Meet the Team
Like all successful organisations the Innovation Observatory is built on the collective effort of a multidisciplinary team.
The Innovation Observatory is funded by the National Institute for Health and Care Research (NIHR) and hosted by Newcastle University. Established in 2017, we bring together expertise in research, data science and health innovation to identify and assess emerging healthcare innovations, helping health and care organisations prepare for the future.
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Like all successful organisations the Innovation Observatory is built on the collective effort of a multidisciplinary team.
We help the health and care ecosystem anticipate and prepare for the future.
Our governance arrangements ensure that priorities, resources and delivery are aligned to the needs of the health and care system while maintaining appropriate assurance and public accountability.
The NIHR Innovation Observatory identifies emerging innovations across the global healthcare landscape and transforms them into trusted intelligence that helps organisations anticipate change, make informed decisions and prepare for the future.
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Identifying today's emerging innovations to prepare for tomorrow's healthcare challenges
Building a connected, scalable infrastructure for the next generation of healthcare horizon scanning
Our four horizon scanning programmes span from Priority, Reactive, Proactive, and Demand Signalling. Find out more about how they all work together.
We are committed to building capability across the health and care system by developing skills, supporting careers and creating opportunities to learn, collaborate and grow.
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We develop and share cutting edge methods in horizon scanning, building capacity in the system across the public, voluntary and industry sectors.
We invest in people and support them in realising their full potential. Through nurturing and encouraging career development, we grow future national and international leaders.
Connecting the wider community with opportunities to learn, collaborate and develop through fellowships, immersion events, placements and external programmes.
We provide a gateway to collaboration, intelligence, and growth opportunities in healthcare and life sciences.
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Connecting with stakeholders across health and care to share knowledge, build relationships and support the effective use of our work.
Embedding lived experience into our work to ensure our approaches and outputs reflect the needs of patients and the public.
Live Dashboards
April 2024
Live Dashboards
September 2023
Live Dashboards
December 2022
20 December 2021
This publication presents some analysis and insights into the data on combination therapies delving specifically into dual combination therapies in pivotal clinical trials.
The COVID-19 pandemic has driven an unprecedented level of global activity in drug discovery and clinical development for effective therapeutics targeting the coronavirus disease. There are currently 744 therapeutics being tested in 2879 clinical trials globally.
Almost 90% of these clinical trials are focused on monotherapies. Combination therapies are the mainstay of antiviral therapeutics to increase the potency of the individual compounds and to combat the rapid evolution of resistance, although combination therapies have inherently complex clinical and regulatory development challenges. Increased understanding of the SARS-CoV-2 lifecycle and COVID-19 pathology provides a scientific rationale for evaluating the effectiveness of different combinations.
In this paper, we provide an overview of the current clinical trial landscape for combination therapeutics targeting COVID-19 through weekly scanning of national and international clinical trial registries. Our analysis delves specifically into dual combination therapies in what can be defined as “pivotal clinical trials” (active, randomised, controlled and at least phase II), with a focus on new and repurposed therapeutic candidates that have shown positive signals and/or been granted authorisation for emergency use based on positive efficacy and safety data.
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