Managing Complex Biomarker Data Archives

On Demand

Duration: 20 minutes

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What you’ll learn:

Learn how to use practical, conversational AI to amplify the power of your biomarker-rich clinical programs with QuartzBio’s Biomarker Intelligence Platform.

Ask a question, get an answer, and gain valuable insights across the precision medicine data ecosystem.
Powered by the first ensemble of Precision Medicine Large Language Models (LLMs)
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)

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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, large language models (LLMs), 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 LLMs 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 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.

Precision Medicine Ecosystem and QuartzBio's Biomarker Intelligence Platform — The Precision Medicine Ecosystem and its interaction with QuartzBio’s Biomarker Intelligence 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 LLMs, 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
Balancing accuracy, speed, and cost efficiency

In this series of posts, we will explore the details of each of these considerations.

Follow QuartzBio for the rest of the story!

And if you’re interested in joining one of our in-person Biomarker Intelligence Summits for R&D organizations to share challenges and opportunities facing data-rich clinical programs, please get in touch.

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“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 Biomarker Intelligence 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 Biomarker Intelligence Platform, powered by AI: An ecosystem of domain- and task-specific small LLMs trained by fine-tuning existing foundational models (FMs). — **QuartzBio’s 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.
Efficiency: Smaller models reduce computational overhead.

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.

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QuartzBio’s team has deep experience in technology-enabled solutions for the life science industry. In this blog series, we invited you to get to know a member of the QuartzBio team.

This month, we are delighted to talk with Caitlin Cook, QuartzBio’s Director, Customer Success. After learning about Caitlin here, please feel free to connect with her on LinkedIn.

In your own words, what do you do?
Modern drug development is a collaborative process involving a multitude of stakeholders – from scientists and researchers to data analysts and regulatory professionals. My team’s role is to foster and maintain strong, trust-based relationships between our company and our clients while also encouraging collaboration among all those various teams. In essence, we’re the glue that binds these elements together and ensures that the exchange of knowledge, expertise, and data flows seamlessly.

As the Director of Customer Success, my mission is crystal clear: to empower our clients with the knowledge, tools, and support they need to thrive in an increasingly data-driven world. This role is at the intersection of technology and human connection, bridging the gap between innovation and its real-world impact. My team and I provide solutions to help pharmaceutical and biotechnology companies accelerate the development of new treatments for the patients that need them. We encourage our customers to think differently about the way they currently approach sample and biomarker data management.

One of the most exciting aspects of my work is the opportunity to guide our clients through the dynamic and ever-evolving realm of data management. We work hand in hand with pharmaceutical companies to design custom solutions that align perfectly with their needs. This journey involves identifying challenges, setting clear objectives, and creating a roadmap to success.
What is your fondest memory of working at QuartzBio?
I was fortunate enough to be part of an amazing milestone for QuartzBio: our inaugural User Summit in November 2022. The Summit was a testament to the strength of community, shared vision, and commitment to the advancement of clinical biomarker sample and data operations management.

The challenges in the industry are manifold, and we wanted to hear directly from our clients to understand their unique perspectives. As Clinical Biomarker Sample and Data Operations Managers, they are the unsung heroes navigating a complex ecosystem. Common industry challenges echoed loudly, and the Summit included discussions around data integration, data quality, and the need for more efficient and scalable solutions.

The discussion at the Summit validated the need for a reliable partner to alleviate these burdens. It provided a platform for our clients to voice their current challenges, but more importantly, it served as a catalyst for solutions. The main takeaways from our clients were both inspiring and invigorating. The clear message I took away from our time together was that our products are pivotal in lessening the manual labor that often leads to resource burnout and attrition. By providing the right tools to do their jobs, we’re contributing to a healthier, more sustainable work environment. We empower our clients to define success within their organizations by providing data that contributes directly to the creation of Key Performance Indicators (KPIs). This alignment between our technology and their vision is a driving force behind their success. The resonance between our company culture and our clients is a testament to the mutual commitment to progress and innovation.

