ONCOLOGY COMPANION DIAGNOSTICS XCHANGE
EAST COAST
Boston
April 6, 2023
Welcome to hubXchange’s East Coast Oncology Companion Diagnostics Xchange 2023, bringing together executives from pharma and biotech to address and find solutions to the key issues faced in developing oncology companion diagnostics.
Discussion topics will cover Clinical Biomarkers, Clinical Development, Liquid Biopsies and Next Generation CDx.
Take advantage of this unique highly interactive meeting format designed for maximum engagement, collaboration and networking with your peers.
Venue Details: Hilton Boston Woburn Hotel, 2 Forbes Road, Woburn MA 01801
SNAPSHOTS OF DISCUSSION TOPICS
- Precision medicine in oncology drug development
- Biomarkers for ADC drugs
- Implementation challenges in getting from bench to bedside
- Designing impactful CDx strategies for early clinical development of new IO and cell therapies
- Is there a defined CDx strategy: Centralized vs decentralized model
- Exploring Laboratory Developed Test (LDT) vs distributed kit approach
- Using MRD to develop patient stratification approaches through tumor-informed or tumor-naive comprehensive insights
- Exploring liquid biopsies for advanced clinical trials
- Consideration of liquid biopsy implementation in next generation CDx in solid tumors
Full Xchange Agenda
Click on each track for detailed agenda
Clinical Biomarkers
Opening Address & Keynote Presentation
Harnessing AI to develop better diagnostic algorithms
Artificial Intelligence (AI), and specifically machine learning (ML, a subset of AI), increasingly is being applied across the healthcare landscape. ML has become an essential tool in biomarker discovery, and promises to play a major role in diagnostic development. The adoption of ML in diagnostics and clinical decisions is not without risks, namely the potential to exacerbate existing biases that characterize patient datasets. On the other hand, ML also can be deployed to identify and mitigate these very same biases. Industry advocacy organizations, public-private dialogue, and informed policy-making are required to ensure the responsible adoption of AI/ML in healthcare.
Chief Executive Officer, Co-founder, Genialis
Rafael is CEO/co-founder of Genialis, a computational precision medicine company unraveling complex biology to find new ways to address disease. Rafael sits on the Board of the Alliance for AI in Healthcare. He earned his doctorate at Yale, and conducted postdoctoral research at LBNL and Baylor College of Medicine.
Precision medicine in oncology drug development
- Decision Enabling Biomarkers
- Patient Enrichment Strategies
- Proof of Mechanism
- Tools to deliver Decision Enabling Biomarkers (e.g. Reverse Translation; Digital Pathology, Radiomics and AI/ML; Real World Omics Data)
Vice President, Immuno Oncology Precision Medicine, Bayer
Amanda Wang is the Vice President and Group Head of Translational Science Leaders at Bayer. Her team are responsible and accountable for the Integrated Translational Sciences strategy, orchestrating Precision Medicine strategy, Clinical Pharmacology strategy and Computational Biology, delivered to all Oncology projects at Bayer. Before the current role, she led the Immuno Oncology (IO)Precision Medicine group, overseeing Biomarker and CDx strategy across various stages of IO development. Before joining Bayer in 2019, Amanda worked at Novartis for over nine years, where she focused on biomarker development in autoimmune, Oncology and additional disease areas. Amanda has in-depth experience of translational science and clinical development in Oncology. Amanda received an PhD degree in Biochemistry and Molecular Biology from the University of Virginia. She also received a Master degree in Biostatistics from Boston University.
Developing CDx from complex signatures: promise, practice and pitfalls
- Benefits and risks of developing CDx based on more complex analytes and signatures
- Challenges of translating signatures from research to the clinic
- Getting the most from RNA-seq in a clinical application
- The future of multi-omics and multi-modal data in diagnostics
Chief Executive Officer, Co-founder, Genialis
Rafael is CEO/co-founder of Genialis, a computational precision medicine company unraveling complex biology to find new ways to address disease. Rafael sits on the Board of the Alliance for AI in Healthcare. He earned his doctorate at Yale, and conducted postdoctoral research at LBNL and Baylor College of Medicine.
Spotlight Presentation
Immunotherapy with or without chemotherapy for advanced stage lung cancer? miRisk provides the answer.
