Monday, September 22, 2025

Event: November 5: BLOODPAC "Therapy Selection Beyond DNA Mutations"

On November 5, 2025, BLOODPAC will hold a two-hour webinar on the interesting topic, "Therapy Section, Beyond DNA Mutations." RNA, digital pathology, multiomic dynamics.

Find more information and registration here.  1-3 ET, 10-12 PT.

https://www.eventbrite.com/e/new-frontiers-in-therapy-selection-beyond-dna-mutations-tickets-1708503553119

Writing,

In just a few weeks, BLOODPAC will host our fourth annual virtual New Frontiers seminar titled "New Frontiers in Therapy Selection: Beyond DNA Mutations." The event will take place on November 5th from 1:00-3:00 PM ET. Please use this link to register for the event.

This year’s New Frontiers Seminar will focus on the integration of multimodal data to inform and support therapy selection. The program will highlight emerging tools, such as RNA and epigenetic signatures, digital pathology, and more, and examine how they can be combined with liquid biopsy to capture real-time, multi-omic tumor dynamics. We’ll also discuss the challenges and opportunities of bringing these next-generation approaches into clinical practice to expand access and advance personalized cancer care.

Confirmed speakers and panelists currently include:

Speakers

  • Alexander Savchenko, Head of Diagnostic and Molecular Pathology, Novartis
  • Asaf Zviran, CEO & Co-Founder, PrismAI Therapeutics
  • Israel Tojal Da Silva, Head of Computational Biology and Bioinformatics, AC Camargo
  • Timothy Taxter, Executive Medical Director, AI Applications, Tempus AI
  • Tuvik Beker, CEO, Pangea Biomed

Panelists

  • Ben Glass, SVP, Product, AI and Translational Research, PathAI
  • Jim Godsey, Scientific Co-Chair, BLOODPAC (moderator)
  • Karim Azer, Global Head of Data and AI, Novartis
  • Matt Eaton, Head of Computational Biology and Bioinformatics, Precede Biosciences
  • Orly Alter, CSO & Co-Founder, PrismAI Therapeutics

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AI CORNER
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I gave the agenda to CHAT GPT 5 and asked it to expand on what the workshop MIGHT cover, in more detail.   Just for fun, here is what the AI guessed might occur.

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AI TEXT FOLLOWS

BLOODPAC “New Frontiers in Therapy Selection: Beyond DNA Mutations”

November 5, 2025 | 1–3 PM ET (Virtual)

This year’s BLOODPAC New Frontiers Seminar promises a focused deep dive into how multi-omic and multimodal data are changing therapy selection. The two-hour agenda brings together leaders from pharma, diagnostics, and AI to discuss the move beyond DNA mutations toward integrated decision frameworks that capture real-time tumor biology. Here’s what this likely means in practice — and what to watch for.

1. Thematic Scope: Beyond DNA = Multi-Omic Therapy Selection

BLOODPAC’s framing (“beyond DNA mutations”) signals a pivot from purely mutational calls toward functional, dynamic, and multimodal signals:

  • cfRNA & Exosomal RNA: Measuring pathway activity, fusions, and splice variants that directly inform therapy selection.

  • Methylation Signatures: Sensitive at low tumor fractions, enabling tissue-of-origin calls and immune profiling.

  • Fragmentomics: Nucleosome and size patterns that infer chromatin state, tumor proliferation, and immune activity.

  • Proteomics & Tumor-Educated Platelets: Circulating proteins and platelet RNA as early-response indicators.

  • Digital Pathology: Whole-slide imaging (WSI) features like immune cell proximity, necrosis, or TLS density that complement liquid biopsy.

  • Composite Scores: AI-driven integration of these modalities into a single predictive index.

2. Speaker and Panel Contributions: What They Likely Add

Knowing the confirmed faculty lets us anticipate specific use cases and challenges that will surface:

  • Alexander Savchenko (Novartis, Molecular Pathology): Case studies on embedding RNA, epigenetics, and digital pathology into drug development pipelines. Likely to discuss regulatory-grade assay design and cross-site harmonization.

  • Asaf Zviran & Orly Alter (PrismAI Therapeutics): Computational biology innovators who will highlight how machine learning on RNA + methylation + liquid biopsy predicts response or resistance, including approaches for algorithm validation.

