century is complexity, Hood said. He described his vision for the convergence of systems biology and the “digital revolution” to transform medicine into an enterprise that he has termed “proactive P4 medicine,” in which P4 refers to predictive, preventive, personalized, and participatory.

Hood said that the digital revolution has provided three key elements that will play a central role in medicine going forward: (1) big datasets, (2) social and business networks that evolve from the knowledge gained from big datasets, and (3) digital personalized devices that will lead to the generation of a “quantized self.”

Hood predicted that in 10 years, each individual will be surrounded by a virtual data cloud of billions of data points from many different types of networks (e.g., genome, proteome, transcriptome, epigenome, phenome, single cells, transactional, telehealth, social media). Big datasets have a lot of noise, and we must be able to analyze the individual types of data and put them into higher meta-level structures that will increase the signal and reduce the noise. Then we will be able to integrate these data to make predictive and actionable models to guide and inform health and medicine, he said.

AN INTEGRATIVE SYSTEMS APPROACH TO BIOLOGY, MEDICINE, AND COMPLEXITY

Biological complexity comes from the random and chaotic process of Darwinian evolution. Evolution arises from random mutations, is driven by environmental challenges, and selects solutions building on past successes, Hood said. To understand how a complex system achieves its end goal, one has to define all of the elements present, their interconnectivity, and their dynamics. This is the essence of systems biology.

Hood described his personal involvement in four paradigm changes that led him to the conceptualization of P4 medicine. First, bringing engineering to biology catalyzed high-throughput biology (e.g., instruments for automated sequencing and synthesizing genes and proteins). High--throughput biology, he noted, was the beginning of large datasets in biomedical research. Second, automated sequencing led to the human genome project, which democratized genes (i.e., made them available to all biologists) and created a complete gene “parts list” that was essential for systems biology. Making automated sequencing a reality required a chemist, an engineer, a computer scientist, and a biologist, and Hood realized that the futures of biology and technology were intertwined. For the third



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