Patients with advanced-stage NSCLC and high PD-L1 expression are eligible for treatment with immunotherapy, however there is debate as to who requires additional chemotherapy. Using an immunotherapy treated, advanced-stage NSCLC cohort, we have defined a blood-based biomarker (miRisk) specifically predictive of response to immunotherapy. miRisk is a myeloid-predominant, 5-microRNA signature, with predicted interactions to immunotherapy pathways including PD-L1 signaling.
miRisk may serve as a complementary diagnostic to objectively guide treatment in advanced-stage NSCLC, or more generally as a signature of non-response to PD- (L)1 monotherapy for multiple uses including the enrichment of patients for novel ICI combination trials.”
Vice President, Medical Sciences, Hummingbird Diagnostics
Timothy Rajakumar leads the immunotherapy biomarker development at HBDx. Prior to this he completed his Academic Foundation training at Oxford University Hospitals, making contributions to spatial transcriptomic analyses of prostate cancer. He gained expertise in small RNA biology during his Ph.D. studies in synthetic biology at the University of Oxford.
15:00 – 16:00
Biomarkers for ADC drugs
- ADC targets in solid tumor vs liquid tumor
- Target expression level vs efficacy
- Target mutation status
- ADC resistance mechanism
- ADC combination therapy
Senior Director, Translational Medicine, Cogent Biosciences
Dr. Chu has more than 20 years of research and development experiences in the pharmaceutical
industry. He joined Sanofi in 2000, headed research teams in proteomics, anybody drug discovery, biomarker and clinical bioanalysis. He proposed several novel drug targets and led successful antibody discovery programs, including IL33 currently in clinical phase 3. His team was instrumental in the FDA approval of Hydrashift 2/4 isatuximab CDx. Before joining Cogent, he headed the clinical biomarker team at Luzsana Biotech (Hengrui USA), supported anti-Her2, -Her3, -Trop2, and -Claudin 18.2 antibody drug conjugate (ADC) clinical development programs.
Implementation challenges in getting from bench to bedside
- Can a clinical biomarker hypothesis be generated during early during drug discovery? What are the challenges associated with the use of pre-clinical models to test biomarkers of response and/or efficacy in human clinical trials?
- How can analytical validation of testing methodology be achieved to generate uniform and consistent data across subjects? Turnover times from sample collection to assay analysis leading to outputs? How to regulate pre-analytics of sample collection and sample handling prior to biomarker analysis?
- Can Clinical Trials be designed to generate proof of concept data for an exploratory biomarker? Is the clinical validation of biomarker prone to fluctuations due to patient heterogeneity, timepoints and drug pharmacology? Can real world evidence data help?
- Do we need extensive clinical data to establish full clinical utility? What are the challenges associated with transition into CDx? Regulatory hurdles?”
Director of Biology, Pre-Clinical and Translational R&D, Partner Therapeutics
Clinical Development
Opening Address & Keynote Presentation
Harnessing AI to develop better diagnostic algorithms
Artificial Intelligence (AI), and specifically machine learning (ML, a subset of AI), increasingly is being applied across the healthcare landscape. ML has become an essential tool in biomarker discovery, and promises to play a major role in diagnostic development. The adoption of ML in diagnostics and clinical decisions is not without risks, namely the potential to exacerbate existing biases that characterize patient datasets. On the other hand, ML also can be deployed to identify and mitigate these very same biases. Industry advocacy organizations, public-private dialogue, and informed policy-making are required to ensure the responsible adoption of AI/ML in healthcare.
Chief Executive Officer, Co-founder, Genialis
Rafael is CEO/co-founder of Genialis, a computational precision medicine company unraveling complex biology to find new ways to address disease. Rafael sits on the Board of the Alliance for AI in Healthcare. He earned his doctorate at Yale, and conducted postdoctoral research at LBNL and Baylor College of Medicine.
Designing impactful CDx strategies for early clinical development of new IO and cell therapies
- Other biomarkers beyond target expression
- How to best design preclinical assays and clinical studies to help define CDx assay cutoff
- Focus on patient selection strategy: higher response rate and longer response duration
- Challenges on getting fresh biopsy for CDx development and validation
- Considerations on validation and implementation using new methods, e.g flow cytometry or ELISA
Oncology Clinical Biomarker Lead, Takeda
Huilan Yao is an oncology clinical biomarker lead in Precision & Translational Medicine department at Takeda. Before that, she was an associate director at Constellation Pharmaceuticals leading a translational research team to delivery IND-enabling studies. Prior to Constellation, she holds multiple positions at H3 Biomedicine, working as a Clinical Biomarker Leader for multiple phase 1-2 clinical trials. In her early career stage, she developed several new clinical diagnostic assays at Molecular Testing Labs under a CAP/CLIA regulation. Huilan received her BS and MS degrees at Tsinghua University, Beijing, China and her PhD in Cell and Developmental Biology at Oregon Health & Science University.
