We are living in unprecedented times. In less than one year, SARS-CoV-2 spread across the globe and claimed the lives of millions of people. New SARS-CoV-2 variants became highly infectious, posing a huge threat to humankind. Scientists around the globe responded with unparalleled force. They accurately characterized SARS-CoV-2 variants and mechanisms of pathogenicity, developing effective vaccines at an unprecedented speed. Success came from extraordinary focus, patience, diligence, and out-of-the-box thinking where entire organizations, industries, governments, academic researchers, and clinicians aligned behind the same urgent cause. The COVID-19 pandemic has shifted the way we now live and work, and, importantly, conduct research as a society. One may think, can this experience be leveraged in developing effective treatments for autoimmune diseases?
New drugs and therapeutic protocols for autoimmune diseases usually require years, a decade on average, from the moment of their discovery to their clinical testing. In addition, the majority of them produce disappointing results. The main reason for failure is the complexity of human biology. Autoimmune diseases are heterogeneous, with the genetic makeup of the individual and the environment they are exposed to playing a significant role. Treatments fail due to translational limitations of the preclinical models, the type and disease stage of an individual at the time of treatment. Some of these failures are also due to poor practices. Poorly designed protocols, lack of sufficient preclinical testing in humanized models, questionable clinical trial endpoints, misguided criteria for patient recruitment, poor operational execution are some examples. With COVID-19 we saw a transformation in this field. COVID-19 vaccines were developed and clinically tested so quickly because of enormous funding that enabled automation in vaccine manufacturing and the development of artificial intelligence tools to process and analyze data. Additionally, it shifted the mindset of regulators who took faster action and allowed firms to run multiple trials in parallel.
This Research Topic welcomes Perspective, Opinion articles, and theoretical analyses discussing how the COVID-19 pandemic could be used as a roadmap for revolutionizing the treatment of autoimmune diseases. Whilst not exhaustive, papers could discuss the role of industry-academia-hospital-regulators-government communication and decision-making. What needs to be changed to accelerate the path of finding a cure for autoimmune diseases?
We also welcome submissions that have leveraged digital technology (e.g. artificial intelligence, machine learning) in the automation of manual processes, incorporation of genetics, genomics, and other biometrics into disease classification and prediction of response to therapies. While not exhaustive manuscripts could discuss:
- How can historical data and artificial intelligence mitigate possible failures in designing effective therapeutic protocols?
- How can genetic and genomic data be leveraged for determining disease endotypes and predicting responses to therapy?
- How can automation accelerate discoveries?
The collective experience and strategy for streamlined research in the face of the Covid-19 pandemic could shift the way we approach the research and discovery of treatments for other pathologies, including immunotherapy for autoimmune diseases in the future.
Topic Editor Dr. Iliopoulos is a co-found of Athos Therapeutics. The other Topic Editors declare no conflicts of interest in relation to the Research Topic focus.
We are living in unprecedented times. In less than one year, SARS-CoV-2 spread across the globe and claimed the lives of millions of people. New SARS-CoV-2 variants became highly infectious, posing a huge threat to humankind. Scientists around the globe responded with unparalleled force. They accurately characterized SARS-CoV-2 variants and mechanisms of pathogenicity, developing effective vaccines at an unprecedented speed. Success came from extraordinary focus, patience, diligence, and out-of-the-box thinking where entire organizations, industries, governments, academic researchers, and clinicians aligned behind the same urgent cause. The COVID-19 pandemic has shifted the way we now live and work, and, importantly, conduct research as a society. One may think, can this experience be leveraged in developing effective treatments for autoimmune diseases?
New drugs and therapeutic protocols for autoimmune diseases usually require years, a decade on average, from the moment of their discovery to their clinical testing. In addition, the majority of them produce disappointing results. The main reason for failure is the complexity of human biology. Autoimmune diseases are heterogeneous, with the genetic makeup of the individual and the environment they are exposed to playing a significant role. Treatments fail due to translational limitations of the preclinical models, the type and disease stage of an individual at the time of treatment. Some of these failures are also due to poor practices. Poorly designed protocols, lack of sufficient preclinical testing in humanized models, questionable clinical trial endpoints, misguided criteria for patient recruitment, poor operational execution are some examples. With COVID-19 we saw a transformation in this field. COVID-19 vaccines were developed and clinically tested so quickly because of enormous funding that enabled automation in vaccine manufacturing and the development of artificial intelligence tools to process and analyze data. Additionally, it shifted the mindset of regulators who took faster action and allowed firms to run multiple trials in parallel.
This Research Topic welcomes Perspective, Opinion articles, and theoretical analyses discussing how the COVID-19 pandemic could be used as a roadmap for revolutionizing the treatment of autoimmune diseases. Whilst not exhaustive, papers could discuss the role of industry-academia-hospital-regulators-government communication and decision-making. What needs to be changed to accelerate the path of finding a cure for autoimmune diseases?
We also welcome submissions that have leveraged digital technology (e.g. artificial intelligence, machine learning) in the automation of manual processes, incorporation of genetics, genomics, and other biometrics into disease classification and prediction of response to therapies. While not exhaustive manuscripts could discuss:
- How can historical data and artificial intelligence mitigate possible failures in designing effective therapeutic protocols?
- How can genetic and genomic data be leveraged for determining disease endotypes and predicting responses to therapy?
- How can automation accelerate discoveries?
The collective experience and strategy for streamlined research in the face of the Covid-19 pandemic could shift the way we approach the research and discovery of treatments for other pathologies, including immunotherapy for autoimmune diseases in the future.
Topic Editor Dr. Iliopoulos is a co-found of Athos Therapeutics. The other Topic Editors declare no conflicts of interest in relation to the Research Topic focus.