Biomarker Strategy in Phase 1: Exploratory vs. Predictive Markers

Optimizing Early Development with Exploratory and Predictive Biomarkers

Table of Contents

Introduction

Phase 1 clinical trials are no longer limited to safety and pharmacokinetics. With the evolution of precision medicine, biomarkers have become essential tools in early development to characterize mechanism of action, monitor biological response, and support rational dose selection. Two major types of biomarkers—exploratory and predictive—are frequently integrated into Phase 1 protocols to bridge preclinical data with clinical outcomes. This article explains how to build a biomarker strategy in Phase 1 trials, the key differences between biomarker types, and how they align with regulatory expectations.

What Is a Biomarker?

A biomarker is a measurable indicator of biological state, condition, or response. In Phase 1, biomarkers are used to:

Assess target engagement or pathway modulation
Monitor pharmacodynamic (PD) response
Identify early safety or efficacy signals
Inform dose-response relationships

Types of Biomarkers in Phase 1 Trials

1. Exploratory Biomarkers

Used to generate hypotheses and understand biological activity
Not yet validated or linked to clinical outcomes
Examples: Cytokines, gene expression signatures, imaging changes

2. Predictive Biomarkers

Used to predict response or resistance to a drug
Typically based on known drug mechanism or prior studies
Examples: EGFR mutations for TKIs, PD-L1 expression for immunotherapy

Why Biomarkers Matter in Phase 1

Mechanism validation: Confirm the drug affects its intended target in humans
Dose optimization: Support RP2D selection with PD evidence
Risk mitigation: Identify early toxicity signals or off-target effects
Patient stratification: Guide cohort expansion based on biomarker status

Designing a Biomarker Strategy for Phase 1

1. Define Biomarker Objectives

Are you measuring target engagement or functional response?
Are the markers mechanistically relevant to the drug?

2. Select the Right Biomarkers

Choose surrogate PD markers linked to pathway activation
Prioritize non-invasive biomarkers where possible (e.g., blood, urine)
Ensure analytical validity: specificity, reproducibility, sensitivity

3. Align Sampling with PK/PD Profiles

Synchronize biomarker sampling with Cmax and Tmax
Collect longitudinal data to assess time-course effects

4. Include Exploratory Biomarkers with Mechanistic Value

Transcriptomics, proteomics, phospho-signaling assays
Bioinformatics may identify patterns linked to response

Examples of Biomarkers in Phase 1 Studies

1. Oncology

Exploratory: Changes in circulating tumor DNA (ctDNA), immune cell infiltration
Predictive: ALK rearrangements, BRAF mutations

2. Inflammation and Autoimmune Disease

Exploratory: Cytokine profiling (IL-6, TNF-α)
Predictive: HLA alleles, CRP levels

3. Neurology

Exploratory: CSF biomarkers (tau, neurofilament light chain)
Predictive: APOE genotype in Alzheimer’s disease

4. Infectious Disease and Vaccines

Exploratory: T-cell activation markers, viral load kinetics
Predictive: Baseline immunity, antibody titers

Regulatory Expectations

FDA

Supports exploratory biomarkers under IND as long as they are not used for enrollment decisions
Predictive biomarkers must be clinically validated if used for patient selection

EMA

Expects biomarkers to be linked to mode of action or disease modulation
Encourages qualification through EMA biomarker qualification procedures

CDSCO (India)

Allows inclusion of biomarkers in Phase 1 for scientific insight
Mandates ethics approval and inclusion in ICF if additional samples collected

Biomarker Sample Logistics

Ensure validated assays are in place before trial begins
Standardize collection kits, transport, and processing protocols
Use central labs for high-complexity tests (e.g., flow cytometry, NGS)

Common Pitfalls and How to Avoid Them

Overpromising exploratory markers: Avoid regulatory reliance on unvalidated assays
Insufficient sample timing: Align with PK and PD kinetics
Low assay sensitivity: May obscure real biological signals

Best Practices for Biomarker Integration

Define biomarker endpoints in protocol (primary, secondary, exploratory)
Use validated assays or define a validation plan
Include biostatistical plans for interpreting exploratory biomarker data
Build biomarker strategy into translational roadmap and IND briefing documents