(Selected Tables and Figures referenced, but not present in this blog
can be found in their corresponding Science Version blogs)
The application of the knowledge from immunoinformatics (computational immunology) has led to a better understanding of the importance of the immune system through effective approaches like in silico immunoinformatics (scientific experimentation and research conducted or produced by means of computer modeling or computer simulation). For example, AI and immunoinformatics are being used to better understand the three-dimensional structure of proteins to determine their genetically encoded amino acid sequence (Next-gen sequencing [NGS]). This structure influences the role and function of the protein involved in SARS-Cov-2 infection its most mRNA vaccine. An AI Google DeepMind system called AlphaFold uses amino acid sequencing and protein structure. This system has been applied to predict the structures of six proteins related to SARS-CoV-2.
In silico immunoinformatics depends on experimental science (“wet lab”) to produce raw data for analysis. It do not replace the traditional experimental research methods of actually testing hypotheses. The quality of immunoinformatics predictions depends on the quality of data and the sophistication of the algorithms being used (remember the old, "garbage in – garbage out" axiom). The future of immunological research will be enhanced by the ability to make discoveries in biologics (e.g., vaccines) more effectively and efficiently through combined AI and in silico immunoinformatics combined with traditional experimental research methods. Notwithstanding the credit certain narcissistic politicians like to take for the rapid development of COVID-19 vaccines, it was the combination of brilliant researchers, AI, and immunoinformatics that brought home the bacon in the desperate COVID-19 human crisis.
The world celebrated the newly discovered vaccines in early 2021 that began the mitigation and reversal of the COVID-19 pandemic. The suffering and ill effects of the novel coronavirus have been devastating to the world through its toll on lives and the crippling economic effects it has had on individuals and governments. Without a doubt the greatest appreciation must go researchers and scientific community who tirelessly worked to find the vaccines so desperately needed. Companies like Pfizer, Moderna, AstraZeneca, J&J and the governments of most industrialized countries prioritized vaccine development with little concerns for costs of such initiatives. And perhaps the greatest cheer should go to the contribution made by the immunology, genetic, and AI technologies that provided the research scientists the tools needed to accomplish their task in record time. Those achievements by the research and scientific community started many years ago with the early work of heroes in immunology (one more shout out to Dr. Fauci) and the genetic research mentioned throughout this book.
We must all be thankful for these accomplishments that have begun to reduce the human suffering and economic devastation brought upon the world from this COVID-19 pandemic. But we must also remain scrupulously vigilant. Today, the impact of COVID-19 and its rapidly evolving variants portend equal or more disastrous effects with the SARS-CoV-2 novel coronavirus being a far more contagious member of the coronaviruses (CoVs). Many countries have relied on an extrapolation of classic infection-control and public-health measures similar to those used for SARS-CoV-1 to contain the COVID-19 pandemic. They range from extreme quarantine measures, “shelter-in-place,” “social distancing,” to painstaking detailed contact tracing with hundreds of contact tracers. However, these measures may not be effective in the coming years for tackling the scale of COVID-19. Healthcare systems should plan to use AI technologies and digital technology “virtual clinics” using telehealth consultations with imaging data uploaded from peripheral sites and interpreted remotely. This would ensure that patients continue to receive standard clinical care while reducing physical crowding of patients into hospitals. Chatbots staffed by health professionals can also provide early diagnoses as well as patient education. And blockchain technologies can coordinate hospital, clinics, and pharmacy patient information.
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