Juliane Mills, MS, MPH, Executive Director, Therapeutic Strategy
I recently had the privilege of presenting at OCT West 2026 on a topic that’s reshaping how we approach oncology clinical trials: the necessary shift for operations and outsourcing teams in the era of precision oncology.
A Steady Increase in Oncology Trials
The oncology clinical trial landscape is continuing to grow. Today, approximately 13% of trials on Clinicaltrials.gov focus on cancer, and between 2005 and 2015, more than half of these trials targeted rare malignancies. This trend is driven by continued growth in oncology research and a shift in drug development toward novel modalities. Trials involving antibody-drug conjugates and multispecific antibodies now account for a growing share of oncology trial starts.
The Need for Innovative Operational Solutions
This evolution in rare oncology research brings a constellation of challenges that traditional trial operational models weren’t built to handle.
Ultra-Low Prevalence Populations
When working with rare, biomarker-defined cohorts, ultra-low prevalence combined with fragmented biomarker assessment can lead to excessive screen-fail rates. To ensure potentially eligible patients are not missed, it is best practice to work with sites that use reflexive testing as part of their standard of care and that have the testing infrastructure in place to test archival tissues.
Complex Study Designs
Molecularly-defined cohorts and basket/umbrella/platform designs are operationally a far heavier lift than traditional trials. They demand intense feasibility work, shared screening infrastructure, centralized governance, and possibly multi-arm CMC coordination. Add to this endpoint heterogeneity and prolonged durations, and this creates significant study management complexity.
Site Network Challenges & Regulatory Variability
Many sites and few eligible patients lead to predictable under-enrolling centers and long activation tails. Regulatory variability across regions for master protocols and biomarkers only adds to the delays in site activation.
The Control Arm Dilemma
Randomized concurrent controls can be impractical or ethically challenging in certain disease settings. Increasingly, sponsors are turning to externally controlled trials (ECTs) and synthetic arms, but these efforts face significant hurdles around data quality, confounding, and harmonization. ECTs require robust, fit-for-purpose data that captures the target endpoints and includes adequate follow-up.
These efforts require meticulous pre-specification and often multi-registry harmonization.
Novel Endpoints
With overall survival/progression-free survival events scarce or slow to accrue in tiny cohorts, sponsors are leaning on novel and surrogate endpoints, including ctDNA and MRD kinetics.
A Strategic Framework for Success
So how do we navigate this complexity? Below is our recommended strategic framework.
1. Up-Front Design
- Choose basket, umbrella, or platform designs with pre-specified subgroup rules
- Pre-specify external control arm sources, matching variables, and sensitivity analyses
- Discuss design and ECT approaches with regulators early; this is non-negotiable
2. Diagnostics & Patient Identification
- Stand up a centralized pre-screening hub
- Formalize a reflex testing cascade (IHC → NGS → liquid biopsy)
- Develop a tiered site network incorporating centers of excellence, community sites, and decentralized clinical trial elements
3. Regulatory Path
- Treat each cohort as a regulatory learning unit
- Assess Project Orbis suitability for global efficiency
- Map EMA expectations for biomarkers and master protocols
4. Data & Vendor Strategy
- Set up a tokenized real-world data pipeline
- Build the infrastructure early to support both trial execution and the development of the external control arm
The Bottom Line
The shift in therapy development toward precision oncology is already here. Operations and outsourcing teams that embrace the complexity of these studies, invest in the right infrastructure, and adopt strategic frameworks for master protocols, biomarker-driven recruitment, and innovative trial designs will be the ones positioned to succeed.
This requires moving beyond traditional operational playbooks and building capabilities purpose-built for the complexity of modern oncology trials. The question isn’t whether to adapt, but how quickly we can make this transition.
