Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity

Front Matter
Copyright
Contributors
Preface
History, current status, and future directions of artificial intelligence
	Introduction: History of artificial intelligence
		Artificial intelligence success in games and competitions
		Ever expanding use of artificial intelligence
		Commercial aspects
		Setting and managing proper expectations
		Ethic and privacy consideration
	Enabling technologies
		Computing power
		Sensors
		Electronic health record systems
		Blockchain technologies
		Internet of things
		Frameworks and libraries
	Introduction of artificial intelligence in life science and healthcare
		Three-tiered application approach of artificial intelligence in healthcare
			Business intelligence in healthcare
			AI-based clinical decision support
			Artificial intelligence and insight into the data/focus on business decisions
		Medical areas
			Electronic health record
			TeleHealth and remote patient monitoring
			Radiology
			Pathology
			Infectious diseases
			Autoimmunity
	Future artificial intelligence development
	Competing interests
	References
Precision medicine as an approach to autoimmune diseases
	Introduction
	From individualized to precision medicine
	Trends that promote precision medicine
	Challenges for therapeutics, medical interventions and clinical trials
		Heterogeneity of autoimmune diseases
		Improved standard of care increases threshold for outcome measures
	Prevention of disease morbidity and mortality
		Modifiable and non-modifiable risk factors
		Prediction tools
		Education of populations at risk for autoimmune diseases
		Prevention of autoimmunity: Simple, safe and potentially beneficial approaches
		Clinical trials for the prevention of autoimmune diseases
	Mobile devices and web-based software applications and the future of medicine
		Symptom checker
		Wearable technologies
		Future of rheumatology?
	Importance of biomarkers
	Health economics
	Conclusion
	Competing interests
	References
Biomarker and data science as integral part of precision medicine
	Introduction
	Definitions of biomarkers
		Diagnostic biomarkers
		Disease monitoring biomarkers
		Pharmacodynamic/response biomarkers
		Risk markers/factors
		Predictive biomarkers
		Prognostic biomarkers
		Digital biomarkers
	Pre-analytical aspects of biomarkers
	Benefits and pitfalls of biomarkers
	Biomarker discovery
		Gene-expression profiling
		Mass-spectrometry-based proteomic profiling
		Peptidomics
		Biomarker family approach
		Secreted protein approach
		Protein arrays
		Epitope mapping as discovery strategy
		Different phases of biomarker discovery
		Platform switch
	Biomarker verification and validation
	Statistical approaches and big data
		Visualization and relevance assessment
			Multi-variate analysis/large datasets
		The statistical trap and correction methods
		Methods to measure and describe clinical performance characteristics
		Machine learning models
	From bench to bedside
	Conclusions
	References
Companion and complementary diagnostics: A key to precision medicine
	Introduction
	Companion and complementary diagnostics
	Drug-diagnostic codevelopment
	Regulatory requirements
		US FDA
		The European Union and other countries
	Concluding remark
	References
Checkpoint inhibitors: Interface of cancer and autoimmunity: Opportunity for second level precision medicine
	Introduction
	History of immune checkpoint inhibitors
	Mechanisms of immune checkpoint inhibitors
	PD-1 or PD-L1 inhibitors
	CTLA-4 inhibitors
	The interface between cancer and autoimmunity
	Immune-related adverse events
	Patients with pre-existing autoimmunity
	Opportunities for precision medicine
	Management of immune-related adverse events
	Autoantibodies and immune-related adverse events
	Conclusions
	Acknowledgments
	Competing interests
	References
The evolving potential of precision medicine in the management of autoimmune liver disease
	Introduction
	History of autoimmune liver disease
	Spectrum of autoimmune liver disease
		Autoimmune hepatitis
		Primary biliary cholangitis
		Primary sclerosing cholangitis
		Overlap syndromes
	Laboratory biomarkers of autoimmune liver disease
		Serological markers for autoimmune hepatitis
		Serological markers of primary biliary cholangitis
		Serological markers of primary sclerosing cholangitis
	Challenges in differential diagnosis of autoimmune liver disease
	Development of precision medicine in autoimmune liver disease
	Conclusions
	Competing interests
	References
Precision medicine in autoimmune disease
	Introduction
	Precision medicine in the diagnosis and prognosis of autoimmune disease
	Precision medicine and the identification of co-morbidities in autoimmune disease
	Precision medicine in the treatment of autoimmune diseases
	Precision medicine in the evaluation of outcomes in autoimmune disease
	Precision medicine and prediction and prevention of autoimmune disease
	Autoantibodies and other factors are highly predictive of future rheumatoid arthritis (and other autoimmune diseases)
	Identification of meaningful biologic targets for prevention
	“Personalized medicine”—What should (and will) a person do to treat a current autoimmune disease, or prevent a future a ...
	Conclusions
	Disclosures
	References
Development of multi-omics approach in autoimmune diseases
	Introduction
	Translation of multi-omics into clinical application
	Types of omics technologies
		Epigenomics
		Transcriptomics
		Proteomics
		Metabolomics
		Immunogenomics
		Microbiomics
		Glycomics
		Other-omics fields
	Progress and success in autoimmunity
	Competing interests
	References
N-of-1 trials: Implications for clinical practice and personalized clinical trials
	Introduction
	Lessons learned from case reports and case series
	Complementary medicine approach
	Study designs
	Statistical considerations
	Ethics and insurance
	Regulatory aspects
	Conclusions
	References
Health risk assessment and family history: Toward disease prevention
	Background
		Genetic and environmental risk factors for autoimmune diseases
		Pathogenesis of autoimmune diseases
	Family history as a construct for prevention
		Assessing family history
		Scenarios for prevention based on family history
		Increased awareness and earlier diagnosis
		Relative and absolute risk
	Prevention strategies
		Primordial and primary prevention
		Cigarette smoking
		Low quality diet
		Excess weight
		Dental health management
	PRE-RA family study
	Pharmacologic prevention
		Drugs for primary prevention of RA
		Family history of RA and perception of pharmacologic interventions
		Drugs for secondary and tertiary prevention of RA
	Conclusions
	Financial support and sponsorship
	Conflict of interest
	References
Regulatory aspects of artificial intelligence and machine learning-enabled software as medical devices (SaMD)
	Introduction
	The Food and Drug Administration (FDA)’s perspective
		Regulatory aspects on artificial intelligence (AI)-enabled clinical decision support software
		Inadequacy of traditional 510(k) process for clearing AI/ML-enabled SaMD
		De-novo pathway for AI/ML SaMD
		The Pre-Certification (Pre-Cert) Program
		Status of those proposed program
		Examples of FDA cleared products using AI in healthcare
	CE mark and in-vitro diagnostic regulation
		Software qualification and classification under medical device regulation (MDR)
		In-vitro diagnostic regulation (IVDR)
	National Medical Products Administration—China
	Data privacy considerations around AI/ML-enabled software
		Health Insurance Portability and Accountability Act
		European Union’s General Data Protection Regulation
	Challenges to the manufacturers when AI/ML SaMD evolve
	Summary
	References
Precision medicine from the patient\'s perspective: More opportunities and increasing responsibilities
	Introduction
	Challenges of autoimmunity
	Technology and telemedicine
	Direct to consumer information and marketing
	The role of the general practitioner/primary care
	Education and communication
	Patient consulting organizations
	References
Index
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