In this chapter, we review six case studies of adaptive clinical trials. This chapter is intended to complement the previous chapters. We have organised the case studies by their main adaptive design feature. Each case study describes the background of individual trial and summarises key design details and overall results. Our presentation and discussion do not necessarily represent the official view of the trial investigators. Our discussion is intended to improve the reader’s general literacy and comprehension of published results of adaptive clinical trials.

In this chapter, we review the history of clinical trials. We review the famous 1948 streptomycin trial for tuberculosis to highlight how the discipline of randomised clinical trials was born out of economic hardship. Other historical events of adaptive trial designs and master protocols are discussed in this chapter.

In this chapter, we review six case studies of basket and umbrella trials. This chapter is intended to complement the previous chapters on master protocols and basket and umbrella trials.

In this chpater, we review the standards and guidelines for adaptive trial designs and master protocols. Methodological rigour and transparent reporting are required in all clinical trials. Adaptive trial designs and master protocols are no exception. The standard reporting guidelines and risk-of-bias assessments for conventional trials can be applied to adaptive trial designs and master protocols. Adaptive trial designs have pre-planned adaptations and analysis plans that are specified in a formal way that outline how the data will be used to guide the design. Planning of adaptive clinical trials, basket trials, umbrella trials, and platform trials will require early engagement with the stakeholders and methodologists to think through potential hurdles and challenges of the statistical design and its implementation.

In this chapter, we discuss four adaptive randomised platform trials as case studies. We review two of the longest ongoing platform trials and another two important examples of ongoing platform trials conducted for COVID-19.

In this chapter, we review practical considerations for adaptive trial designs and master protocols. Planning adaptive trial designs and master protocols require resources and time. It is best to plan ahead with key stakeholders with statistical, content, and operational expertise to make the trial possible. Customised education and training plans will likely be required for the vendors, investigators, and other personnel involved in the trial. Critical thinking is needed from the personnel involved to create flexible technology systems and procedures required to execute these clinical trials. During the conduct, it is important to document what happened, maintain a proper firewall, and manage external communications effectively. For long-term platform trials, study adjustments may be unavoidable, but it is important that these adjustments are made before the patients are enrolled into the new study arm.

This chapter discusses the property and principles of adaptive trial designs. Adaptive trial designs refer to trial designs that offer pre-planned opportunities to modify the design of an ongoing trial based on accumulating trial data. Decisions for potential adaptations are made during the trial based on interim data, but flexibilities in adaptive trial designs are established and outlined in the study documents before any patient is recruited. For statistical planning, a simulation-guided approach is often used to evaluate the statistical properties of the design. It is generally required to demonstrate control of false positive rates for the regulatory, ethics, and funding bodies. Measures to mitigate and plan for operational bias and complexity in adaptive trial designs are needed.

In this chapter, we discuss the use of simulations for clinical trials. Simulation in statistics generally refers to repeated analyses of randomly generated datasets with known properties. Clinical trial simulation is required to explore, compare, and characterise operating characteristics and statistical properties of adaptive and other innovative trials with complex designs. Clinical trial simulation is an important tool that allows for comparison of different design choices during the planning stage to enhance the quality and feasibility of the trial. While simulations are most frequently used in adaptive and other complex trial designs, they can be applied to fixed trial designs.

In this chapter, we discuss the key concepts, terminologies, and principles of master protocols. The term ‘master protocol’ is often misunderstood and misused. This term refers to a single overarching protocol document that is developed with the intention of evaluating multiple interventional hypotheses. ‘Master protocol’ itself does not refer to a specific type of clinical trial. There are three types of clinical trials that are conducted using the master protocol framework: platform trials, basket trials, and umbrella trials. While master protocols can naturally extend to adaptive trial designs, the use of adaptive trial designs is not a defining feature of master protocols nor of platform, basket, and umbrella trials. Master protocols implement common screening, trial systems, and standardised operating procedures across multiple trial institutions under one centralised governance model. In addition to statistical efficiencies, operational efficiencies can be gained by adopting the master protocol framework.

In this chapter, we review the concept of platform trials in close detail. Platform trials refer to clinical trials that allow new interventions to be added to the platform over time even, if they are not pre-specified in the design stage. Platform trials can be applied to all phases of clinical trial research. While they are most often conducted as randomised clinical trials with adaptive trial designs (adaptive platform randomised trials), they can be conducted with non-randomised or fixed sample trial designs as well. As a general goal, platform trials aim to establish a shared trial infrastructure where multiple interventions can be evaluated. Independent clinical trial evaluation would result in multiple separate teams creating shorter term infrastructure and trials that would otherwise compete against each other. Platform trials represent an exciting turning point for clinical research. The key design considerations of platform trials are outlined in this chapter.