  • Israel Tojal da Silva (AC Camargo): Insights from a major cancer center on applying multi-omics in clinical trial cohorts and navigating real-world logistics (sample handling, assay reproducibility).

  • Timothy Taxter (Tempus AI): Experience with large-scale multimodal data fusion — probably a case where combining WSI + RNA + DNA outperforms single-omic models for patient stratification.

  • Tuvik Beker (Pangea Biomed): Perspective on pathway-level “network activity scores” derived from RNA, and how they can predict sensitivity to targeted therapies even in the absence of canonical driver mutations.

On the panel, expect:

  • Ben Glass (PathAI): Deep dive on using AI-powered histology features as a co-equal “omic” alongside liquid biopsy.

  • Karim Azer (Novartis): Pharma view on data integration at scale and challenges for regulatory acceptance and clinical trial endpoints.

  • Matt Eaton (Precede Biosciences): Practical considerations for deploying multi-omic assays in diverse patient populations, including reference ranges and normalization.

3. Likely Discussion Tracks

a) Therapy Selection When DNA Isn’t Enough

Examples where mutation calls are inconclusive — e.g., tumors with no actionable mutation, ambiguous VAFs, or pathway redundancy — and how RNA/methylation rescue the signal.

b) Real-Time Tumor Dynamics

Moving beyond baseline biomarkers: serial blood draws to track therapy response, clonal evolution, immune activation. Look for debate about sampling cadence and “how much change is enough” to alter treatment.

c) Digital Pathology + Blood Concordance

Integrating tissue and plasma signals:

  • Resolving false negatives in ctDNA by leveraging pathology-based tumor burden metrics.

  • Using WSI-derived immune contexture to decide if a patient is an I/O responder even when blood signals are borderline.

d) Analytics & AI

Managing heterogeneous, missing-by-design data:

  • Late vs. early data fusion.

  • Model drift and reproducibility in multi-omic pipelines.

  • Version control and regulatory reporting for AI-based algorithms.

e) Pre-Analytical Discipline

Blood tube chemistry, time-to-spin, RNA stabilization — critical for multi-omic reliability. Expect mention of BLOODPAC’s pre-analytical best practices playbooks and calls for community consensus on multi-omic QC metrics.

f) Regulatory & Reimbursement Pathways

  • Regulated unit question: Is the “test” the wet lab assay, the algorithm, or the combined system?

  • FDA change-control rules for composite tests — can you swap in a new RNA panel without a full re-clearance?

  • MolDx & CPT coding: Will multi-omic reports get one bundled code or modular coding (DNA + RNA + algorithm add-on)? This matters for pricing and adoption.

4. Clinical Utility & Trial Design

  • Designing trials that credit composite decision-making (RNA+DNA+IHC) rather than a single biomarker.

  • Using real-world data to justify coverage when randomized trials aren’t feasible.

  • Outcomes endpoints: replacing imaging scans with serial multi-omic MRD-style testing.

5. Consortium Deliverables

Expect BLOODPAC to preview:

  • Expanded multi-omic lexicon building on its ctDNA/MRD glossary.

  • Candidate reference materials for methylation and RNA assays.

  • Plans for shared datasets and benchmark challenges to accelerate algorithm validation.

6. Questions to Anticipate

  • “What is the clinical decision delta when adding RNA/methylation — beyond just higher AUC?”

  • “How do we validate a composite score when each component has different LoDs?”

  • “How do we manage regulatory submissions when AI models evolve?”

  • “How to price and code serial, multimodal tests for longitudinal care?”

Bottom Line

This seminar is poised to be less about abstract enthusiasm for multi-omics and more about how to make it work in practice — technically, operationally, and regulatorily. The lineup suggests robust case studies, frank discussions of assay standardization, and an emphasis on data fusion and deployment in real-world trials.

If you plan to attend, prepare to engage on clinical utility design, regulatory evidence frameworks, and practical multi-omic integration, as these will be front and center.

Would you like me to turn this into a one-page executive briefing or slide-ready deck (with key sections bolded and schematic diagrams for “multi-omic data fusion” and “clinical decision flow”)? That could make it easy to share with clients or colleagues ahead of the seminar.


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