We’re not just partners; we’re collaborators in a shared journey. Our clients value us for our efficiency and flexibility. In an industry marked by constant change, these attributes ensure our solutions evolve with them.

I couldn’t help but be excited about the future. After attending that event and talking with our clients, I knew I made the right choice to join the QuartzBio leadership team.
Complete this sentence: QuartzBio is _________ because _________.
QuartzBio is pioneering because of our innovative and groundbreaking role in the field of biomarker data platforms.

Describing QuartzBio as ‘pioneering’ captures the company’s commitment to both push the boundaries of what is possible and lead the way in a field that is critical for the future of healthcare and clinical research.
Complete this sentence: QuartzBio customers are _________ because _________.
QuartzBio customers are resilient and creative because they are caring and innovative.
What piece of art – book, movie, music, artwork, etc. – inspired you the most and why?
Living in Atlanta, Georgia for more than 10 years has given me insights and fresh perspectives to a melting pot of creativity. I spent much of my time during the pandemic quarantined in the north-end of the city where violent riots, looting, and vandalism destroyed most of the shops in the area. In one shop, though, there was a sculpture of a silver woman standing resilient and untouched. This metal composite figure turned out to be the work of Martin Dawe, a sculptor famous to local Atlantans for his giant historical pieces around the city such as the World Athletes Monument and the Dr. Martin Luther King Jr. monument.

The silver woman, also known as ‘Repose’, inspired me and is in my home today. She is a testament of strength and grace, and a reminder to me to be unwavering in how I show up in the world every day.
What’s the best piece of advice you have ever been given?
“Every day for the rest of your life you will find yourself at one of three phases: aspiration, success, failure. You will battle ego in each of them. You will make mistakes in each of them. You must sweep the floor every minute of every day. And then sweep again.” – Ryan Holiday

My interpretation: The work to improve never stops. You can sweep your floors and yet they are dirty again tomorrow. Effort isn’t a one-time thing. You must commit to yourself and others each day, over and over again.

Connect with Caitlin on LinkedIn

Explore patient biomarker profiles across assays and vendors with a single solution

Duration: 30 minutes

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What you’ll learn:

Biomarkers, when used to guide clinical programs, could mean the difference between success and failure.

But exploratory biomarker data can be a headache to manage. Translational and data science teams struggle with disconnected data flows from specialty labs, sponsor data processing pipelines, and clinical data stores.

Join Bill Hall for a webinar demo of the QuartzBio^® enterprise Biomarker Data Management solution.

We’ll show you how to

Generate patient profiles to view tumor burden over course of treatment
Explore multi-marker views of patient profiles
Review ancillary data (e.g. images)
Evaluate patient profiles on a cohort level
Cross-reference biomarker measures across file types; e.g., compare ctDNA profiles of interest with clinical efficacy biomarkers such as immunohistochemistry

Who should attend: Translational Research teams, Biomarker Operations teams, Clinical/Biomarker Data Science teams, Clinical Development teams, Bioinformatics and Computational Biology teams, Office of the CIO/CTO, Data Management teams

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AI/ML can be a powerful, error-reducing tool for managing clinical sample data as well as biomarker data.

AI/ML-based tools should not replace human judgment, particularly for insight generation, at least until AI/ML-based tools are extensively and rigorously validated (as any piece of critical software would be). Furthermore, regulatory compliance and data privacy are of utmost importance and must be considered when building and using solutions that leverage generative AI frameworks.

However, near-term applications of AI/ML can dramatically improve any tedious process involving a human inspecting data. We list some of these processes in the box below, along with steps we recommend taking to reduce risk in each case.

Register to Watch Webinar On Demand:

Biomarker data can be time-consuming to clean and prepare for analysis, because assay results data files are often disconnected and have inconsistent formats.

This “data chaos” prevents translational, clinical, and bioinformatics teams from extracting insights to advance therapeutic development.