Spotlight Presentation
Immunotherapy with or without chemotherapy for advanced stage lung cancer? miRisk provides the answer.
Patients with advanced-stage NSCLC and high PD-L1 expression are eligible for treatment with immunotherapy, however there is debate as to who requires additional chemotherapy. Using an immunotherapy treated, advanced-stage NSCLC cohort, we have defined a blood-based biomarker (miRisk) specifically predictive of response to immunotherapy. miRisk is a myeloid-predominant, 5-microRNA signature, with predicted interactions to immunotherapy pathways including PD-L1 signaling.
miRisk may serve as a complementary diagnostic to objectively guide treatment in advanced-stage NSCLC, or more generally as a signature of non-response to PD- (L)1 monotherapy for multiple uses including the enrichment of patients for novel ICI combination trials.”
Vice President, Medical Sciences, Hummingbird Diagnostics
Timothy Rajakumar leads the immunotherapy biomarker development at HBDx. Prior to this he completed his Academic Foundation training at Oxford University Hospitals, making contributions to spatial transcriptomic analyses of prostate cancer. He gained expertise in small RNA biology during his Ph.D. studies in synthetic biology at the University of Oxford.
Is there a defined CDx strategy: Centralized vs decentralized model
- Does speed matter?
- What are the key points to consider?
- Which patient segments to serve – Global vs local?
- Is tissue still the only issue or what else is an issue?
Chowdary Dondapati, Executive Director, Global Oncology Marketing, Precision Medicine, Merck
Chowdary Dondapati is a trained cancer biologist with an extensive experience in precision oncology, from setting a global strategy to implementing local tactics. He has held several leadership roles in advancing precision medicine – running a CLIA reference laboratory, leading oncology biomarker development, market development, commercial launch of FDA cleared diagnostic systems & kits, innovative patient identification strategies for therapy. He did his doctoral thesis at Hunter College in city of New York, NY and MBA at Rutgers Business school in city of Newark, NJ.
16:10 – 17:10
Exploring Laboratory Developed Test (LDT) vs distributed kit approach
- What key factors need to be considered when choosing an LDT vs distributed kit approach for clinical trials?
- Is one approach more advantageous than the other?
- How does each approach affect study design? What are some helpful insights for an effective study design?
- What are the key considerations for diagnostic partner selection specific to each approach?
Associate Director, Precision Medicine CDx, Regeneron
Melis McHenry, PhD, is an Associate Director of Precision Medicine Companion Diagnostics at Regeneron Pharmaceuticals. Previously, she held positions at Roche Tissue Diagnostics and Beckman Coulter Flow Cytometry as subject matter expert for several assay platforms and oversaw their clinical implementation. She began her career at EMD Serono leading numerous discovery and pre-clinical studies. She received her PhD from University of Illinois at Chicago interrogating the role of oncogenic pathways in cell migration and proliferation. In her current role, she leads CDx strategy, assay development, validation and testing efforts to support both oncology and non-oncology clinical trials.
Liquid Biopsies
Opening Address & Keynote Presentation
Harnessing AI to develop better diagnostic algorithms
Artificial Intelligence (AI), and specifically machine learning (ML, a subset of AI), increasingly is being applied across the healthcare landscape. ML has become an essential tool in biomarker discovery, and promises to play a major role in diagnostic development. The adoption of ML in diagnostics and clinical decisions is not without risks, namely the potential to exacerbate existing biases that characterize patient datasets. On the other hand, ML also can be deployed to identify and mitigate these very same biases. Industry advocacy organizations, public-private dialogue, and informed policy-making are required to ensure the responsible adoption of AI/ML in healthcare.
Chief Executive Officer, Co-founder, Genialis
Rafael is CEO/co-founder of Genialis, a computational precision medicine company unraveling complex biology to find new ways to address disease. Rafael sits on the Board of the Alliance for AI in Healthcare. He earned his doctorate at Yale, and conducted postdoctoral research at LBNL and Baylor College of Medicine.
