Adaptive & Flexible Trials

Listening, learning, adapting.

Flexibility is one of the most powerful tools in your trial design arsenal. That’s why Adaptive Trial Designs give you the opportunity to reduce risk of failure by factoring in analyses at key points so study design parameters like sample size, dosage, or patient selection can be adjusted accordingly. 

In fact, a 2018 report we commissioned called The Innovation Imperative: The Future of Drug Development by The Economist Intelligence Unit (EIU) found that adaptive trial designs boost a new therapy’s likelihood of launch by 13% on average. That percentage climbs even higher in certain therapeutic areas – up to 32% for oncology. However, although this approach is encouraging, it’s still not widely used.

By implementing Adaptive Trial Designs you have the opportunity to carefully evaluate clinical data in real-time, so you can make informed decisions to change the direction of the study for a better chance of success. A well-designed and executed Adaptive Trial Design can:

  • increase the probability of success for your new therapy
  • maximize the information from the trial
  • shorten development timelines
  • reduce overall development costs and
  • reduce the risk for study volunteers and sponsors
  • maximize the probability of success with regulators and payers

 

Types of Adaptive Trial Designs
Types of Adaptations Description
Adaptive dose finding Used to identify the minimum effective dose (MED) and/or the maximum tolerable dose (MTD). Continuous reassessment method (CRM) or a Bayesian Logistic Regression Model (BLRM)
Population enrichment (e.g., based on biomarker or pharmacogenomic data) Unblinded interim analysis for subsets of interest for identifying sub-populations with significantly higher response to treatment based on scientific rationales. Subjects may undergo biomarker or genomic testing to determine eligibility for participation in the clinical trail or to enable interim decisions to continue with selected sub-populations or the full population
Sample size re-estimation (SSR) Sample size adjustments or re-estimation based on unblinded interim data while not inflating the false-positive probability at the final analysis
Adaptive randomization Modification of randomization scheduled based on accumulating study data like baseline covariates or responses
Seamless Phase I/II studies - dose escalation and dose expansion trials Combines dose escalation with an expansion phase to generate first activity data
Seamless Phase II/III Combines a Phase II and Phase III into one trial, incorporates a decision to adapt the study at an interim analysis and uses data before and after the adaptation in the final analysis
Master protocols Includes umbrella, basket and platform designs. Master protocols can be very beneficial in the early development to screen different compounds in the portfolio and select the best for each of the indications or test one compound in several indications to select those indications where a compound is particularly effective. Umbrella designs investigate multiple treatments for a single disease whereas basket trials evaluate a single drug in multiple diseases or disease subtypes (e.g., different tumor types that share the genomic characteristics). Platform trials evaluate multiple treatments in multiple diseases and permit treatment regimens to be added or removed based on pre-specified decision algorithms
Inclusion of real-world data (RWD) Real-world data as part of development, forming synthetic control arms

More services we provide:

  • Statistical expertise to develop Adaptive Trial Designs to optimize study plans and clinical development plans 
  • Biostatistics expertise in planning and execution of adaptive trials, Bayesian adaptive dose finding, sample size re-estimation, seamless designs to combine phases of development, performing simulations of design and decision scenarios
  • Project leadership with experience in managing Adaptive Trial Designs:
    • We develop the entire plan, bringing in all the disciplines: scientists, data managers, statisticians, medical experts, regulatory experts, logistics, and technology experts. They are all there to provide their input into the design and execution of the trial
    • Clinical monitoring resources who understand the effects of rapid design shift impacts on on-site workload, site motivation and retention, etc. 
    • Data management staff with experience in adapting database structures to changing study designs
    • We partner with the right technology developers to work on flexible data platform solutions to gather, synthesize and analyze the data from different sources 
    • Regulatory experts that have relationships with different regulatory agencies and can speak to the regulatory agencies expectation to maximize acceptability of the particular development plan 

Reduce the risk of failure with adaptive trial designs

Learn how to evaluate interim data at pre-defined points and then adapt your study design parameters to optimize outcomes.

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