Join the webinar led by Adam Brown and Mike Waters, who will show how using a unified biomarker data management solution to acquire and process biomarker data, connected to clinical and sample data, empowers teams to break down data silos, creating an integrated data asset across the enterprise.

You’ll learn how the QuartzBio^® enterprise Biomarker Data Management solution enables teams to:

Systematically verify data quality, consistency, and availability with automated checks
Navigate and explore cleaned, annotated data at scale across your entire portfolio—whether a single program or hundreds of studies, at all phases of development
Link assay and clinical data across file types from any assay technology–transcriptomics, genomics, proteomics, flow cytometry, imaging, and more
Explore and visualize biomarker trends across cohorts, subjects, and timepoints and perform exploratory analyses to surface signals of interest
Integrate non-clinical/pre-clinical data to further enhance your data asset

During the presentation, the team will highlight how QuartzBio’s scalable data standardization and integration technology helps scientists shorten time from data acquisition to data insight and exploration of historically siloed data.

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Who should attend:
Translational Research teams, Biomarker Strategy teams, Clinical/Biomarker Data Science teams, Clinical Development teams, Bioinformatics and Computational Biology teams, Office of the CIO/CTO, Data Management teams

QuartzBio Connecting Raw Processed and Ancillary Data

October 31, 2022 – Translational and clinical teams spend more than 70% of their time managing, cleaning, and harmonizing data generated in biomarker-rich clinical programs.

In a recent webinar, Adam Brown demonstrated how the QuartzBio® enterprise Biomarker Data Management (eBDM) solution addresses one set of frequently intractable challenges: connecting raw, processed, and ancillary data across multiple clinical studies.

We invite you to sign up for on-demand access to the recorded webinar.

Multiple Assay Modalities, File Types, Data Storage Locations

As we have previously described, research teams are generating biomarker data from a wide variety of assay modalities, and this data can be housed in multiple, disconnected storage locations. In the example use case described in the webinar, data was being generated from targeted assays like flow cytometry and immunohistochemistry to high-throughput omics assays.

The QuartzBio eBDM solution is specifically engineered to ingest, standardize, visualize, and analyze this data. The unified data platform connects raw and processed data to ancillary files, such as the images used for immunohistochemistry quantification or PDF omics reports. All of the raw files are available for download individually or in bulk. They can also be previewed directly within the user interface.

As shown in Video 1, the QuartzBio enterprise data platform can centralize and harmonize data from multiple file types across clinical programs, including:

Image files
Tabular files
Omics files, e.g., BAM or VCF files
Sequencing reports for particular mutations or genomic regions of interest

**Video 1** (Click image to view video): The QuartzBio enterprise data platform can centralize and harmonize data from multiple file types across clinical programs. Video demonstrates access to images, PDF files, and genomics data.

As shown in Video 2, the QuartzBio eBDM solution can combine processed files with harmonized clinical annotations, with both subject and sample level data, as well as the relevant quantified reportables for a specific assay modality. These reportables are very configurable and can be changed according to the needs of a sponsor, a program, or even a specific study.

**Video 2** (Click image to view video): Processed files combine harmonized clinical annotations with both subject- and sample-level data.

The QuartzBio team can also further preprocess raw assay data directly and apply quality control metrics as well as normalization techniques. We can also extract relevant data and metadata from PDFs, such as omics reports and informed consent forms.

In summary, the webinar demonstrated how the biomarker data modules of the QuartzBio platform can enable easy access to both key raw and processed data assets through the user interface, in addition to robust visualization and data exploration capabilities.

Flexible Biomarker Data Management Means Faster Deployment

QuartzBio’s enterprise-grade Biomarker Data Management application provides a flexible, scalable solution for transforming biomarker data into consumable information across a sponsor’s entire study portfolio.

This resilient approach is enabled by a robust enterprise data platform with a library of pre-built, configuration-ready pipelines for data ingestion.

Contact us to learn more about data management SaaS solutions and let us know which additional features and capabilities you’d like featured in our next webinar.

Contact Us to Continue the Conversation