- How does tumor-informed MRD assays differ from tumor-naive diagnostic approaches? Is one more advantages
than the other? - What are some of the key challenges or considerations for implementing MRD patient stratification approaches
in clinical development? - How can we use ctDNA as an early endpoint for monitoring therapy?
- Are there any barriers to using ctDNA as a
potential surrogate endpoint? - How is MRD defined in hematological cancers and how is it different from solid tumor settings?
- Can MRD be used as a stratification method for both early and late stage cancers? How about cancer types?
LBx Strategy Lead, Companion Diagnostics, Takeda
Minakshi Guha is a PhD scientist with 18+ years of experience in cancer genomics, next generation sequencing, assay development, and clinical diagnostics. Minakshi earned her PhD at UMass Medical School studying cancer cell survival mediated by tumor suppressors. She went on to complete a postdoctoral fellowship at Dana Farber Cancer Institute developing novel methods for detecting low abundance mutations in cancer. Recognized for the ability to develop and implement NGS assays in clinical diagnostics, she now works at Takeda within the Precision & Translational Medicine function. Prior to Takeda, she led projects in clinical biomarkers and companion diagnostics in solid tumors, rare diseases, neuroscience, and cardiovascular indications at Novartis.
She is an advocate for personalized medicine, minimal invasive diagnostic solutions, and liquid biopsy-based biomarker assays.
- Earlier detection of disease recurrence
- Utility in more disease indications, and at earlier stages of disease
- Clinical trial needs for patient enrichment
- Screening/enrollment
- Surrogate endpoint analysis
- Necessity for higher resolution variant tracking
Director, Strategic Business Development, Personalis
Julie Meyer is Director of Strategic Business Development for Personalis. She leads strategy and engagement across stakeholders of translational, clinical, diagnostic, regulatory, commercial, and medical affairs departments within global Pharma. Experienced in both tumor-agnostic and tumor-informed liquid biopsy approaches, Julie champions ultra-sensitive detection of molecular residual disease and tracking of clinically relevant variants to inform patient oncology treatment decisions in real-time, months to years earlier than current approaches.
PhD, Field Applications Scientist, Personalis
Dr. Yates joined Personalis as a Field Applications Scientist in 2020 with 12 years of research
experience in the areas of cancer biology, translational research, biomarker discovery, and
disease modeling. As a member of the Field Applications Scientist team, Travis has the
responsibility of providing both pre- and post-sale technical support for the Personalis NeXT
Platform Cancer Portfolio.
Spotlight Presentation
Immunotherapy with or without chemotherapy for advanced stage lung cancer? miRisk provides the answer.
Patients with advanced-stage NSCLC and high PD-L1 expression are eligible for treatment with immunotherapy, however there is debate as to who requires additional chemotherapy. Using an immunotherapy treated, advanced-stage NSCLC cohort, we have defined a blood-based biomarker (miRisk) specifically predictive of response to immunotherapy. miRisk is a myeloid-predominant, 5-microRNA signature, with predicted interactions to immunotherapy pathways including PD-L1 signaling.
miRisk may serve as a complementary diagnostic to objectively guide treatment in advanced-stage NSCLC, or more generally as a signature of non-response to PD- (L)1 monotherapy for multiple uses including the enrichment of patients for novel ICI combination trials.”
Vice President, Medical Sciences, Hummingbird Diagnostics
Timothy Rajakumar leads the immunotherapy biomarker development at HBDx. Prior to this he completed his Academic Foundation training at Oxford University Hospitals, making contributions to spatial transcriptomic analyses of prostate cancer. He gained expertise in small RNA biology during his Ph.D. studies in synthetic biology at the University of Oxford.
Exploring liquid biopsies for advanced clinical trials
- Using liquid biopsies at different points in a clinical trial (selection, early response monitoring, endpoint evaluation), how do you optimize different liquid biopsy sample types for different uses?
- Extracellular vesicles are a unique liquid biopsy sample type. What are the pros and cons of extracellular vesicles in clinical trials?
- FDA requirements for liquid biopsies are centered around reproducibility and sensitivity. Are there certain liquid biopsy types that are more amenable to the requirements? How do you think about centralized versus decentralized sample analysis in relation to liquid biopsies?
- Different tumor types shed material at different rates. Which indications are best posed for the use of liquid biopsies?
