1. Importance of CDx for Biologics and Small Molecule Drugs – therapeutic and market value

1. Economic qualification of CDx and precision medicine – Stratification, Safety, Efficacy, Cost-effectiveness, QALYs, etc.
2. Critical roles of alliance management to ensure value throughout value chain to the clinic
3. Considerations in using CDx to indicate and differentiate drugs (biologics, small molecules)
   1. Differentiating products in a rapidly growing sector
   2. Assays to determine markers for biologics, small molecule, combination therapies
   3. Assays for markers to differentiate Biologics vs biologics (e.g., Keytruda, Opdivo, Tecentriq)
   4. Liquid biopsies and exosomes as sources for novel biomarkers and diagnostics
   5. Panels of CDx (gene-, mRNA, protein-, metabolite-based, etc.)
   6. CDx role in identifying new indications for currently marketed drugs or drugs in trials
   7. Strategies for long-term vs short-term investments (CDx, complementary Dx, LDTs, and clinical assays)
4. Challenges of finding novel biomarkers to differentiate emerging products
5. Differentiating personalized, precision, companion, complementary as terms of the art

2. Technologies to identify markers

1. Profiling samples using Genomics, Proteomics, Metabolomics, Lipidomics to identify signature panels for CDx indications
2. NGS to profile and identify candidate signatures
3. Portfolio of assays and reagents – antibodies, gene profiles, cells
4. CTCs and related liquid biopsy assays (oncology and others)
5. Technologies for precision engagement of drugs with targets
6. Informatics to identify and vet biomarkers for selection in clinical diagnostics
7. Image IHC and ISH for BMx clinical sample analysis

3. Evolving CDx from animal models: From proof of concept (POC) to generating BMx candidates; drug dosing; and response tracking

1. How animal models expedite co-development of drug-CDx pairs
2. Testing and use of CDx in huMouse models and platforms for ImmOnc, Infectious Disease, etc
3. Choosing and testing with the best animal models to expedite drug-biomarker progress

4. Informatics for analyzing Big Data sets

1. Deep Learning for Translational and Precision Biologics
   1. Pattern recognition for data trends – response to treatment, potential for new indications in trials
   2. Data visualization tools
   3. Hypothesis generation
2. Classification, regression, and other methods to identify responders
3. Achieving statistical significance for rare/ultra-rare and infectious diseases
4. Text mining from caregivers’ notes (EHRs), patients’ diaries (e-notes)

5. Regulatory

1. Filing and prosecution
2. Guidance on CDx, LDTs

Attendees will hear speakers address topics covering the following areas:

• Tools and techniques to validate CDx-drug pairs
• Examples of business cases as models for future offerings
• Growth potential of complementary diagnostics
• Trade-offs between LDTs and CDx pathways
• Competitive advantages for drugs with a companion assays
• Strategies for successful partnerships enabling development through marketing
• Alliance management among pharma, diagnostic, and CRO partners
• Tactics for drafting and closing deals for CDx-drug pairs

We welcome researchers in biotechnology organizations ranging from start-up companies to leading-edge suppliers to non-profit institutions. Functions of attendees range from development to post-marketing surveillance with biomarkers (development) and diagnostics (market offerings).

Professionals in biopharma, biotech, academics, government, diagnostics, and CROs are all invited to register:

• VPs in Translational Medicine and related functions
• Executive/Senior Directors
• Laboratory and Technology Directors
• Project Managers (technical, logistical, and transitioning projects to partners)
• Technology leaders and researchers (assays, platforms, informatics)
• Researchers in assays, diagnostics (basic, development, validation, execution)
• Allied VP, Executive/Senior Directors, Directors, and Associates in licensing and regulatory