine AI Agent Platform, powered by AI, which allows precision medicine development teams to extract the most value from clinical trial samples and exploratory biomarker data.
“One benefit of natural language understanding capabilities of conversational AI is that a broad range of user personas, with diverse roles and functions, can interact with and extract insights from a unified, singular data ecosystem of sample and biomarker data.
Teams such as data science, translational research, and biosample or biomarker operations can now interrogate a unified data asset using natural language.”
Considerations for developing a large language model (LLM) ecosystem for precision medicine
To build a solid GAI framework to enable our sample and biomarker intelligence products, the QuartzBio team asked themselves:
What LLMs are needed to support our domain and the tasks performed through the components of our products?
How can we integrate these models into a scalable GAI workflow to support user stories and workflows without having to re-invent the wheel as we move from use case to use case?
QuartzBio’s Precision Medicine AI Agent Platform, formerly called the Biomarker Intelligence Platform, powered by AI: An ecosystem of domain- and task-specific small LLMs trained by fine-tuning existing foundational models (FMs). LLMs support the data management layer of the platform, the business intelligence layer to support conversational and prescriptive AI insights, and the overarching navigational AI component to enhance user experience and adoption.
Considerations for developing individual LLMs:
LLM Development
Leverage existing Foundational Models: Start with existing powerful language models that are right-sized.
Fine-Tuning: Customize these models for specific domains and tasks.
Small LLMs: Create smaller, specialized models for targeted applications for improved cost/accuracy.
GAI Integration
Prompt Engineering: Design tailored prompts to guide LLM behavior based on supported tasks.
Leverage RAG: Combine LLMs with retrieval mechanisms for enhanced performance.
User Agents: Implement user-specific agents to optimize model interactions and leverage live data.
Benefits
Precision: Fine-tuned LLMs provide accurate and context-aware responses for specific tasks.
Supporting the entire precision medicine lifecycle
QuartzBio is integrating this GAI framework seamlessly into its Biomarker Intelligence platform to support a broad range of user stories and flows with a suite of SaaS products.
Sponsors are using the platform and products to build an interconnected data asset and, subsequently, draw insights via QuartzBio’s Biomarker Intelligence tools powered by conversational AI.
Sponsors leverage the platform as a force multiplier by creating internal efficiencies. Their teams are free to focus on insight generation rather than data wrangling.
Further, the QuartzBio platform amplifies knowledge by centralizing information and insights and making these easily consumable by a wide range of stakeholders. Ultimately, this increased access to intelligence enables sponsor teams to advance Precision Medicine objectives, such as accelerating patient selection strategies, identifying drug targets, and driving clinical trial efficiency.
Learn more: Watch a demo of QuartzBio’s AI-powered platform
Join the next webinar demonstration of our platform by signing up on our Webinars & Events page! We’ll invite you to our next webinar, and meanwhile you can watch one of our recent demos on demand.