Associate Director, Translational Clinical Development, Kronos Bio
Melinda is an Associate Director at Kronos Bio, managing late stage preclinical and clinical programs targeting transcriptional regulatory networks in oncology. Prior to joining Kronos, her PhD training was completed at the University of Michigan studying the cytoplasmic and epigenetic regulation of autophagy. She then trained as a post-doctoral scientist at the University of Illinois elucidating how chaperone proteins promote a dynamic nuclear environment. In 2015 she joined Roche’s Tissue Diagnostic Division, where she worked on an early research and development program addressing how to better capture tumor heterogeneity within a diagnostic sample. From there she joined Cyteir Therapeutics where she led the discovery team in moving a program targeting DNA repair from hit to lead efforts through to IND enabling studies and Phase I clinical trials.
Next Generation CDx
Opening Address & Keynote Presentation
Harnessing AI to develop better diagnostic algorithms
Artificial Intelligence (AI), and specifically machine learning (ML, a subset of AI), increasingly is being applied across the healthcare landscape. ML has become an essential tool in biomarker discovery, and promises to play a major role in diagnostic development. The adoption of ML in diagnostics and clinical decisions is not without risks, namely the potential to exacerbate existing biases that characterize patient datasets. On the other hand, ML also can be deployed to identify and mitigate these very same biases. Industry advocacy organizations, public-private dialogue, and informed policy-making are required to ensure the responsible adoption of AI/ML in healthcare.
Chief Executive Officer, Co-founder, Genialis
Rafael is CEO/co-founder of Genialis, a computational precision medicine company unraveling complex biology to find new ways to address disease. Rafael sits on the Board of the Alliance for AI in Healthcare. He earned his doctorate at Yale, and conducted postdoctoral research at LBNL and Baylor College of Medicine.
Spotlight Presentation
Immunotherapy with or without chemotherapy for advanced stage lung cancer? miRisk provides the answer.
Patients with advanced-stage NSCLC and high PD-L1 expression are eligible for treatment with immunotherapy, however there is debate as to who requires additional chemotherapy. Using an immunotherapy treated, advanced-stage NSCLC cohort, we have defined a blood-based biomarker (miRisk) specifically predictive of response to immunotherapy. miRisk is a myeloid-predominant, 5-microRNA signature, with predicted interactions to immunotherapy pathways including PD-L1 signaling.
miRisk may serve as a complementary diagnostic to objectively guide treatment in advanced-stage NSCLC, or more generally as a signature of non-response to PD- (L)1 monotherapy for multiple uses including the enrichment of patients for novel ICI combination trials.”
Vice President, Medical Sciences, Hummingbird Diagnostics
Timothy Rajakumar leads the immunotherapy biomarker development at HBDx. Prior to this he completed his Academic Foundation training at Oxford University Hospitals, making contributions to spatial transcriptomic analyses of prostate cancer. He gained expertise in small RNA biology during his Ph.D. studies in synthetic biology at the University of Oxford.
Consideration of liquid biopsy implementation in next generation CDx in solid tumors
- What are the challenges associated with clinical validation of ctDNA as the surrogate early endpoint for early- stage disease?
- What are the challenges associated with clinical validation of ctDNA-based MRD for patient enrichment?
- What are the challenges to implement ctDNA as the surrogate endpoint for late stage of diseases?
- What are the challenges associated with analytical validation of ctDNA-based MRD?
- For a given indication, what is the threshold of ctDNA best correlates with clinical outcome? What is the appropriate time of the window for assessment? How to validate it?
- Future innovative approaches
Senior Director, Head of CDx, Clinical Biomarker Expert Team Lead, EMD Serono/ Merck KGaA
Janet Wang has more than 15 years of Pharma/Biotech experience with deep expertise in translational science and precision medicine in early and late stages of clinical development and life cycle management in Oncology and Immuno-Oncology therapeutic areas. Currently, Janet is the Senior Director at Merck KGaA/EMD Serono where she is not only the Head of CDx overseeing CDx strategy and development for Immuno-Oncology and ADC programs; but also the Clinical Biomarker Expert Team Lead responsible for Oncology and Immuno-Oncology programs. Janet previously led R&D teams focusing on translational science and precision medicine at Pharma/biotech companies, including Novartis and On-Q-ity. Before her industry career, Janet was an instructor focusing on cancer research at Dana-Farber Cancer Institute, Harvard Medical School. She has co-authored many peer-reviewed publications/abstracts and patents.