Improving Complex Trial Designs
Novel innovations in research have allowed for the study of more complex topics across various therapeutic disciplines. This is especially true across therapeutic indications with a vast number of individual differences, such as immunology, neurology, oncology, and rare diseases. Innovations in these disciplines have enabled the introduction of complex trial designs within pharmacology, biotech, and medical device research, with the ultimate goal of gaining a deeper understanding of how to treat these complex diseases.
What Makes a Trial Design “Complex”
Complex trial designs integrate novel, Bayesian, and/or adaptive statistical designs to determine operating procedures. Previously, the “gold standard” for clinical research was considered to be the traditional randomized control trial (RCT). However, adaptive designs allow for adaptations in trial design as the clinical trial progresses, such as allowing for multiple treatments, diseases, or disease outcomes to be studied in parallel based on emerging data or results. Because of this, complex trial designs have emerged as a solution for simultaneously improving the success of different clinical trials, while reducing negative outcomes to patients, including potential adverse events, time, and/or cost. Complex trial designs have also emerged as especially relevant in therapeutic areas requiring complex research questions, such as rare disease and oncology, as they allow for adapting rules and the integration of personalized, preliminary, and emerging external data in real-time, and allow for a personalized approach to drug and device development. Because of this flexibility, complex trial designs also allow for increased patient participation when compared to the strict inclusion and exclusion criteria typical of traditional RCTs.
Recent Innovations in Complex Trial Design
Basket Trials
Basket trials are a type of complex design that tests the effectiveness of a single drug on a specific genetic mutation across several disease types (in the case of rare disease indications) or different cancer types (in the case of oncology). Patients are selected for basket trials based on a shared molecular feature (e.g., mutation or biomarker) of their disease state, rather than the disease’s location, and all patients in the “basket” receive the same experimental drug designed to target that specific marker, regardless of their disease or cancer location.
Early use of basket trial designs has proven effective in cases of rare disease and oncology, because they instead focus on the treatment of the biology of the disease itself rather than just the location of where the disease has started. Basket trials can also bring treatments of rare diseases and cancers to patients faster, since they avoid the slowness of running separate trials, and can identify new indications for existing drugs.
Umbrella Trials
Umbrella trials study patients with the same disease, but treatment is personalized based on the specific mutation, biomarkers, or subtype of their disease or cancer. Each subgroup receives a different targeted drug (or combination of drugs) that matches their specific mutation or biomarker. Additionally, study arms may be added or removed as new treatment options become available, which further streamlines treatment development. Umbrella trials, therefore, allow for the testing of many treatment options and hypotheses within one trial, accelerating drug discovery and allowing for the study of rare genetic subtypes within one specific disease or cancer type.
Biomarker-Adaptive Designs
Similarly, biomarker-adaptive designs utilize patient biomarker data to adapt the trial in real-time based on pre-planned rules to adjust recruitment, randomization, or analysis. This complex trial design type helps better identify the best treatment for specific patient subsets and avoid ineffective treatment for others. Biomarker-adaptive designs may utilize biomarker-stratified randomization, treatment thresholds, interim analyses, or machine-learning-based classifiers to test different subgroups. Biomarker-adaptive designs are particularly effective because they help better identify the effect of treatment for the right patients and allow for the stoppage of ineffective treatments early on.
Factorial Designs
Factorial designs test multiple treatments and dosages simultaneously. Often, factorial designs may implement a wearable device to measure certain efficacy outcomes of different doses. Factorial designs allow for greater trial efficiency because patients can gain access to multiple treatments across a single trial. Factorial designs can be particularly beneficial because they examine not only individual, main effects of different treatment options, but also how they interact with each other.
The Strategic Role of Medical Writers in Complex Trial Design
As complex trial designs become the norm in therapeutic areas such as neurology, immunology, rare disease, and oncology, the need for experienced medical writers with a strong understanding of these research designs will also increase. Drafting complex trial design study protocols will require not only excellent writing skills but also strong expertise in clinical research design, biostatistical methods, and the latest therapeutic guidelines, as well as the ability to effectively implement review of these aspects across a cross-functional review team.
